An Abstract of the Thesis Of

AN ABSTRACT OF THE DISSERTATION OF

Mei Song for the degree of Doctor of Philosophy in Food Science and Technology presented on June 8, 2017.

Title: Free Monoterpene Isomer Profiles in White Wine: Effect of Grape Variety, Region and Style and Impact on Odor Perception

Abstract approved:

______Elizabeth Tomasino

Monoterpenes are important volatile compounds to the aroma of many white wines. Many monoterpenes are chiral and found in wine as different isomers. These isomers (also known as enantiomers) are non-superimposable mirror images of each other, maintain the same molecular structure and in many instances possess different sensory characteristics. Much research in wine has investigated the contents of monoterpenes, but has largely overlooked the monoterpene enantiomer profiles and important roles of the different monoterpene enantiomers in wine.

Monoterpene enantiomer profiles in grapes and final wine are due to many factors, including genotype (grape variety), climate, temperature, soil type and winemaking technique. These compounds are of great interest to wine as they are related to the unique sensory identity of varietal wine. The aim of the project was to: firstly develop a robust and valid method for monoterpene enantiomer identification and quantitation, secondly investigate the effect of grape variety, growing region and wine style on the profiles of monoterpene enantiomers, thirdly determine the important role of

monoterpene isomer profiles in wine matrix and evaluate the effect of interactions between monoterpenes and other wine components on odor perception of wine.

The study presented the comprehensive exploration of monoterpene enantiomers

(S-(-)-limonene, R-(+)-limonene, (2R,4S)-(+)-cis-rose oxide, (2S,4R)-(-)-cis-rose oxide,

(2R,4R)-(-)-trans-rose oxide, (2S,4S)-(+)-trans-rose oxide, (2R,5R)-(+)-trans-linalool oxide, (2R,5S)-(-)-cis-linalool oxide, (2S,5S)-(-)-trans-linalool oxide, (2S,5R)-(+)-cis- linalool oxide, R-(-)-linalool, S-(+)-linalool, S-(-)-α-terpineol, R-(+)-α-terpineol, and R-

(+)-β-citronellol) in white wines from different grape varieties using head-space solid phase micro-extraction-multidimensional GC-MS (HS-SPME-MDGC-MS). In addition, it presented for the first time the varietal differences from monoterpene enantiomers and enantiomer fractions which were calculated by dividing the first eluting enantiomer by the total enantiomers of each compound (enantiomer pairs). Despite heterogeneity in vintages, regions, and styles, varietal wines could be clearly differentiated. Results have expanded upon the current knowledge of varietal distinctiveness based on isomer profiles and enantiomeric fraction.

Riesling wines possess very diverse flavors as the composition of grapes, can be altered by environmental characteristics and viticultural practices. Moreover, Riesling wines carry more stylistic variability in terms of residual sugar content, than any other major international white grape variety. Our study found that chiral monoterpene profiles and enantiomer fractions could be important factors to classify Riesling wines according to their geographical origin and style.

Sensory discrimination tests were performed to elucidate the interactions between monoterpene isomers at low concentrations and other wine components. The results imply that a combination of enhancing and suppression effects occur and impact the perception of monoterpene isomer profiles in Pinot gris wines. Furthermore, the effects of same monoterpene profiles differed according to the matrices, displaying the many interactions that occur and affect sensory perception.

The study on chiral monoterpenes in white wine not only expands our knowledge on monoterpene isomer analysis and distribution, but it provides information for varietal quality, by offering an objective measure of flavor quality. Additionally we have shown that when investigating sensory perception it is important to use a matrix as close to the original product and we further support that aroma compounds found at concentrations below their known perception thresholds can effect aroma perception.

Free Monoterpene Isomer Profiles in White Wine: Effect of Grape Variety, Region and Style and Impact on Odor Perception

by Mei Song

A DISSERTATION

submitted to

Oregon State University

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Presented June 8, 2017 Commencement June 2017

Doctor of Philosophy dissertation of Mei Song presented on June 8, 2017

APPROVED:

______Major Professor, representing Food Science & Technology

______Head of the Department of Food Science & Technology

______Dean of the Graduate School

I understand that my dissertation will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my dissertation to any reader upon request.

______Mei Song, Author

ACKNOWLEDGEMENTS

I would like to acknowledge all those people who have supported and helped me so much throughout my PhD program.

I would like to express the deepest appreciation to my advisor, Dr. Elizabeth

Tomasino, without her invaluable guidance and constant help this dissertation would not have been possible. She provided recommendations and instructions but also gave me intellectual freedom in my work, supported my attendance at various conferences, encouraged my scholarships application, and demanded a high quality of work has made me more independent and confident and enabled me to finish this dissertation effectively.

I am also very grateful to all committee members. Thanks to Dr. Claudio Fuentes for his encouragement and supervisory role on my statistical analysis during the study.

My thanks also go out to Dr. Michael Qian for his invaluable advice and feedback on my research design. I greatly appreciate the support from Dr. James Osborne on Pinot gris winemaking for my sensory study. A special thank goes to Dr. Benjamin Philmus, who was willing to serve as GCR in my final defense at the last moment.

My deep appreciation goes out to Nadine Skyllingstad for her assistance with my sensory panels, and bottling of wine. Many thanks to Ying Xia, Athena Loos, Akira

Kurniawan Ishii, and Hongyan Yu for their help with wine sampling and the residual sugar analysis in all of the wines investigated; Samuel Hoffman, Kiyomi Ide, Chase E

Jutzi, Anthony Le, and Vaishnavi Trivedi for their help with the sensory analysis in this study. In addition, thanks to my lab mates, Pallavi Mohekar, Jack Twilley, Anthony

Sereni and Quynh Phan for their friendship, help and support. Many thanks go out to Dr.

Robert McGorrin, Linda Hoyer, Linda Dunn, Holly Templeton, Debby Yacas, and

Christina Hull for their support and help during my PhD program.

I would also like to say a heartfelt thank you to my parents, in-laws and younger sister for always believing in me, supporting and encouraging me, dedicating their time taking care of my kids, providing the emotional support I needed to complete my dissertation. To them, I am eternally grateful.

Finally, I would like to thank my husband, Qing Yan who has been by my side throughout this PhD. He was always there cheering me up, listening to me, giving me suggestions through the good times and bad times. And thanks to my darling Ethan and

Christoph for being such good little kids, made me the happiest mom in the world. This dissertation would not have been possible without their warm love and endless support.

CONTRIBUTION OF AUTHORS

Chapter 1: Mei Song wrote Chapter 1 with revision from Dr. Elizabeth Tomasino.

Chapter 2: Dr. Elizabeth Tomasino and Mei Song conceived and designed the study. Acquisition, analysis and interpretation of data were performed by Mei Song. Dr. Elizabeth Tomasino and Mei Song participated in drafting the manuscript with revision from Dr. Elizabeth Tomasino.

Chapter 3: Dr. Elizabeth Tomasino and Mei Song conceived and designed the study. Acquisition, analysis and interpretation of data were performed by Mei Song. Mei Song drafted the manuscript with revision from Dr. Elizabeth Tomasino and Dr. Claudio Fuentes.

Chapter 4: Dr. Elizabeth Tomasino and Mei Song conceived and designed the study. Acquisition, analysis and interpretation of data were performed by Mei Song. Mei Song drafted the manuscript with revision from Dr. Elizabeth Tomasino and Dr. Claudio Fuentes.

Chapter 5: Dr. Elizabeth Tomasino, Dr. James Osborne and Mei Song conceived and designed the study. Acquisition, analysis and interpretation of data were performed by Mei Song. Mei Song drafted the manuscript with revision from Dr. Elizabeth Tomasino and Dr. Claudio Fuentes.

Chapter 6: Mei Song wrote chapter 6 with revision from Dr. Elizabeth Tomasino.

TABLE OF CONTENTS

Page

CHAPTER 1: Introduction ...... 1

1.1. Monoterpene chemistry ...... 3

1.1.1. General structure ...... 3

1.1.1.1. Acyclic monoterpenes ...... 3

1.1.1.2. Monocyclic monoterpenes ...... 4

1.1.1.3. Bicyclic monoterpenes ...... 4

1.1.1.4. Chiral monoterpenes ...... 5

1.1.2. Synthesis of terpenes ...... 6

1.1.2.1. Biosynthesis ...... 6

1.1.2.2. Biotransformation ...... 9

1.2. MonoterpeneS in grapes ...... 10

1.3. MonoterpeneS in wine ...... 11

1.4. Chemical analysis of monoterpenes in grapes and wine ...... 12

1.4.1. MDGC-MS to separate chiral compounds ...... 14

1.4.1.1. The origin of Multi-Dimensional Gas Chromatography (MDGC) ...... 15

1.4.2. MDGC characteristics ...... 16

1.4.2.1. Conventional MDGC ...... 17

1.4.2.2. Comprehensive gas chromatography GC×GC ...... 21

1.5. Wine terroir and monoterpene compounds ...... 23

1.6. Objectives ...... 23

CHAPTER 2: Investigation on the Quantitative Method for the Analysis of Chiral Mono- terpenes in White Wine by HS-SPME-MDGC-MS of Different Wine Matrix ...... 33

TABLE OF CONTENTS (Continued)

Page

2.1. Introduction ...... 35

2.2. Results and Discussion ...... 38

2.2.1. Separation of chiral mono-terpenes in MDGC-MS ...... 38

2.2.2. Validation of the quantitative method ...... 38

2.2.2.1. Linearity of calibration curve in different wine matrix ...... 38

2.2.2.2. Limit of Detection (LOD), Limit of Quantitation (LOQ), wine reproducibility and internal standards stability ...... 41

2.2.2.3. Accuracy ...... 41

2.2.2.4. Temperature stability ...... 42

2.2.3. Wine analysis ...... 42

2.3. Experimental Section ...... 46

2.3.1. Chemicals ...... 46

2.3.2. d3-Limonene synthesis ...... 47

2.3.2.1. Synthesis of 4-acetyl-1-methyl cyclohexene ...... 47

2.3.2.2. D3-limonene synthesis ...... 47

2.3.3. Sample preparation ...... 48

2.3.4. Solid phase micro-extraction coupled with MDGC-MS...... 48

2.3.5. Validation of the quantitative method ...... 50

2.3.5.1. Linearity of calibration curve in different wine matrix ...... 50

2.3.5.2. Limit of Detection (LOD), Limit of Quantitation (LOQ), wine reproducibility and internal standards stability ...... 51

2.3.5.3. Accuracy ...... 52

TABLE OF CONTENTS (Continued)

Page

2.3.5.4. Temperature stability ...... 52

2.3.6. Chiral mono-terpene contents in 12 white wines ...... 52

2.3.7. Data analysis ...... 53

2.4. Conclusions ...... 53

CHAPTER 3: Free Monoterpene Isomer Profiles of Eight Vitis Vinifera L. cv. White Wines ...... 73

3.1. Introduction ...... 75

3.2. Materials and methods ...... 76

3.2.1. Chemicals ...... 76

3.2.2. Samples ...... 77

3.2.3. Sample Preparation ...... 77

3.2.4. Head Space Solid Phase Micro-Extraction Coupled with MDGC-MS (HS-SPME-MDGC-MS) ...... 78

3.2.5. Statistical Analysis ...... 79

3.3. Results ...... 79

3.3.1. Varietal Wines ...... 79

3.3.2. Monoterpene Content in Varietal Wines ...... 80

3.3.3. Classification of the Grape Variety and Wine Style Based on Monoterpene Isomer Concentrations ...... 82

3.3.4. Enantiomer Fraction (EF) in Varietal Wines ...... 83

3.3.5 Classification of the Grape Variety and Wine Style Based on Enantiomer Fractions ...... 86

3.4. Discussion ...... 87

TABLE OF CONTENTS (Continued)

Page

CHAPTER 4: Chemo-diversity in chiral monoterpenes of Riesling wine from different regions and wine styles ...... 121

4.1. Introduction ...... 123

4.2. Materials and methods ...... 125

4.2.1. Chemicals ...... 125

4.2.2. MDGC-MS/SPME/wine preparation ...... 126

4.2.3. Wine ...... 127

4.2.4. Statistical analysis ...... 128

4.3. Results and discussion ...... 128

4.3.1. Separation and identification of chiral monoterpenes in Riesling wines ...... 128

4.3.2. Quantification of chiral monoterpenes in Riesling wines at regions and styles ...... 129

4.3.3. Discriminant plot (DA) on concentration of monoterpene isomers of Riesling wines in regions and styles ...... 130

4.3.4. Quantification of enantiomer fractions in Riesling wines by region and style ...... 132

4.3.5 Discriminant plot on monoterpene enantiomer fractions of Riesling wines in regions and styles...... 134

4.4. Conclusion ...... 135

CHAPTER 5: Odor perception interactions between free monoterpene isomers and wine composition of Pinot gris wines ...... 150

5.1. Introduction ...... 153

5.2. Materials and methods ...... 156

5.2.1. Wine samples ...... 156

TABLE OF CONTENTS (Continued)

Page

5.2.2. Chemicals ...... 156

5.2.3. Monoterpene compositions of Pinot gris wines ...... 157

5.2.4. Wine matrix preparation ...... 158

5.2.5. Sensory analysis ...... 159

5.2.5.1. Participants ...... 159

5.2.5.2. Stimuli ...... 159

5.2.5.3. Triangle test procedure ...... 160

5.2.6. Statistical Analysis ...... 161

5.3. Results and discussion ...... 161

5.3.1. Mean concentrations of monoterpene isomers in Pinot gris wines ...... 161

5.3.2. Monoterpene isomer profiles classification ...... 163

5.3.3. Sensory results ...... 164

5.4. Conclusions ...... 168

CHAPTER 6: General conclusion and future work ...... 181

6.1. General Conclusion ...... 181

6.2. Future Work ...... 184

Bibliography ...... 185

LIST OF FIGURES

Figure Page

Figure 1.1. Terpene building blocks ...... 2

Figure 1.2. Schematic example of mono- and bicyclic monoterpenes ...... 4

Figure 1.3. Linalool enantiomer structure...... 5

Figure 1.4. Scheme of the biogenesis of monoterpenes...... 7

Figure 1.5. The reaction mechanisms of all monoterpenes start with the ionization of GPP ...... 8

Figure 1.6. Postulated biotransformation of linalool with fungi ...... 9

Figure 1.7. Example structure of free form S-linalool and S-linalool-glucopyranoside ...... 10

Figure 1.8. Structure of β-cyclodextrin ...... 14

Figure 1.9. Basic dean switch setup ...... 16

Figure 1.10. Schematic of connection of two columns ...... 18

Figure 1.11. Left—compounds heart-cut in the first column was trapped in one cold trap; Right-- compounds heart-cut in the first column were trapped into separate sample reservoirs ...... 18

Figure 1.12. Different online heart cut systems coupled with two column ...... 19

Figure 1.13. MDGC system with a switching device, one or two GC ovens and two detectors ...... 20

Figure 1.14. MDGC system based on Deans type pressure balancing ...... 21

Figure 1.15. Comprehensive gas chromatography method ...... 22

Figure 2.1. Separation of chiral monoterpenes and deuterium isotopes mixture using MDGC-MS ...... 70

Figure 2.2. PCA plot of 12 white wines on concentration of chiral mono-terpenes...... 71

Figure 2.3. Chemical structures of the chiral monoterpenes isomers ...... 72

LIST OF FIGURES (Continued)

Figure Page

Figure 3.2: Discriminant plot of varietal wines on concentration of monoterpene isomers ...... 110

Figure 3.3: Discriminant plot of wine style on concentration of monoterpene isomers...... 111

Figure 3.4: X-Y scatterplots of enantiomer pair concentrations (µg/L) in all varietal wines with fitted lines and adjusted R2 ...... 112

Figure 3.5: Discriminant plot of grape variety and wine style on monoterpene enantiomer fractions...... 113

S 3.2. A-B, a chromatograph of the monoterpene isomers in one Torrontes varietal wine from MDGC-MS. A-30 min to 63 min (small spectrum with selected ions of S-(-)- limonene, (2R, 4R)-(-)-trans-rose oxide, and (2R, 5S)-(-)-cis-linalool oxide attached due to co-eluted with other compounds), B-63 min to 87 min...... 115

S 3.4. Monoterpene isomers vector loadings for varietal wines classification by discriminant analysis ...... 118

S 3.6. X-Y scatterplots of enantiomer pair concentrations (µg/L) in all varietal wines with fitted lines and adjusted R2 ...... 120

Figure 4.1. Mean concentrations of chiral monoterpene isomers in Riesling wines (µg/L)...... 146

Figure 4.2. Discriminant plot on concentration of chiral monoterpene contents of Riesling wines in regions and styles...... 147

Figure 4.3. X-Y scatterplots of enantiomer pair concentrations (µg/L) in the 4 regions with fitted lines...... 148

Figure 4.4. Discriminant plot on monoterpene enantiomer fractions of Riesling wines in regions and styles...... 149

Figure 5.1. Mean concentration of monoterpene isomers from 46 Pinot gris wines...... 178

LIST OF TABLES

Table Page

Table 2.1. Calibration curve information of 15 chiral mono-terpenes in different de- aromatized wine matrices ...... 61

Table 2.2. LOD, LOQ, percent spiked recovery, reproducibility and standard stability for wine samples with different matrix ...... 62

Table 2.3. Average variation (peak area ratio) of seven mono-terpene standards based on injection and extraction temperature ...... 63

Table 2.4. Multiple Comparisons (Tukey) of the average concentration of 12 chiral mono-terpenes for 12 white wines ...... 64

Table 2.5. Odor descriptors, purity, CAS# and perception threshold (µg/L) for chemical standards ...... 66

Table 2.6. Six point concentration of each compound for calibration ...... 68

Table 2.7. Riesling and Pinot Gris white wine samples from different regions ...... 69

Table 3.1. Distribution of varietal wines across, region of origin, vintage and wine style ...... 101

Table 3.2. Mean concentrations of isomers*± standard error from different varietal wines (µg/L) using ANOVA with Tukey’s HSD (α= 0.05) ...... 104

Table 3.3. GLM multivariate test investigating varietal and style effects ...... 106

Table 3.4. Enantiomer fractions (EFs)* ± standard error found in different varietal wines determined by ANOVA and Tukey’s HSD (α= 0.05) ...... 107

Table 3.5. The R2 value and slope for the fitted line in the X-Y scatterplots of Figure 3.4 ...... 108

S 3.1. Quantifier and qualifier ions selected for monoterpene isomers ...... 114

S 3.3. Limit of detection (LOD)/2 for monoterpene isomers (µg/L) and the number of wines with non-detectable isomer ...... 116

S 3.5. Structure matrix of variable correlations for wine styles classification by discriminant analysis ...... 119

Table 4.1. Distribution of Riesling wines across region of origin, vintage and wine style...... 142

LIST OF TABLES (Continued)

Table Page

Table 4.2. Effect of region and style on chiral monoterpene contents for Riesling determined by ANOVA and Tukey’s HSD (α= 0.05)...... 143

Table 4.3. Effect of region and style on enantiomer fraction for Riesling determined by ANOVA and Tukey’s HSD (α= 0.05)...... 145

Table 5.1. Selection of 46 bottles of Pinot gris wines...... 175

Table 5.2. Profiles of monoterpene isomers in Pinot gris wines (µg L-1)*...... 176

Table 5.3. d’ value between added samples and control in the 10 monoterpene profiles through 3 matrices performed by z-test...... 177

S 5.1. Working standards (WS) for sensory test (mg L-1)...... 179

S 5.2. Limit of detection (LOD)/2 for monoterpene isomers (µg L-1) and the number of wines with non-detectable isomer...... 180

CHAPTER 1

INTRODUCTION

The term terpenes originate from turpentine (lat. Balsamum terebinthinae) referred to as ‘resin of pine trees’. A pleasant floral and fruity note is emitted from cutting or carving the bark or the new wood of several pine tree species, which is attributed to terpenes (Breitmaier, 2006a).

There are many different terpene compounds, with more than 30,000 found throughout nature (De Carvalho & da Fonseca, 2006). These compounds are the most abundant compound class in natural and are found with a wide assortment of structural types, including monoterpenes (C10), sesquiterpenes (C15), diterpenes (C20) and triterpenes (C30) (Figure 1.1) (Degenhardt et al., 2009). Different enzymes, known as terpene synthases, produce multiple structures that result in terpene diversity. For example, a single (+)-sabinene synthase from Salvia officinalis, also known as sage, produces 63% (+)-sabinene, 21% c-terpinene, 7.0% terpinolene, 6.5% limonene and 2.5% myrcene (Wise et al., 1998)

Figure 1.1. Terpene building blocks (adapted from (Breitmaier, 2006b))

Monoterpenes are primarily found in plants and have many ecological roles. They act as deterrents against feeding by herbivores, have antifungal properties and are attractants for pollinators (Langenheim, 1994). In mammals, terpenes stabilize cell membranes, and have a role in many metabolic processes by regulating enzymatic reactions (Kannan & Bastas, 2015). Terpenes are of interest for their potential health benefits to humans as they play potential roles in prevention and therapy of several diseases, e.g. cardiovascular diseases (Santos et al., 2011) and inflammatory airway diseases (Juergens, 2014); act as natural insecticides and antimicrobial agents (Reis et al.,

2016); inhibit sprouting during potato storage; are used in the synthesis of natural aroma chemicals (Demyttenaere & De Kimpe, 2001); and are used to clean electronic components, cables, and aircraft parts (Brown et al., 1992). Lastly, they are well known and used extensively as fragrances and flavors.

1.1. MONOTERPENE CHEMISTRY

1.1.1. General structure

About 30,000 terpenes are presently known (A.A. Newman (Hrsg.), 1972;

Goodwin, 1971; Hill, 1991; Pinder, 1960; Templeton, 1969). In nature, terpenes occur predominantly as hydrocarbons, alcohols, ethers, aldehydes, ketones, carboxylic acids and esters. Terpenes are built from isoprene units as described by Ruzicka and Wallach

(Figure 1.1) (Croteau, 1998). Monoterpenes specifically contain two isoprene units that result in mono-(C10) carbon skeletons.

1.1.1.1. Acyclic monoterpenes

Linear arrangements of two isoprene units lead to the formation of acyclic monoterpenes, e.g. geraniol and β-citronellol. Further rearrangements and oxidation result in the formation of linalool, citral, citronellol and others (Bauer et al., 2008). They are found primarily in marijuana, mangos, hops, and lemon grass (Breitmaier, 2006a).

1.1.1.2. Monocyclic monoterpenes

In addition to linear arrangements of acyclic monoterpenes, the isoprene units can undergo cyclization and rearrangement to form six-membered rings, found in limonene.

Monocyclic monoterpenes are found widely in citrus, rosemary, juniper, and peppermint

(Figure 1.2) (Breitmaier, 2006a).

1.1.1.3. Bicyclic monoterpenes

Bicyclic monoterpenes are formed from two sequential cyclization reactions of geranyl diphosphate, resulting in compounds such as pinene. Pinene is the primary constituent of pine resin (Coppen et al., 1983). Bicyclic monoterpenes can be classified into five categories including Thuyanes, Caranes, Pinanes, Camphanes-isocamphanes and

Fenchanes (Figure 1.2) (Breitmaier, 2006a).

Figure 1.2. Schematic example of mono- and bicyclic monoterpenes (adapted from (Shahidi et al., 1999))

1.1.1.4. Chiral monoterpenes

Many monoterpenes are chiral molecules which are non-superimposable mirror images of each other, called enantiomers (Figure 1.3). Chiral monoterpenes have at least one chiral center (for example, linalool has one chiral center with two enantiomers).

Enantiomers share the same chemical formula and 2D chemical structure; however, they can differ by optical activity, their odor quality and/or odor intensity. For example, R-(-)- linalool has an aroma described as woody or lavender, while S-(+)-linalool has a sweet, petigrain-like aroma (Lehmann et al., 1995; Peña et al., 2005c). Enantiomer pairs also typically have very different perception thresholds, the concentration at which a compound has a noticeable aroma. R-(-)-linalool (perception threshold of 0.8 µg/L) is perceived at concentrations 10 times lower than S-(+)-linalool (7.4 µg/L) (Padrayuttawat et al., 1997a).

Chiral center Mirror plane Mirror

Figure 1.3. Linalool enantiomer structure

1.1.2. Synthesis of terpenes

1.1.2.1. Biosynthesis

Acetyl-coenzyme A, also known as activated acetic acid, is the biogenetic precursor of terpenes in eukaryotes, some plants also use non-mevalonate pathway in plastids (J.W.

Porter et al., 1981). It undergoes several reactions, including Claisen condensation, aldol reaction, enzymatic reduction, phosphorylation, de-carbonation and dehydration to form isopentenyl pyrophosphate (IPP). IPP is further isomerized to γ,γ-dimethylally- pyrophosphate (DMAP). Two of these isomers bind and form geranyl pyrophosphate

(GPP) a direct precursor of monoterpenes (Breitmaier, 2006a) (Figure 1.4). Subsequent reactions including cyclization, hydride shift and rearrangement of GPP in the presence of terpene synthases form many different monoterpenes (Figure 1.5 A and B). Many monoterpenes are formed through enzymatic reactions (terpene synthases) or through chemical reactions (Degenhardt et al., 2009; Dudareva et al., 2004).

activated acetic acid biological acetoacetyl-CoA CLAISEN-condensation (biological CoA acetoacetic acid CoA CoA ester) nucleophile electrophile biological aldol reaction H2O HSCoA CoA

β-hydroxy-β-methyl-glutaryl-CoA

HO2C CoA

(NADPH+H+) -HSCoA

(R)-mevalonic acid HO2 OH

(ATP)

Mevalonic acid diphosphate HO2 OPP

-CO2, -H2O

isopentenyl-pyrophosphate (Isomerasee) (activated isoprene) OPP OPP γ,γ-dimethylallyl-pyrophosphate

-HOPP

geranylpyrophosphate OPP (monoterpene)

Figure 1.4. Scheme of the biogenesis of monoterpenes (adapted from (Breitmaier, 2006a))

Figure 1.5. The reaction mechanisms of all monoterpenes start with the ionization of GPP (Adapted from (Degenhardt et al., 2009)).

1.1.2.2. Biotransformation

Monoterpenes may also be diversified through biotransformation. Approximately three-fourth of biocatalyst studies from the last decade have used biotransformation from fungi or bacteria to synthesize terpenes (De Carvalho & da Fonseca, 2006). Linalool was biotransformed with Aspergillus niger DSM 821, Botrytis cinerea 5901/02, and B. cinerea 02/FBII/2.1 to produce different isomers of lilac aldehyde and lilac alcohols or linalool oxides (Figure 1.6) (Mirata et al., 2008).

Figure 1.6. Postulated biotransformation of linalool with fungi (adapted from (Mirata et al., 2008), AN1, Aspergillus niger ATCC 16404; AN2, A. niger DSM 821; BC1, Botrytis cinerea 5901/2; BC2, B. cinerea 02/FB II/2.1; CC1, Corynespora cassiicola DSM 62475).

1.2. MONOTERPENES IN GRAPES

Wine is highly complex and contains mouthfeel, taste and aroma compounds.

Wine flavor is an important indicator of wine quality. Although many aroma compounds occur at trace levels, such as monoterpenes, they play significant roles in wine quality.

Unlike many other wine aromatics, monoterpenes are primarily derived from grapes and are mainly located on the grape skin (R. S. Jackson, 2009). Monoterpenes may be free (unbound to sugars) or glycosidically bound. Only those that occur as free forms contribute to wine fragrance and are aromatically active (Figure 1.7).

Figure 1.7. Example structure of free form S-linalool and S-linalool-glucopyranoside (adapted from (Raguso & Pichersky, 1999)).

Monoterpenes are responsible for the varietal distinctiveness of many aromatic grape varieties, such as Muscat, Gewurztraminer and Riesling (C. Strauss et al., 1987).

The aroma importance of monoterpenes and their derivatives have been summarized in several reviews (Bayonove & Cordonnier, 1971; Drawert & Rapp, 1966, 1968; Peynaud

& Ribereau-Gayon, 1971; Suomalainen, 1983). Linalool is responsible for the slightly fruity note in Riesling grapes (VanWyk et al., 1967), and is the typical aroma of Muscat

Alexandrie grapes (Bayonove & Cordonnier, 1970a, 1970b). Other research has found that the aroma of Muscat grapes can be attributed to the presence of different terpene compounds: linalool, nerol, geraniol, α-terpineol and four linalool-oxides (Ribéreau-

Gayon et al., 1975).

Monoterpene content reaches the highest concentrations shortly after commercial harvest and then decreases should berries become overripe. Ripening conditions, especially temperature and solar exposure, are linked to formation of monoterpenes

(Belancic et al., 1997; Tingey et al., 1980). It appears that monoterpene accumulation occurs as a stress response or acceleration of metabolic reaction rates by temperature increase or solar exposure (Crippen & Morrison, 1986). Grape infected by B. cinerea reduces linalool or terpenen-4-ol content and modifies linalool to other monoterpenes, such as linalool oxides, geraniol and α-terpineol (Bock et al., 1988; Shimizu et al., 1982).

1.3. MONOTERPENES IN WINE

During fermentation and aging, wine monoterpene content changes significantly

(Rapp & Guntert, 1986). These changes and rearrangements of monoterpenes include: hydrolysis of glyosidic bonds; oxidation of monoterpene alcohols to oxides; and cyclization and transformation into ketones. For example, during yeast metabolism, the two different reductive pathways known for rose oxides could be manipulated and

12 resulted in a change in rose oxide content (Koslitz et al., 2008). Linalool can undergo several changes, oxidized to linalool oxide or degraded by Botrytis cinerea (Bock et al.,

1986). These changes affect odor quality as the sensory thresholds for the newly formed monoterpene compounds are quite different (R. Jackson & Jackson, 2009). For example, linalool oxide, formed due to linalool oxidation, has a higher sensory threshold compared to linalool.

Monoterpenes are primarily derived from grapes and affected by fermentation.

Therefore monoterpene profiles including linalool oxide, linalool, hotrienol, nerol oxide, and citronellol have been used for varietal and place of origin classification (Calleja &

Falqué, 2005; Rapp, 1990; Schreier & Jennings, 1979; Zamuz & Vilanova, 2006).

Terpenes are important to differentiate varietal wines (Rapp et al., 1976; Rapp et al.,

1978; Schreier et al., 1976). Schreier et al. (1977) identified and measured the largest monoterpene components in German wines, including concentrations of linalool, hotrienol, cis-linalool oxide and α-terpineol. Linalool, nerol, geraniol, terpineol, linalool oxide, rose oxide, and nerol oxide have been used to differentiate Muscat wines from different regions (Versini et al., 1990a; Vilanova et al., 2013; Wagner et al., 1977;

Williams et al., 1981).

1.4. CHEMICAL ANALYSIS OF MONOTERPENES IN GRAPES AND WINE

Measurement of monoterpenes can be challenging. Despite the important aroma impact concentrations can be low and these compounds are considered minor

13 components of many wines, with concentrations of total monoterpenes as low as 0.5 mg/L in Riesling wines (Simpson & Miller, 1983).

Enantiomer separation can be traced to the 1800’s with Pasteur’s separation of tartaric acid enantiomers in wine (S. Ebeler et al., 2001c; Gal, 2008; Mason, 1986;

Vallery-Radot, 1885). Derivatization of enantiomers with a chiral reagents forming diastereomer complex was an early technique that was used to separate enantiomers on an achiral stationary phase. However this technique had limitations, for example the racemization of a chiral auxiliary during derivatization procedure usually results in impurity of diastereomers (S. Ebeler et al., 2001a).

GC and GCMS techniques have played fundamental roles in flavor chemistry for over half a century and are now the standard for measuring aroma compounds in wine

(Flamini & Traldi, 2009). In the mid 1960’s, chiral amide-based GC stationary phases were introduced for direct separation of enantiomers, these columns allowed for excellent separation of amino acids but had limited application for analysis of most volatile compounds (S. Ebeler et al., 2001a). In the late 1970’s and 1980’s, chiral cyclodextrin-based GC stationary phases provided chemists with direct separation of many chiral aroma compounds (S. Ebeler et al., 2001a).

β-Cyclodextrin is cyclic, chiral and torus-shape molecule with seven α-D-glucose units linked together (Figure 1.8). For gas chromatographic applications, the hydroxyl groups on the glucose units are usually derivatized to improve chromatographic properties. The β-cyclodextrins can bind with enantiomers to form inclusion complexes

14 which possess different charges, shape and size, resulting in enantiomeric separation

(Jung et al., 1994).

Figure 1.8. Structure of β-cyclodextrin (adapted from (Snor et al., 2007))

Cyclodextrin stationary phases have been used to separate 3,4-dihydro-3- oxoedulans enantiomers in Riesling wine (Schmidt et al., 1995) and wine lactone isomers

(3a, 4, 5, 7a-tetrahydro-3,6-dimethylbenzofuran-2(3H)-one) in Gewurztraminer wine

(Guth, 1996).

1.4.1. MDGC-MS to separate chiral compounds

Single column gas chromatography has been one of the outstanding research separation tools with high peak capacities. However, ambiguous or problematic peak identification can occur with complex samples, such as food matrices, crude oil

(Brunnock, 1969; Mondello, 2002), and essential oils (Herrero, 2009). Multidimensional gas chromatography (MDGC) or two-dimensional GC has been introduced resulting in

15 increasing peak capacity and speed of analysis (Mondello, 2002). MDGC is consequently well suited to the analysis of target compounds or selected groups of compounds present in complex matrices. An additional advantage of MDGC is that a large concentrated injection in the first chromatographic column still could obtain a perfect chromatographic separation in the second analytical column, so that method detection limits can be improved (Campo, 2007; Mondello, 2002).

Research using MDGC has investigated the origin and authenticity of wine by determining the enantiomeric ratios of terpineol, linalool and the furanoid linalool oxides

(C. Askari et al., 1991). MDGC-MS was also applied for monoterpene metabolism in grapes by He et al. (He & Beesley, 2005).

1.4.1.1. The origin of Multi-Dimensional Gas Chromatography (MDGC)

The origin of multidimensional chromatography lies in the development of paper chromatography (Consden, 1944) and two-dimensional thin-layer chromatography (TLC)

(Kirchner, 1951; Stahl, 1967). The major break within two-dimensional system is the basic principle of pressure switching device introduced by Deans (1968). The basis of the method is to control carrier gas flow by using pressure balancing at junctions with solenoid valves which has subsequently been used extensively for heart-cutting, venting and back-flushing (Figure 1.9) .

Figure 1.9. Basic dean switch setup (adapted from (Boeker et al., 2013))

Early uses of MDGC analysis, dating back to the 1960s, were within the oil and feedstock industries (Brunnock, 1969). The first significant industrial application of

MDGC in 1971 was derived from the PIONA analysis (paraffins; isoparaffins; olefins; naphalenes; aromatics) (Mondello, 2002) and the famous planar separation reported by

O’Farrell in 1975. The MDGC double-oven system, that holds independent temperatures at the first and second column, was applied by Fenimore et al. (1973). The two- dimensional GC involving two columns was introduced by Liu and Phillips (1991) in the early 1990s.

1.4.2. MDGC characteristics

Two main types of MDGC have been used to date: conventional MDGC and the comprehensive two-dimensional GC×GC (Cai, 2009). Comprehensive GC×GC is a high-

17 throughput application resulting in better compound separation, as it provides greater peak capacity and is less time-consuming. Conventional MDGC is considered more useful for analysis of specific compounds, such as those measured in environmental analysis (Pažitná, 2013; Sciarrone, 2010), crude oil studies (Bertoncini, 2005), insect odors (Botezatu, 2013) and food science (Herrero, 2009; A. L. Robinson, Refidaff, C.,

Robinson, A.L., Boss, P.K., Solomon, P.S., Heymann, H. and Ebeler, S.E., 2014).

1.4.2.1. Conventional MDGC

The concept of conventional MDGC lays in allowing the partially separated fractions in the first GC to be reinjected onto the second GC, which increases the signal- to-noise (S/N) ratio as a result of the focusing effect at the modulator. It can be used together with many detectors (mass spectrometry, atomic emission, Fourier transform infrared (FTIR), diode array detection and the like) (Pažitná, 2013).

Direct coupling or pressure tuning in GC, such as multiple heart-cuts into one storage reservoir, is applied to introduce the solute into the second dimension (Figure

1.10). The second separation dimension can be a single chromatographic analysis (with single cryotrap in GC) or separate storage devices with discrete analysis of each (Figure

1.11).

Figure 1.10. Schematic of connection of two columns (adapted from (Marriott, 2012)).

Figure 1.11. Left—compounds heart-cut in the first column was trapped in one cold trap; Right-- compounds heart-cut in the first column were trapped into separate sample reservoirs (adapted from (Marriott, 2012)).

Continuous transfer of the effluent or selected fractions, or cuts from the first column to the subsequent one is crucial. This can be achieved by operating carrier gas flow to divert the fractions to an exit (venting) or reversed for back-flushing. Resolution is improved with the heart-cutting technique (Bertoncini, 2005). An on-line heart cut

(Figure 1.12), which allows the transportation of only some key analytes from the first to the second column, could be done using either a valve or a pneumatic switcher (Herrero,

2009; Pažitná, 2013).

Figure 1.12. Different online heart cut systems coupled with two column (adapted from (Herrero, 2009))

Figure 1.13. MDGC system with a switching device, one or two GC ovens and two detectors (adapted from (Herrero, 2009; Pažitná, 2013)).

A complete description of the cryotrap modulator (Figure 1.13) is as follows: solutes from the first column move towards a cryogenically cooled zone and are refocused in a narrow band, thus eliminate the dispersion effect, afterwards the focused zone is exposed and released to a thermal environment. It is estimated that the component release time is 30 ms (Fullana, 2005).

A more sophisticated switching method for carrier gas flow has been introduced compared to the original Dean’s switch (Deans, 1968): the valve less deans type interface or “live switching” between columns (Figure 1.14). In Figure 1.14, two modes are described. The arrows show the direction of the carrier gas: the white arrows correspond to venting mode and the black ones to heart cutting mode respectively. The 6-port valve switching controls the effluent eluting from the primary column and is vented to the FID detector during venting mode. During cut mode, the 6-port valve switching also can

21 create a flow inversion in the interface and introduces a small part of the effluent into the secondary column attached to another detector during the cut (Bertoncini, 2005).

Figure 1.14. MDGC system based on Deans type pressure balancing (adapted from (Bertoncini, 2005)).

1.4.2.2. Comprehensive gas chromatography GC×GC

New developments in MDGC are still occurring. Comprehensive GC×GC is one such development and is achieved by the hyphenation of two columns of different polarity so that independent “orthogonal” separations can be obtained. In GC×GC, the whole first dimension effluent is transferred onto a second column without affecting the second dimension analysis (Figure 1.15). In this technique, the second column elution

Figure 1.15. Comprehensive gas chromatography method (adapted from (Marriott, 2012)).

time must be shorter than the first column, thus ensuring that each compound elution to the second column is completed before the subsequent is introduced.

The modulators acts as the interface between the two dimensions and plays a major function that increases the amplitude of the signal and facilitates transfer of compounds to the second dimension by entrapping and releasing smaller and more manageable portions. Two main kinds of modulators have been reported: flow switching modulators which operate as high frequency division valves, and thermal modulators which are divided into three groups; heat, cryogenic and jet pulsed modulators. Thermal modulators are more expensive and harder to maintain than valve modulators, but are more widely found as they can be used for many applications and result in better separation (Herrero, 2009).

1.5. WINE TERROIR AND MONOTERPENE COMPOUNDS

Important aroma compounds from grapes play decisive roles in the varietal and regional character of wines (Ribéreau-Gayon et al., 2000). For example, the aromatic grape variety Muscat produces wines with characteristic aromas corresponding to the

Muscat grape variety. Rapp and Hastrich (1978) have shown that the ratios among the various monoterpenes can be used to distinguish not only one cultivar from another but also by region or origin (Rapp et al., 1978). Such ‘terpene profiles’ are useful for the separation of Riesling wines from others so-called “Rieslings” (e.g. Welsch Riesling, Kap

Riesling, Emerald Riesling) but not produced from true Riesling. Rapp (1998) reported a significant analytical differentiation between Riesling and Welsch Riesling from different growing regions (Austria, Italy and Yugoslavia) based on terpene profiles, which indicated that monoterpene constituents contribute to varietal differences. Specifically, significant higher concentrations of selected monoterpene compounds (e. g. linalool, trans-linalool oxide, α-terpineol) were present in true Riesling wines compared with

Welsch Riesling (Rapp, 1998).

1.6. OBJECTIVES

Monoterpene compounds have been emphasized as important aroma compounds in aromatic white wines, such as Riesling (M. Dziadas, Jeleń, H.H., 2010; S. K. a. N.

Park, A.C., 1993; Skinkis, 2008) and Gewurztraminer (Marai, 1987; S. K. a. N. Park,

A.C., 1993; Skinkis, 2008). However, enantiomers of monoterpene compounds

24 possessing different aroma descriptors have been little explored. In addition, the influence of monoterpene enantiomers on odor perception of wines is still unknown. The purpose of the project is to widely explore the monoterpene isomers or enantiomers, and to investigate the importance of monoterpene isomer profiles to wine aroma. Therefore, the objectives of this project are as follows:

 Develop a method to measure monoterpene isomers in wine

 Investigate the profiles of monoterpenes in varietal wines

 Investigate the profiles of monoterpenes in Riesling from different regions

and styles

 Determine impact of monoterpenes to odor perception of Pinot gris wines.

Conventional MDGC-MS was accessible and used in our study. Heart cut-

MDGC-MS analyses were performed using Shimadzu GC-2000 plus with a split/splitless injector coupled to Shimadzu QP 2010 GC-mass spectrometer using a dean switch.

Monoterpenes are very important characteristic aroma compounds in white wines. The study was performed using conventional MDGC-MS on monoterpene chemical profile through grape variety, region and wine style in white wines, and using discrimination test on sensory impact of monoterpenes in Pinot gris wine.

REFERENCES

A.A. Newman (Hrsg.). (1972). Chemistry of terpenes and terpenoids. Academic Press.

Askari, C., Hener, U., Schmarr, H.-G., Rapp, A., & Mosandl, A. (1991). Stereodifferentiation of some chiral monoterpenes using multidimensional gas chromatography. Fresenius' Journal of Analytical Chemistry, 340(12), 768-772.

Bauer, K., Garbe, D., & Surburg, H. (2008). Common fragrance and flavor materials: preparation, properties and uses: John Wiley & Sons.

Bayonove, C., & Cordonnier, R. (1970a). Recherches sur l'arôme du muscat. I. Evolution des constituants volatils au cours de la maturation du Muscat d'Alexandrie. Ann. Technol. Agric, 19(2), 79-93.

Bayonove, C., & Cordonnier, R. (1970b). Recherches sur l'arome du muscat. II. Profils aromatiques de cepages muscat et non muscat. importance du linalol chez les muscats. Ann Technol Agr.

Bayonove, C., & Cordonnier, R. (1971). Le linalol, constituant important mais non specifique des muscats. Comptes Rendus de l ‘Academie d’Agriculture de France, 1374- 1377.

Belancic, A., Agosin, E., Ibacache, A., Bordeu, E., Baumes, R., Razungles, A., & Bayonove, C. (1997). Influence of sun exposure on the aromatic composition of Chilean Muscat grape cultivars Moscatel de Alejandria and Moscatel rosada. American Journal of Enology and Viticulture, 48(2), 181-186.

Bertoncini, F., Vendeuvre, C. and Thiébaut, D. (2005). Interest and applications of multidimensional gas chromatography for trace analysis in the petroleum industry. Oil & gas science and technology, 60(6), 937-950.

Bock, G., Benda, I., & Schreier, P. (1986). Biotransformation of linalool by Botrytis cinerea. Journal of Food Science, 51(3), 659-662.

Bock, G., Benda, I., & Schreier, P. (1988). Microbial transformation of geraniol and nerol by Botrytis cinerea. Applied Microbiology and Biotechnology, 27(4), 351-357.

Boeker, P., Leppert, J., Mysliwietz, B., & Lammers, P. S. (2013). Comprehensive theory of the deans’ switch as a variable flow splitter: fluid mechanics, mass balance, and system behavior. Analytical Chemistry, 85(19), 9021-9030.

Botezatu, A. I., Kotseridis, Y., Inglis, D., Pickering, G.J. (2013). Occurrence and contribution of alkyl methoxypyrazines in wine tainted by. Journal of the Science of Food and Agriculture, 93(4), 803-810.

Breitmaier, E. (2006a). Terpenes: flavors, fragrances, pharmaca, pheromones: John Wiley & Sons.

Breitmaier, E. (2006b). Terpenes: Importance, general structure, and biosynthesis. Terpenes: Flavors, Fragrances, Pharmaca, Pheromones, 1-9.

Brown, L. M., Springer, J., & Bower, M. (1992). Chemical substitution for 1, 1, 1- trichloroethane and methanol in an industrial cleaning operation. Journal of Hazardous Materials, 29(2), 179-188.

Brunnock, J. V. a. L., L.A. (1969). Separation of naphthenes and paraffins on an alkali- treated molecular sieve. Journal of Chromatography A, 39, 500-501.

Cai, L., Koziel, J.A., Dharmadhikari, M. and van Leeuwen, J. (2009). Rapid determination of trans-resveratrol in red wine by solid-phase microextraction with on- fiber derivatization and multidimensional gas chromatography-mass spectrometry. Journal of Chromatography A, 1216(2), 281-287.

Calleja, A., & Falqué, E. (2005). Volatile composition of Mencıa wines. Food Chemistry, 90(3), 357-363.

Campo, E., Cacho, J. and Ferreira, V. (2007). Solid phase extraction, multidimensional gas chromatography mass spectrometry determination of four novel aroma powerful ethyl esters:Assessment of their occurrence and importance in wine and other alcoholic beverages. Journal of Chromatography A, 1140(1-2), 180-188.

Consden, R. O., Gordon, A.H. and Martin, AJP. (1944). Qualitative analysis of proteins: a partition chromatographic method using paper. Biochemical Journal, 38(3), 224.

Coppen, J., Green, C., Greenhalgh, P., Keeble, B., & Milchard, M. (1983). The potential of some tropical pines as sources of marketable turpentine. In Proceedings, Ninth International Congress on Essential Oils, Singapore, (pp. 138-147).

Crippen, D. D., & Morrison, J. C. (1986). The effects of sun exposure on the compositional development of Cabernet Sauvignon berries. American Journal of Enology and Viticulture, 37(4), 235-242.

Croteau, R. (1998). The discovery of terpenes. Discoveries in Plant Biology, 1, 329-343.

De Carvalho, C. C., & da Fonseca, M. M. R. (2006). Biotransformation of terpenes. Biotechnology Advances, 24(2), 134-142.

Deans, D. (1968). A new technique for heart cutting in gas chromatography Chromatographia, 1(1), 18-22.

Degenhardt, J., Köllner, T. G., & Gershenzon, J. (2009). Monoterpene and sesquiterpene synthases and the origin of terpene skeletal diversity in plants. Phytochemistry, 70(15), 1621-1637.

Demyttenaere, J., & De Kimpe, N. (2001). Biotransformation of terpenes by fungi: Study of the pathways involved. Journal of Molecular Catalysis B: Enzymatic, 11(4), 265-270.

Drawert, F., & Rapp, A. (1966). Contents of musts and wines. VII. Investigations for aroma compounds in wines and their biogenesis by gas chromatography (Translated from German). Vitis, 5, 351-376.

Drawert, F., & Rapp, A. (1968). Gas chromatographic analysis of plant aromas. Enrichment, separation and identification of volatile aroma substances in grape, musts and wines. Chromatographia, 1, 446-457.

Dudareva, N., Pichersky, E., & Gershenzon, J. (2004). Biochemistry of plant volatiles. Plant Physiology, 135(4), 1893-1902.

Dziadas, M., Jeleń, H.H. (2010). Analysis of terpenes in white wines using SPE–SPME– GC/MS approach. Analytica Chimica Acta, 677(1), 43-49.

Ebeler, S., Sun, G. M., Datta, M., Stremple, P., & Vickers, A. K. (2001a). Solid-phase microextraction for the enantiomeric analysis of flavors in beverages. Journal of AOAC International, 84(2), 479-485.

Ebeler, S., Sun, G. M., Vickers, A. K., & Stremple, P. (2001b). Gas chromatographic analysis of chiral aroma compounds in wine using modified cyclodextrin stationary phases and solid phase microextraction. In Aroma Active Compounds in Foods, vol. 794 (pp. 45-56): American Chemical Society.

Flamini, R., & Traldi, P. (2009). Mass spectrometry in grape and wine chemistry (Vol. 42): John Wiley & Sons.

Fullana, A., Contreras, J.A., Striebich, R.C. and Sidhu, S.S. (2005). Multidimensional GC/MS analysis of pyrolytic oils. Journal of Analytical and Applied Pyrolysis, 74(1), 315-326.

Gal, J. (2008). The discovery of biological enantioselectivity: Louis Pasteur and the fermentation of tartaric acid, 1857-A review and analysis 150 yr later. Chirality, 20(1), 5- 19.

Goodwin, T. W. (1971). Aspects of terpenoid chemistry and biochemistry; proceedings of the Phytochemical Society symposium, Liverpool, April 1970. Academic Press: London.

Guth, H. (1996). Determination of the configuration of wine lactone. Helvetica Chimica Acta, 79(6), 1559-1571.

He, L., & Beesley, T. E. (2005). Applications of enantiomeric gas chromatography: a review. Journal of Liquid Chromatography & Related Technologies, 28(7-8), 1075-1114.

Herrero, M., Ibáñez, E., Cifuentes, A. and Bernal, J. (2009). Multidimensional chromatography in food analysis. Journal of Chromatography A, 1216(43), 7110-7129.

Hill, R. A. C. J. D. (1991). Dictionary of terpenoids. London: Chapmann & Hall.

J.W. Porter et al. (1981). Biosynthesis of isoprenoid compounds.

Jackson, R., & Jackson, R. S. (2009). Wine tasting: a professional handbook: Academic Press.

Jackson, R. S. (2009). Wine tasting: a professional handbook: Academic Press.

Juergens, U. (2014). Anti-inflammatory properties of the monoterpene 1,8-cineole: current evidence for co-medication in inflammatory airway diseases. Drug research, 64(12), 638-646.

Jung, M., Mayer, S., & Schurig, V. (1994). Enantiomer separation by GC, SFC, and CE on immobilized polysiloxane-bonded cyclodextrins. LC GC, 12(6), 458-466.

Kannan, V. R., & Bastas, K. K. (2015). Sustainable approaches to controlling plant pathogenic bacteria: CRC Press.

Kirchner, J. G., Miller, J.M. and Keller, G.J. (1951). Separation and identification of some terpenes by new chromatographic technique. Analytical Chemistry, 23(3), 420-425.

Koslitz, S., Renaud, L., Kohler, M., & Wüst, M. (2008). Stereoselective formation of the varietal aroma compound rose oxide during alcoholic fermentation. Journal of Agricultural and Food Chemistry, 56(4), 1371-1375.

Langenheim, J. H. (1994). Higher plant terpenoids: a phytocentric overview of their ecological roles. Journal of Chemical Ecology, 20(6), 1223-1280.

Lehmann, D., Dietrich, A., Hener, U., & Mosandl, A. (1995). Stereoisomeric flavour compounds. LXX: 1-p-menthene-8-thiol: Separation and sensory evaluation of the enantiomers by enantioselective gas chromatography-olfactometry. Phytochemical Analysis, 6(5), 255-257.

Marai, J. (1987). Terpene concentrations and wine quality of Wtis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar practices. Vitis, 26, 23l-245.

Marriott, P. J., Chin, S.T., Maikhunthod, B., Schmarr, H.G. and Bieri, S. (2012). Multidimensional gas chromatography. Trends in Analytical Chemistry, 34, 1-21.

Mason, S. (1986). The origin of chirality in nature. Trends in Pharmacological Sciences, 7(0), 20-23.

Mirata, M.-A., Wüst, M., Mosandl, A., & Schrader, J. (2008). Fungal biotransformation of (±)-linalool. Journal of Agricultural and Food Chemistry, 56(9), 3287-3296.

Mondello, L., Lewis, A.C., Bartle, K.D. and Wiley, J. (2002). Multidimensional chromatography: Wiley Chichester.

Padrayuttawat, A., Yoshizawa, T., Tamura, H., & Tokunaga, T. (1997). Optical isomers and odor thresholds of volatile constituents in citrus sudachi. Food Science and Technology International, Tokyo, 3(4), 402-408.

Park, S. K. a. N., A.C. (1993). Monoterpenes and monoterpene glycosides in wine aromas. In ACS symposium series (USA)).

Pažitná, A., Jánošková, N., Špánik, I. (2013). Multidimensional gas chromatography and its applications in food and environmental analysis. Acta Chimica Slovaca, 6(1), 133-140.

Peña, R. M., Barciela, J., Herrero, C., & García‐Martín, S. (2005). Optimization of solid‐phase microextraction methods for GC‐MS determination of terpenes in wine. Journal of the Science of Food and Agriculture, 85(7), 1227-1234.

Peynaud, E., & Ribereau-Gayon, P. (1971). The grape. The biochemistry of fruits and their products, 2, 171-205.

Pinder, A. R. (1960). The chemistry of terpenes. Chapman & Hall,.

Raguso, R. A., & Pichersky, E. (1999). A day in the life of a linalool molecule: chemical communication in a plant-pollinator system. Part 1: linalool biosynthesis in flowering plants. Plant Species Biology, 14(2), 95-120.

Rapp, A. (1990). Natural flavours of wine: correlation between instrumental analysis and sensory perception. Fresenius' Journal of Analytical Chemistry, 337(7), 777-785.

Rapp, A. (1998). Volatile flavour of wine: correlation between instrumental analysis and sensory perception. Die Nahrung, 42(6), 351-363.

Rapp, A., & Guntert, M. (1986). Changes in aroma substances during the storage of white wines in bottles. Developments in food science, 1986.

Rapp, A., Hastrich, H., & Engel, L. (1976). Gas chromatographic investigations on the aroma constituents of grape berries. 1. Concentration and separation by capillary glass columns. Vitis-Berichte ueber Rebenforschung mit Dokumentation der Weinbauforschung (Germany, FR).

Rapp, A., Hastrich, H., Engel, L., & Knipser, W. (1978). Possibilities of characterizing wine quality and vine varieties by means of capillary chromatography. Flavor of foods and beverages, 391.

Reis, S. L., Mantello, A. G., Macedo, J. M., Gelfuso, E. A., da Silva, C. P., Fachin, A. L., Cardoso, A. M., & Beleboni, R. O. (2016). Typical monoterpenes as insecticides and repellents against stored grain pests. Molecules, 21(3), 258.

Ribéreau-Gayon, P., Boidron, J., & Terrier, A. (1975). Aroma of Muscat grape varieties. Journal of Agricultural and Food Chemistry, 23(6), 1042-1047.

Ribéreau-Gayon, P., Glories, Y., & Maujean, A. (2000). Handbook of enology, Volume 2: The chemistry of wine and stabilization and treatments. In): John Wiley and Sons Ltd., England.

Robinson, A. L., Refidaff, C., Robinson, A.L., Boss, P.K., Solomon, P.S., Heymann, H. and Ebeler, S.E. (2014). Origins of grape and wine aroma. Part 2. chemical and sensory analysis. American Journal of Enology and Viticulture, 65(1), 25-42.

Santos, M. R., Moreira, F. V., Fraga, B. P., Souza, D. P. d., Bonjardim, L. R., & Quintans-Junior, L. J. (2011). Cardiovascular effects of monoterpenes: a review. Revista Brasileira de Farmacognosia, 21(4), 764-771.

Schmidt, G., Neugebauer, W., Winterhalter, P., & Schreier, P. (1995). Synthesis and Enantiodifferentiation of Isomeric 2, 3, 5, 6, 8, 8a-Hexahydro-2, 5, 5, 8a-tetramethyl-7H- 1-benzopyran-7-ones (3, 4-Dihydro-3-oxoedulans). Journal of Agricultural and Food Chemistry, 43(7), 1898-1902.

Schreier, P., Drawert, F., & Junker, A. (1976). Identification of volatile constituents from grapes. Journal of Agricultural and Food Chemistry, 24(2), 331-336.

Schreier, P., & Jennings, W. G. (1979). Flavor composition of wines: a review. Critical Reviews in Food Science and Nutrition, 12(1), 59-111.

Sciarrone, D., Tranchida, P.Q., Ragonese, C., Schipilliti, L. and Mondello, L. (2010). Multidimensional GC coupled to MS for the simultaneous determination of oxygenate compounds and BTEX in gasoline. Journal of Separation Science, 33(4‐5), 594-599.

Shahidi, F., Kolodziejczyk, P., Whitaker, J. R., Munguia, A. L., & Fuller, G. (1999). Chemicals via higher plant bioengineering (Vol. 464): Springer Science & Business Media.

Shimizu, J.-i., Uehara, M., & Watanabe, M. (1982). Transformation of terpenoids in grape must by Botrytis cinerea. Agricultural and Biological Chemistry, 46(5), 1339-1344.

Simpson, R., & Miller, G. (1983). Aroma composition of aged Riesling wine. Vitis, 22(1), 51-63.

Skinkis, P. A., Bordelon, B.P. and Wood, K.V. (2008). Comparison of monoterpene constituents in Traminette, Gewürztraminer, and Riesling winegrapes. American Journal of Enology and Viticulture, 59(4), 440-445.

Snor, W., Liedl, E., Weiss-Greiler, P., Karpfen, A., Viernstein, H., & Wolschann, P. (2007). On the structure of anhydrous β-cyclodextrin. Chemical Physics Letters, 441(1), 159-162.

Stahl, E. (1967). Thin-layer chromatography. A laboratory handbook. (2nd edition).

Strauss, C., Wilson, B., Anderson, R., & Williams, P. (1987). Development of precursors of C13 nor-isoprenoid flavorants in Riesling grapes. American Journal of Enology and Viticulture, 38(1), 23-27.

Suomalainen, H. (1983). Aroma of beer, wine and distilled alcoholic beverages (Vol. 3): Springer.

Templeton, W. (1969). An introduction to the chemistry of the terpenoids and steroids. London: Butterworths.

Tingey, D. T., Manning, M., Grothaus, L. C., & Burns, W. F. (1980). Influence of light and temperature on monoterpene emission rates from slash pine. Plant Physiology, 65(5), 797-801.

Vallery-Radot, R. (1885). Louis Pasteur: his life and labours: D. Appleton and Co.

VanWyk, C., Webb, A., & Kepner, R. (1967). Some volatile components of Vitis vinifera variety White Riesling. 1. Grape juice. Journal of Food Science, 32(6), 660-&.

Versini, G., Rapp, A., Volkmann, C., & Scienza, A. (1990). Flavour compounds of clones from different grape varieties. Vitis, 513-524.

Vilanova, M., Genisheva, Z. A., Graña, M., & Oliveira, J. (2013). Determination of odorants in varietal wines from international grape cultivars (Vitis vinifera) grown in NW Spain. South African Journal of Enology and Viticulture, 34(2), 212-222.

Wagner, R., Dirninger, N., Fuchs, V., & Bronner, A. (1977). Study of the intervarietal differences in the concentration of volatile constituents (linalool and geraniol) in the aroma of the grape. Interest of such analyses for the appreciation of the quality of the harvest. In Int. Symp. Qual. Vintage. Cape Town, (pp. 137-142).

Williams, Strauss, C., & Wilson, B. (1981). Classification of the monoterpenoid composition of Muscat grapes. American Journal of Enology and Viticulture, 32(3), 230- 235.

Wise, M. L., Savage, T. J., Katahira, E., & Croteau, R. (1998). Monoterpene synthases from common sage (Salvia officinalis) cDNA isolation, characterization, and functional expression of (+)-sabinene synthase, 1, 8-cineole synthase, and (+)-bornyl diphosphate synthase. Journal of Biological Chemistry, 273(24), 14891-14899.

Zamuz, S., & Vilanova, M. (2006). Volatile composition of the Vitis vinifera Albarino musts according to geographic areas from Rias Baixas DO (Spain). Italian journal of food science, 18(3), 323.

Molecules 2015, 20, 7359-7378; doi:10.3390/molecules20047359

CHAPTER 2

Investigation on the Quantitative Method for the Analysis of Chiral Mono-terpenes

in White Wine by HS-SPME-MDGC-MS of Different Wine Matrix

Mei Song1, Ying Xia2 and Elizabeth Tomasino3,*

1 Department of Food Science & Technology, Oregon State University, Wiegand

Hall, Corvallis, Oregon, USA 97331; E-Mail: [email protected]

2 Department of Food Science & Technology, Oregon State University, Wiegand

Hall, Corvallis,

Oregon, USA 97331; E-Mail: [email protected]

3 Department of Food Science & Technology, Oregon State University, Wiegand

Hall, room 220A, Corvallis, Oregon, USA 97331;

E-Mail: [email protected]

*Author to whom correspondence should be addressed;

E-Mail:[email protected];

Tel.: 541-737-4866.

Received: 16 March 2015 / Accepted: 16 April 2015 / Published: 22 April 2015

ABSTRACT

A valid quantitative method for chiral mono-terpenes in white wine using headspace solid phase micro-extraction-MDGC-MS (HS-SPME-MDGC-MS) with stable isotope dilution analysis was established. Fifteen compounds: (S)-(-)-limonene, (R)-(+)- limonene, (+)-(2R,4S)-cis-rose oxide, (-)-(2S,4R)-cis-rose oxide, (-)-(2R,4R)-trans-rose oxide, (+)-(2S,4S)-cis-rose oxide, furanoid (+)-trans-linalool oxide, furanoid (-)-cis- linalool oxide, furanoid (-)-trans-linalool oxide, furanoid (+)-cis-linalool oxide, (-)- linalool, (+)-linalool, (-)-α-terpineol, (+)-α-terpineol and (R)-(+)-ß-citronellol were quantified. Two calibration curves were performed in different wine bases, with varying residual sugar content, and three calibration curves in each wine base were investigated during single fiber lifetime. This was needed as both sugar content and fiber life impacted the quantification of the chiral terpenes. The chiral mono-terpene content of six Pinot

Gris wines and six Riesling wines were analyzed using the verified method. ANOVA with Tukey multiple comparisons showed significant differences for each of the detected chiral compounds in all 12 wines. PCA score plot showed a clear separation between the

Riesling and Pinot Gris wines. Riesling wines had greater number of chiral terpenes in comparison to Pinot Gris wines. Beyond total terpene content it is possible that the differences in chiral terpene may be driving the aromatic differences in white wines.

KEYWORDS:

Mono-terpenes; Chiral; MDGC-MS; Riesling; Pinot Gris

2.1. INTRODUCTION

Monoterpene compounds are known to be important aroma compounds in aromatic white wines [1–3]. While it is noted that monoterpenes are important to aromatic white wine varieties, enantiomers of monoterpene compounds have been little explored in wine. Enantiomers are chiral molecules that are non-superimposable mirror images of each other. Many molecules are enantiomers, with one enantiomer being

“active” and the other “inactive” such as with many pharmaceuticals. In wine, enantiomers of volatile aroma compounds have been found to have different perception thresholds and aroma descriptions [4]. For instance, (R)-(+)-limonene has a perception threshold of 200 ppb and an aroma of fresh, citrus and orange-like, while (S)-(-)- limonene has a perception threshold of 500 ppb and aroma described as harsh, turpentine- like, lemon note [5].

In nature many chiral compounds are enantio-pure or only found in one form.

Unlike many other wine aroma compounds, terpenes are primarily derived from grapes, a natural source. These terpenes are present in bound forms in the grape (known as glycosides, as they are bound to sugars) and are not aromatically active. Once the terpenes are unbound, or free, they contribute to aroma [6]. There are some free forms in grapes but much of the free terpene content of wine is released during fermentation [6].

The free forms are released from their sugars due to enzymes, typically found in the yeast. However there are enzyme treatments (using glycosidase enzymes) that can increase the free terpene content of wine. Therefore the chiral terpene content of wine may be due to either viticulture or winemaking processes. It is entirely possible that these

36 chiral compounds may be enantio-pure in wine or be present as all or some of their diastereomers. Due to their various properties and content in wine, the concentration of enantiomers or enantiomer excess has potential to explain relationships between wine chemistry, wine sensory, place of origin or different viticultural or winemaking processes that have been problematic or less explored in the past.

While the properties of chiral compound in wine are known, and mentioned above, measurement of the different enantiomers is challenging. The first record of enantiomeric separation in wine dates back to the mid 1800’s with Pasteur’s separation of tartaric acid enantiomers [7–9]. Since this achievement chemists have looked for improved methods for the analysis and separation of chiral compounds. Derivatization of analytes with chiral reagents to form diastereomers and then chromatographicalseparation on achiral phases has been widely employed [10]. However this method has not been found to be successful for a range of chiral compounds, specifically chiral volatile aroma compounds.

Direct separation of enantiomeric compounds on chiral amide-based GC stationary phase (e.g., Chirasil-val) was demonstrated in the mid 1960’s [11,12]. These columns allowed for excellent separation of amino acids but had limited application for analysis of most volatile compounds. With the introduction of chiral cyclodextrin-based

GC stationary phases in the late 1970’s and 1980’s, chemists were provided with the ability to directly separate a large number of underivatized chiral compounds [13]. For example, several early studies demonstrated separations of cyclic and acyclic

37 enantiomers with a range of functional groups including lactones, terpene hydrocarbons, carbonyls, alcohols, spiroketals, and oxiranes [14–16].

For the analysis of grapes and wines, cyclodextrin stationary phases have been used to establish the enantiomeric distribution of isomeric 3,4-dihydro-3-oxoedulans in

Riesling wine [17], and solerone (5-oxo-4-hexanolide) and Riesling acetal (2,2,6,8- tetramethyl-7,11-dioxatricyclo[6.2.1.01,6]undec-4-ene) in brandy and Riesling [18]. Guth

[19] separated the eight possible isomers of wine lactone (3a, 4, 5, 7a-tetrahydro-3,6- dimethylbenzofuran-2(3H)-one) on a cyclodextrin stationary phase and determined that the predominate isomer occurring in Gewurztraminer wine was the 3S, 3As, 7aR-isomer which has an intense sweet coconut-like aroma and an aroma threshold of 0.02 pg/L in air. The proposed study in this paper employs two different cyclodextrin columns in sequence using heart-cutting MDGC-MS to measure chiral terpenes in white wines, producing a more sensitive method for measurement of these compounds. Specifically compound stability over the course of analysis was investigated as was impact of wine matrix.

Monoterpenes are important to white wine aroma, but not much is known about the contribution of chiral monoterpenes. Measurement of these chiral compounds has become more accessible as now measurement can be achieved with minimum sample preparation. The aim of this study was to produce a robust, reproducible and sensitive

GC-MS based method to easily measure chiral monoterpenes. This method would then be used to investigate chiral monoterpene differences in Pinot Gris and Riesling wines.

2.2. RESULTS AND DISCUSSION

2.2.1. Separation of chiral mono-terpenes in MDGC-MS

A chromatogram of all 15 chiral mono-terpenes and isotopes is found in Figure

2.1. All of the compounds showed good resolution. The elution order for linalool oxide and rose oxide isomers (standards were only available as isomer mixtures) were confirmed from previous methods investigating chiral compounds using the same column configuration as this method [20].

2.2.2. Validation of the quantitative method

2.2.2.1. Linearity of calibration curve in different wine matrix

Many reports have investigated the effect of non-volatile compounds on aroma compounds in wine, such as residual sugar, ethanol content, polyphenol, total acidity and so on [21–23]. Calibration curves performed in a synthetic matrix may not be representative of measurements taken in wines with diverse non-volatile compounds. In this study, two kinds of white wines with distinct different residual sugar contents were chosen as base wine for calibration curve; Low PG (Pinot gris) (L) base for lower residual sugar content (3.7 g/L) and High RS (Riesling) (H) base for higher residual sugar content (64.1 g/L). These wines were identified as appropriate base wines for the effect of nonvolatile matrix on all wines measured in this study (data not shown). As can be seen in Table 2.1, there were some differences between the two kinds of calibration curves, especially for compounds of limonene and rose oxide isomers, thus two calibration curves were used in this study. Wines with corresponding residual sugar measurements

39 were matched to the appropriate calibration curve. Wines with residual sugar content less than 19 g/L used the L calibration curve, while H calibration curve was used if the residual sugar content was greater than 19 g/L. The choice of 19 g/L as the dividing point was set based on spiked recovery study of wines with diverse residual sugar content

(Table 2.2).

One of the differences that occurred between the L and H calibration curves was the slope. A lower slope for 2 and 4 (limonene isomers) and higher slope for 5, 6, 9 and

10 (rose oxide isomers) were found in H base calibration curve compared with L base calibration curve. Rose oxide isomers seemed more easily released from the diluted wine solution with higher residual sugar content, while limonene isomers were retained longer in the same wine base. Other work has shown that high amounts of fructose concentrations in model wine solutions have strong retaining effect of odorants in headspace extraction [24]. However, another study showed the extraction of esters was not affected by sugar content in a varying saccharose content (0-200 g/L) of synthetic wine using HS-SPME-HRGC [25], suggesting that the impact of sugar concentration on extraction for HS-SPME measurements varies depending on the volatile compound being measured. Our results showed that the measurement for concentration of chiral monoterpenes would not be accurate if a wine with a high residual sugar utilized a calibration curve from a dry wine to calculate the concentration of terpenes, especially for limonene and rose oxide isomers. This suggested a strong matrix effect on the investigated compounds.

Several other method factors were investigated to ensure accurate and repeatable measurements of the chosen chiral mono-terpenes. HS-SPME was used as it is an inexpensive and reproducible method to measure volatile compounds [26–28]. In our study, single fiber repeatability was investigated in both wine bases. Calibration curves were divided into three parts, based on the age (or usage) of a new fiber; the beginning

(first 8-10 days of fiber life), middle use (within 8-13 days of fiber life) and at the last life of fiber (last 10 days of fiber life). In total, six calibration curves were plotted in terms of wine matrix and fiber age over 300 injections; L first, L middle, L last, H first, H middle and H last. A significant change in slope for compounds 2, 4, 5, 6, 9 and 10 was noted from first to last intervals for both wine bases (Table 2.1). Interestingly, limonene isomers (2 and 4) had decreasing affinity to SPME fiber in single fiber durability. Rose oxide isomers (5, 6, 9 and 10) showed a greater affinity for the fiber during the middle interval, in comparison with the decreasing affinity noted for other compounds.

Compounds 7, 8, 11, 12, 14, 16, 18, 20 and 21were not affected by the life of the SPME fiber. The reason for the poor repeatability of single fiber was not clear. It was reported that SPME fibers suffer from some weakness, such as limited lifetime and sample carryover [29]. The carry over effect had been eliminated in our study by re-desorption in the heater port for 10 min, lengthening this time did not improve compound affinity over time. One report mentioned poor reproducibility of fiber from one to another, and suggested a new calibration each time the fiber was changed [30]. To eliminate the error due to single fiber variance, chemical composition was determined using calibration curves from the same time period.

2.2.2.2. Limit of Detection (LOD), Limit of Quantitation (LOQ), wine reproducibility and internal standards stability

LOD and LOQ data are reported in Table 2.2. The LOQ ranges from 1 ng/L to

1.11 μg/L and these limits are lower than the known olfactory thresholds for the measured compounds (Table 2.5). The detected LOQ (µg/L) values are also lower than previous methods measuring chiral terpenes [2,31,32].

Wine reproducibility values varied around 15% (relative standard deviation, RSD

%) for all compounds in Riesling and Pinot Gris wines. Reproducibility of 14, 16, 18 and

20 were the best of all compounds, with an RSD less than 10%. This study showed that all the terpenes in the standards and wines were stable and did not degrade or react under the chosen storage conditions (-18°C).

2.2.2.3. Accuracy

The majority of the spiked recoveries fell within 80%-120%, although there were some exceptions (Table 2.2). Compounds 7, 8, 11 and 12 in PG dry style were about 70% and 5 and 9 in most of wine style was approximately 130%. As mentioned before in

Table 2.1, compounds 7, 8, 11 and 12 had greater retention in L base, which may explain the low calculated recovery. Concentrations of 7, 8, 11 and 12 from Pinot Gris dry white wine were adjusted to 100% by recovery factor (multiply by 1.4 for 7, 8 and 12; by 1.3 for 11). A possible explanation for the spiked recoveries for 5 and 9 (~130%) may be due to the very low concentrations measured. Reports show that systematic errors may be present for some monoterpenes at very low concentration, especially close to the LOQ if

42 an internal standard was not analogous to the compound being quantified, thus leading to non-linear responses [33] and recovery values higher than 100% [34]. Compounds 5 and

9 (rose oxide isomers) were calculated using d3-linalool as the internal standard as a deuterium labeled rose oxide isotope was not available.

2.2.2.4. Temperature stability

The temperature stability of the chiral mono-terpenes at key steps of the method were investigated as studies have shown that these compounds may degrade at high temperatures [35,36]. The extraction temperature during head space sampling and the injector temperature were investigated for seven of the chiral mono-terpenes (Table 2.3).

The stability of the terpenes at temperatures of 200 °C, 230 °C and 250 °C were determined. The range of injector temperatures was chosen because they are higher than the boiling point of all compounds and lower than the column maximum temperature. T- test and one way ANOVA were performed and no significant differences were found due to injector and extraction temperatures (α=0.05, Table 2.3). The results showed that the chosen temperatures did not impact the adsorption of the compounds onto the SPME fiber or any degradation of the compounds when injected into the GC.

2.2.3. Wine analysis

All of the measured chiral mono-terpenes were found in 12 white wines except for 5, 9 and 10. P refers to Pinot Gris wines and R refers to Riesling wines. The concentrations of all the compounds detected in investigated wines, except 14 and 16,

43 were below perception threshold detected in air or ethanol solutions (Table 2.4). ANOVA with Tukey multiple comparisons showed significant differences for all of the detected chiral compounds. 7, 8, 12, 18 and 20 were detected in all 12 white wines. Compound 21 was not detectable in R2 wine. 14 and 16 were found in all six Riesling wines and three

Pinot Gris wines. Interestingly, 5 and 11 were only detected in five and six wines respectively. The presence of only one rose oxide isomer (5) is consistent with another report of (–)-cis-rose oxide present at high enantiomeric excess in grape musts [4]. These results suggest that the profile of chiral mono-terpenes may have the potential to differentiate diverse wines.

PCA of the chiral monoterpenes showed a clear separation between the Riesling and Pinot Gris wines, with Riesling wines containing more chiral terpenes than Pinot Gris wines (Figure 2.2). While the Pinot Gris wines all grouped in the same relative area, the

Riesling wines were further separated into two groups on F2. Specifically, half of the wines were correlated with 5, 6, 7, 8, 9, 10, 11, and 12 and the other half correlated to 2,

4, 14, 16, 18 and 20.

It will be interesting to determine the origins of the differences in chiral monoterpenes. The ANOVA and PCA results suggest there is some difference in grape varieties as the Pinot Gris and Riesling wines group in a similar area. This differentiation by grape variety was expected, as it is known that the precursors to these terpenes are formed in the grape [6,37]. It was anticipated that the Pinot Gris wines would have lower concentrations and a less complex composition of monoterpenes than the Riesling wines, as Riesling wines are considered to be a more aromatic varietal. The further separation on

44 the right side of the PCA plot, namely the vertical separation of Riesling, may be due to a number of factors. There are many mechanisms for release of terpenes from their bound forms including enzyme additions, pH of juice and wine, yeast strain used for fermentation, fermentation temperature and other viticulture and winemaking practices

[38–42]. The further separation of the Riesling wines is most likely due to viticultural or winemaking practices. Specifically R1, R2 and R5 are characterized by higher concentrations of the four linalool oxide isomers and three of the rose oxide isomers. R3 and R4 are best characterized by limonene and α-terpineol isomers and R6 characterized by linalool isomers.

The higher concentrations of linalool-oxides in the R1, R2 and R5 may correlate to ripeness in the grapes prior to fermentation, as these oxides are typically formed from oxidation and cyclization of linalool [43]. Alternatively linalool oxides are also produced from Botrytis cinerea metabolism, and this may be the defining factor between the

Riesling wines [44], although none of the wines chosen were late harvest or styles of

Riesling associated with Botrytis cinerea. However those wines with higher levels of linalool oxides isomers also contained high levels of rose oxides isomers. Formation of rose oxide isomers is from a different source, namely yeast metabolism. There are two different reductive pathways known in yeast that result in rose oxide formation [45]. The limonene and α-terpineol found in R3 and R4 is quite interesting as acidic environments, such as in wine, result in the formation of α-terpineol from limonene [46]. Therefore it was anticipated that wines with higher concentrations of α-terpineol may have lower concentrations of limonene isomers. But α-terpineol is also one of the most abundant

45 terpenes produced by yeast [47], therefore the terpene content of these two Riesling wines may be due to a combination of factors. The high levels of linalool in R6 may also be due to several factors, such as a high level of linalool-glycosides in the grapes and then of release of this into the free form. But it could also be related to the low transformation of linalool after fermentation resulting in retention of more linalool than the other wines. As stated before linalool oxidizes to linalool oxides in the presence of oxygen, but it may also be degraded by Botrytis cinerea [48]. It has also been found that higher levels of caffeic and gallic acid can stop the degradation of linalool in wine [49].

Therefore the nonvolatile composition, which was not investigated beyond sugar content in this study, may be more favorable for linalool retention.

Finally it is of great interest to determine if the differences in the chiral monoterpene content of these wines are also present in sensory perception. We have stated earlier in the paper that all of these compounds are present at levels below their known perception threshold. But current perception thresholds may not be realistic in wine, as the solution they are tested in plays an important role and most perception thresholds are measured in water or a water and ethanol solution [50–52]. To add to this complexity it is known that the perception threshold of some monoterpenes, specifically linalool, changes when it is in a mixture with other monoterpenes [53]. Therefore further research investigating the sensory impact of these compounds is important. It will be able to determine how the compound impacts aroma individually and then in combination with other chiral terpenes.

2.3. EXPERIMENTAL SECTION

2.3.1. Chemicals

The following standards were obtained from Sigma Chemical Co. (St. Louis,

MO): (S)-(-)-limonene, (R)-(+)-limonene, (-)-rose oxide, linalool oxide, linalool, α- terpineol, and (R)-(+)-β-citronellol (Table 2.5). The chemical structures of the standards are showed in Figure 2.3. D3-(±)-α-terpineol and d3-(±)-linalool were purchased from

CDN isotopes (Pointe-Claire, Quebec, Canada). D3-(±)-limonene was not available by a commercial source. Synthesis information can be found in Section 2.3.2. Other chemicals, including methyl-vinyl ketone (99%, CAS# 78-94-4), isoprene (CAS# 78-79-

5), aluminum chloride (CAS# 7446-70-0), magnesium sulfate (CAS# 7487-88-9), d3- methyl-triphenylphosphonium iodide (95 atom %D, CAS# 1560-56-1), and sodium amide (98%, CAS# 7782-92-5) were purchased from Sigma Chemical Co. (St. Louis,

MO); Sodium sulfate (anhydrous, CAS# 7757-82-6) was from Mallinckrodt AR®;

Potassium carbonate (anhydrous, CAS# 584-08-7) from EMD. Organic solvents used were HPLC grade, absolute ethyl alcohol (anhydrous) was from Pharmco-AAPER, dichloromethane and n-hexane (95%) were from EMD, ethyl ether (anhydrous) was from

Macron fine chemicals. Milli-Q water was obtained from Millipore continental water system.

Residual sugar of each wine was analyzed according to the revised

Rebelein method in duplicate [54]. Alcohol content was analyzed using Alcolyzer Wine

M (Anton Paar GmbH, Australia).

2.3.2. d3-Limonene synthesis

2.3.2.1. Synthesis of 4-acetyl-1-methyl cyclohexene

3 mL of dichloromethane was placed in a 5 mL beaker on an ice bath. 150 µL of methyl-vinyl ketone and 150 µL of isoprene were slowly pipetted into the beaker, and a small spatula tip of anhydrous AlCl3 was added. This solution was stirred for 2 hours at room temperature. The resulting mixture was diluted with 5 mL of diethyl ether and then washed with 10% Na2SO4 solution (x2). The upper layer was kept and dried with magnesium sulfate. The resulting compound was checked with GC-MS and resulted in around 5 mL solution of 4-acetyl-1-methyl cyclohexene.

2.3.2.2. D3-limonene synthesis

10 mL of anhydrous ethyl ether was added to a tree neck flask with continual nitrogen blowing. With vigorous stirring, 1 mL of 4-acetyl-1-methylcyclohexene and around 0.5 g of d3-methyl-triphenylphosphonium iodide was added to the ethyl ether.

The flask was closed with its caps and stirred vigorously for 10 min, after that, around sodium amide solution (2.5-3 g) dissolved in 10 mL anhydrous ethyl ether was slowly added. The mixture was stirred vigorously for 15 min. The solution was allowed to cool to room temperature and transferred to a separator funnel. The mixture was diluted with

30 mL hexane and washed with 10 mL of 10% aqueous solution K2CO3 (x2). The upper layer was retained and dried with 10 mL 10% of Na2SO4 (x2), then dried with Mg2SO4.

The resulting compound was concentrated by gently boiling the organic layer on a hot plate. The final compound was thick residue with yellow color and orange aroma. Three

48 ions were different (71, 124, and 139) in comparison to regular limonene (68, 121, and

136), showing that hydrogen was replaced by deuterium in three positions.

2.3.3. Sample preparation

All wine samples were diluted immediately prior to analysis. 0.9 mL of each wine were added to 8.06 mL of milli-Q water into 20 mL amber glass, screw cap vials, 22.5 x

75.5 mm, followed by 40 µL of the composite isotopically-labelled internal standard solution. The total volumes used were equivalent to a 10-fold dilution of the wine sample

[55]. Sodium chloride (4.5-5.0 g) was added to the SPME vial and vials were tightly capped. Samples were then incubated initially for 10 min at 60 °C, during which time the vial was agitated at 500 rpm (5 sec on, 2 sec off). The sample was extracted for 50 min with no further agitation. The fiber was then injected into the first GCMS for 10 min at

250 °C followed by further conditioning in an NDL heater for 10 min at 250 °C.

2.3.4. Solid phase micro-extraction coupled with MDGC-MS

Three-phase Stableflex SPME fiber (50/30 µm DVB/CAR/PDMS, 2 cm, 24 Ga) was purchased from Supelco (Poznań, Poland). The fiber was conditioned at 250 °C for 1 hour before analysis. All samples were extracted using Shimadzu auto-sampler AOC-

5000 plus fitted with a stack cooler set at 4 °C.

Heart cut-MDGC-MS analyses were performed using Shimadzu GC-2000 plus with a split/splitless injector coupled to Shimadzu QP 2010 GC-mass spectrometer using a dean switch. The first GC column was a RtX-wax, 30 m in length, 0.25 mm ID, and 0.5

µm of film thickness (Crossbond ® Carbowax ® Polyethylene glycol, Restek

Corporation, PA). Method parameters for the first GC oven were as follows; injector temperature at 230 °C. The column oven was held at 65 °C for 3 min, and then increased to 145 °C at 4 °C min-1, at which the temperature was kept constant for 10 min, then further increased to 230 °C at 4 °C min-1 and held at this temperature for 15 min. Flow control mode was set using pressure mode at a constant 235 kpa, switching pressure was

200 kpa. The cut windows for further separation on second GC column were: 7.85-8.50 min; 12.00-14.00 min; 14.25-15.80 min; 15.85-17.25 min, 18.50-21.25 min; 22.00-26.00 min; 26.75-30.00 min, 33.00-38.00 min, 38.50-45.00 min. The second GC contained two columns connected in sequence. Rt®-βDEXsm connected with Rt®-βDEXse (alkylated beta-cyclodextrins in cyanopropyl-dimethyl polysiloxane, Restek Corporation, PA), 60 m in length in total, 0.25 mm ID, and 0.25 µm of film thickness. The second oven program began at the same time as the first as is as follows; the column oven was held at 40 °C for

10 min, then increased to 125 °C at 3.0 °C min-1 holding for 10 min, followed by an increase of 3.0 °C min-1 to 135 °C, then further increased to 170 °C at 2.0 °C min-1, held for 2 min, finally increased to 230 °C at 15.0 °C min-1 and held at this temperature for 8 min. The total run time was 83.17 min. GCMS transfer line temperature was 230 °C; ion source temperature was 200 °C. Spectra were acquired using electron impact ionization

(EI, 70 eV) in a full scan mode from 3 min to 83 min with scan range of m/z 33–303 Da at 0.20 sec event time. Detector was run at a variable gain factor for each compound from

0.80 to 1.35.

Identification of all chiral mono-terpenes was based on the comparison of retention time and mass spectra with authentic standards and NIST11 database.

Quantitation of all compounds was based on calibration curves calculated from peak area ratios (peak area of the mono-terpene standard /peak area of the corresponding isotope standard) were plotted against the concentration ratios (mono-terpene standard / the corresponding isotope standard) for 6 series of mono-terpene concentrations.

2.3.5. Validation of the quantitative method

2.3.5.1. Linearity of calibration curve in different wine matrix

All the 15 chiral monoterpenes were quantified using 6 point calibration curve.

Two de-aromatized wines were prepared as the base wine: one was 2012 Pinot Grigio, alcohol content 12.3%, residual sugar 3.7 g/L, defined as Low RS (L) wine base; another one was 2012 late harvest Riesling, alcohol content 9.6%, residual sugar 64.1 g/L, defined as High RS (H) wine base. 100 mL of wine was de-aromatized using a rotary evaporator (Buchi heating bath B-490, IL, USA) at 35 °C water bath and 135 rpm rotation for 2 hours under 63 cm of hg vacuum. The de-aromatized wine was adjusted with ethanol solution to original alcohol content and dH2O was added to bring the volume up to the original 100mL, ensuring the same nonvolatile matrix. The de-aromatized wine contained only trace amounts of linalool oxide and α-terpineol isomers. These concentrations were subtracted from the calibration curves to ensure accurate measurements.

Six point calibration curves for all compounds were performed. Compounds were added to de-aromatize wine base at specific concentration (Table 2.6) into 20 mL amber glass, screw cap vials, 22.5 x 75.5 mm, followed by 40 µL of the composite isotopically- labelled internal standard solution, to make a final volume of 9.0 mL.

Over the lifetime of the SPME fiber, there may have varied partition coefficient of volatile compounds with SPME fiber and resulting in poor fiber repeatability. Calibration curves were divided into three parts at the beginning of a new fiber, middle use of fiber and at the last life of fiber. Totally six kinds of calibration curves were plotted in terms of wine matrix and fiber during time. Each calibration curve was done in triplicate (Table

2.6).

2.3.5.2. Limit of Detection (LOD), Limit of Quantitation (LOQ), wine reproducibility and internal standards stability

LOD and LOQ (Table 2.2) were calculated as in [56] and [57]. Two wine samples

(2011 dry Riesling, ALC of 10.8%, RS of 0.58 g/L; 2013 Pinot Gris, ALC of 11.8%, RS of 16.43 g/L) were measured every 2 days over the course of the analysis period to determine stability and reproducibility. The wine samples were all kept frozen (at -18 °C) prior to analysis. The Standard 4 point of the calibration curve was made fresh and measured every 2 days over the course of the analysis period to measure internal standard stability (Table 2.2).

2.3.5.3. Accuracy

The accuracy of the analytical method was evaluated by calculating the recoveries

(Table 2.2) of the standard addition. Different styles of wines (dry, medium dry, medium sweet and sweet) were selected, each of them spiked to standard 4 concentrations. The spiked recoveries were calculated by the difference of concentration of compounds between spiked wine and original wine divided by the real concentration of compounds in standard 4. The two kinds of varieties (Riesling and Pinot Gris) were investigated respectively and done in duplicate.

2.3.5.4. Temperature stability

Seven chiral mono-terpenes, (+)-α-terpineol, (-)-linalool, R-(+)-β-citronellol, (R)-

(+)-limonene, (S)-(-)-limonene, (+)-(2R, 4S)-cis-rose oxide, (-)-(2S, 4R)-cis-rose oxide were chosen to detect temperature stability. Each compound was added to milli-Q water at concentrations close to standard 6 and extracted with SPME at 60 °C for 50 min; the purity (peak area ratio of these compounds to corresponding isomers) was investigated at injector temperature of 200 °C, 230 °C and 250 °C, respectively. The extraction temperature was performed at 40 °C and 60 °C as injector temperature at 250 °C.

2.3.6. Chiral mono-terpene contents in 12 white wines

Twelve white wines from Riesling and Pinot Gris grape varieties were donated from top companies all over the world including New Zealand, Australia, Italy and the

USA. Detailed information of 12 wines is listed in Table 2.7. Wine type was categorized

53 according to European regulation [58]: wine with residual sugar content not exceeding

4g/L can be considered as ‘dry’; between 4g/L and 12g/L as ‘medium dry’; not exceeding

45g/L as ‘medium sweet’, above 45g/L as ‘sweet’ wine. All of the wines were sampled and stored at -18 °C before analysis.

2.3.7. Data analysis

T-test, ANOVA and Tukey multiple comparisons were calculated with XLSTAT-

Pro 2014 (Addinsoft). Principle Component Analysis (PCA) using Pearson correlation matrix was also calculated with XLSTAT-Pro 2014 (Addinsoft).

2.4. CONCLUSIONS

It is possible to measure the different terpene enantiomers in white wine using an

HS-SPME-MDGC-MS method. This method was able to quantify concentrations of the different enantiomers down to 1 ng/L. It is not possible to use a single calibration curve for all wines as significant matrix effect, related to sugar content, was noted.

Additionally, the fiber age also impacted the measurement of some of the chiral terpenes.

In particular the rose oxide isomers, and limonene isomers were most impacted by fiber life and the matrix. However, this method resulted in good separation and sensitive, accurate and reproducible measurement of chiral monoterpenes when different wine matrices were used. A difference in chiral monoterpene content was noted between Pinot

Gris and Riesling wines, with Riesling wines contained larger number of the chiral terpenes than Pinot Gris wines. Terpenes are known to impact the floral and citrus

54 aromatics of wine, but the identification and quantitation of the individual isomers may explain differences in these aromatics between wines. Further investigations will determine if the different terpene isomers are impacting wine aroma.

ACKNOWLEDGMENTS

This project was funded by the Oregon Wine Board and the Oregon Wine

Research Institute.

AUTHOR CONTRIBUTIONS

Elizabeth Tomasino conceived the experiments. Mei Song and Elizabeth

Tomasino designed the experiments, analyzed the data and wrote the paper. Mei Song and Ying Xia performed the experiments.

CONFLICTS OF INTEREST

The authors declare no conflict of interest.

REFERENCES AND NOTES

1. Skinkis, P. A.; Bordelon, B. P.; Wood, K. V. Comparison of monoterpene constituents in Traminette, Gewurztraminer, and Riesling winegrapes. Am. J. Enol. Vitic. 2008, 59, 440–445.

2. Dziadas, M.; Jeleń, H. H. Analysis of terpenes in white wines using SPE–SPME– GC/MS approach. Anal. Chim. Acta 2010, 677, 43–49.

3. Park, S. K.; Noble, A. C. Monoterpenes and monoterpene glycosides in wine aromas. In; 1993.

4. Brenna, E.; Fuganti, C.; Serra, S. Enantioselective perception of chiral odorants. Tetrahedron Asymmetry 2003, 14, 1–42.

5. Friedman, L.; Miller, J. G. Odor Incongruity and Chirality. Science 1971, 172, 1044– 1046.

6. Mateo, J. J.; Jiménez, M. Monoterpenes in grape juice and wines. J. Chromatogr. A 2000, 881, 557–567.

7. Gal, J. The discovery of biological enantioselectivity: Louis Pasteur and the fermentation of tartaric acid, 1857—A review and analysis 150 yr later. Chirality 2008, 20, 5–19.

8. Mason, S. The origin of chirality in nature. Trends Pharmacol. Sci. 1986, 7, 20–23.

9. Vallery-Radot, R. Louis Pasteur--his life and labours; D. Appleton and Co., 1885.

10. Srinivas, N.; Shyu, W.; Barbhaiya, R. Gas chromatographic determination of enantiomers as diastereomers following pre-column derivatization and applications to pharmacokinetic studies: a review. Biomed. Chromatogr. 1995, 9, 1–9.

11. Gil-Av, E.; Feibush, B.; Charles-Sigler, R. Separation of enantiomers by gas liquid chromatography with an optically active stationary phase. Tetrahedron Lett. 1966, 8, 1009–1015.

12. Frank, H.; Nicholson, G.; Bayer, E. Chiral polysiloxanes for resolution of optical antipodes. Angew Chem Int Ed Engl 1967, 9, 3345–3347.

13. Ebeler, S. E.; Sun, G. M.; Vickers, A. K.; Stremple, P. Gas Chromatographic Analysis of Chiral Aroma Compounds in Wine Using Modified Cyclodextrin Stationary Phases and Solid Phase Microextraction. In Aroma Active Compounds In Foods; American Chemical Society, 2001; pp. 45–56.

14. König, W.; Krebber, R.; Wenz, G. Enantioselective capillary gas chromatography on the basis of host‐guest interactions with modified cyclodextrins. J. High Resolut. Chromatogr. 1989, 12, 641–644.

15. Nowotny, H.; Schmalzing, D.; Wistuba, D.; Schurig, V. Extending the scope of enantiomer separation on diluted methylated β‐cyclodextrin derivatives by high‐ resolution gas chromatography. J. High Resolut. Chromatogr. 1989, 12, 383–393.

16. Mosandl, A.; Hener, U.; Hagenauer‐Hener, U.; Kustermann, A. Direct enantiomer separation of chiral γ‐lactones from food and beverages by multidimensional gas chromatography. J. High Resolut. Chromatogr. 1989, 12, 532–536.

17. Schmidt, G.; Neugebauer, W.; Winterhalter, P.; Schreier, P. Synthesis and Enantiodifferentiation of Isomeric 2, 3, 5, 6, 8, 8a-Hexahydro-2, 5, 5, 8a-tetramethyl-7H- 1-benzopyran-7-ones (3, 4-Dihydro-3-oxoedulans). J. Agric. Food Chem. 1995, 43, 1898–1902.

18. Dollmann, B.; Full, G.; Schreier, P.; Winterhalter, P.; Guntert, M.; Sommer, H. Synthesis and enaniotdifferentiation of riesling acetals. Phytochem. Anal. 1995, 6, 106– 111.

19. Guth, H. Determination of the configuration of wine lactone. Helv. Chim. Acta 1996, 79, 1559–1571.

20. A guide to the analysis of chiral compounds by GC. Resteck Corp. 1997.

21. Jackson, R. S. Wine Science; Principles, Practices and Perceptions; 2nd Edition.; Academic Press: San Diego and London, 2000.

22. Muñoz-González, C.; Martín-Álvarez, P. J.; Moreno-Arribas, M. V.; Pozo-Bayón, M. Á. Impact of the nonvolatile wine matrix composition on the in vivo aroma release from wines. J. Agric. Food Chem. 2013, 62, 66–73.

23. Sorrentino, F.; Voilley, A.; Richon, D. Activity coefficients of aroma compounds in model food systems. AIChE J. 1986, 32, 1988–1993.

24. Villamor, R. R.; Evans, M. A.; Mattinson, D. S.; Ross, C. F. Effects of ethanol, tannin and fructose on the headspace concentration and potential sensory significance of odorants in a model wine. Food Res. Int. 2013, 50, 38–45.

25. Rodrıguez-Bencomo, J.; Conde, J.; Rodrıguez-Delgado, M.; Garcıa-Montelongo, F.; Pérez-Trujillo, J. Determination of esters in dry and sweet white wines by headspace solid-phase microextraction and gas chromatography. J. Chromatogr. A 2002, 963, 213– 223.

26. Tuduri, L.; Desauziers, V.; Fanlo, J. L. Potential of solid-phase microextraction fibers for the analysis of volatile organic compounds in air. J. Chromatogr. Sci. 2001, 39, 521– 529.

27. Djozan, D.; Bahar, S. Solid-phase microextraction of aliphatic alcohols based on polyaniline coated fibers. Chromatographia 2004, 59, 95–99.

28. Popp, P.; Paschke, A. Solid phase microextraction of volatile organic compounds using carboxen-polydimethylsiloxane fibers. Chromatographia 1997, 46, 419–424.

29. Abolghasemi, M. M.; Karimi, B.; Yousefi, V. Periodic mesoporous organosilica with ionic liquid framework as a novel fiber coating for headspace solid-phase microextraction of polycyclic aromatic hydrocarbons. Anal. Chim. Acta 2013, 804, 280–286.

30. Pozo-Bayón, M.; Pueyo, E.; Martın-Alvarez, P.; Polo, M. Polydimethylsiloxane solid-phase microextraction–gas chromatography method for the analysis of volatile compounds in wines: Its application to the characterization of varietal wines. J. Chromatogr. A 2001, 922, 267–275.

31. Pena, R. M.; Barciela, J.; Herrero, C.; Garcia-Martin, S. Optimization of solid-phase microextraction methods for GC-MS determination of terpenes in wine. J. Sci. Food Agric. 2005, 85, 1227–1234.

32. Peña-Alvarez, A.; Capella, S.; Juárez, R.; Labastida, C. Determination of terpenes in tequila by solid phase microextraction-gas chromatography–mass spectrometry. J. Chromatogr. A 2006, 1134, 291–297.

33. Perkins, M. L.; D’Arcy, B. R.; Lisle, A. T.; Deeth, H. C. Solid phase microextraction of stale flavour volatiles from the headspace of UHT milk. J. Sci. Food Agric. 2005, 85, 2421–2428.

34. Garrido-Frenich, A.; Romero-González, R.; Martínez-Vidal, J.; Plaza-Bolaños, P.; Cuadros-Rodríguez, L.; Herrera-Abdo, M. Characterization of recovery profiles using gas chromatography-triple quadrupole mass spectrometry for the determination of pesticide residues in meat samples. J. Chromatogr. A 2006, 1133, 315–321.

35. Garneau, F.-X.; Collin, G.; Gagnon, H. Chemical composition and stability of the hydrosols obtained during essential oil production. I. The case of Melissa officinalis L. and Asarum canadense L. Am. J. Essent. Oils Nat. Prod. 2014, 2, 54–62.

36. Garneau, F.-X.; Collin, G.; Gagnon, H. Chemical composition and stability of the hydrosols obtained during essential oil production. II. The case of Picea glauca (Moench) Voss., Solidago puberula Nutt., and Mentha piperita L. Am. J. Essent. Oils Nat. Prod. 2014, 2, 29–35.

37. Versini, G.; Carlin, S.; Nicolini, G.; Dellacassa, E.; Carrau, F. Updating of varietal aroma components in wines. In Vitiviniculture in the Southern emishpere: proceedings of the 7th Latin-American Congress of viticulture and winemaking; 1999; pp. 323–349.

38. Gunata, Z.; Bitteur, S.; Brillouet, J.-M.; Bayonove, C.; Cordonnier, R. Sequential enzymatic hydrolysis of potentially aromatic glycosides from grape. Carbohydr. Res. 1988, 183, 139–149.

39. Zoecklein, B. W.; Marcy, J. E.; Williams, J. M.; Jasinski, Y. 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. J. Food Compos. Anal. 1997, 10, 55–65.

40. Fernández-González, M.; Di Stefano, R.; Briones, A. Hydrolysis and transformation of terpene glycosides from muscat must by different yeast species. Food Microbiol. 2003, 20, 35–41.

41. Maicas, S.; Mateo, J. J. Hydrolysis of terpenyl glycosides in grape juice and other fruit juices: a review. Appl. Microbiol. Biotechnol. 2005, 67, 322–335.

42. Macaulay, L. E.; Morris, J. R. Influence of cluster exposure and winemaking processes on monoterpenes and wine olfactory evaluation of Golden Muscat. Am. J. Enol. Vitic. 1993, 44, 198–204.

43. Rapp, A.; Marais, J. The shelf life of wine: Changes in aroma substances during storage and ageing of white wines. In Shelf life studies of food and beverages. Chemical, biological, physical and nutritional aspects; Elsevier Science Publishers: Amsterdam, 1993; pp. 891–921.

44. Shimizu, J.; Uehara, M.; Watanabe, M. Transformation of terpenoids in grape must by Botrytis cinerea. Agric. Biol. Chem. 1982, 46, 1339–1344.

45. Koslitz, S.; Renaud, L.; Kohler, M.; Wust, M. Stereoselective formation of the varietal aroma compound rose oxide during alcoholic fermentation. J. Agric. Food Chem. 2008, 56, 1371–1375.

46. Tatum, J.; Nagy, S.; Berry, R. Degradation products formed in canned single-strength orange juice during storage. J. Food Sci. 1975, 40, 707–709.

47. Carrau, F. M.; Medina, K.; Boido, E.; Farina, L.; Gaggero, C.; Dellacassa, E.; Versini, G.; Henschke, P. A. De novo synthesis of monoterpenes by Saccharomyces cerevisiae wine yeasts. FEMS Microbiol. Lett. 2005, 243, 107–115.

48. Bock, G.; Benda, I.; Schreier, P. Biotransformation of linalool by Botrytis cinerea. J. Food Sci. 1986, 51, 659–662.

49. Lambropoulos, I.; Roussis, I. G. Inhibition of the decrease of volatile esters and terpenes during storage of a white wine and a model wine medium by caffeic acid and gallic acid. Food Res. Int. 2007, 40, 176–181.

50. Cullere, L.; Cacho, J.; Ferreira, V. An assessment of the role played by some oxidation-related aldehydes in wine aroma. J. Agric. Food Chem. 2007, 55, 876–881.

51. Frank, S.; Wollmann, N.; Schieberle, P.; Hofmann, T. Reconstitution of the flavor signature of dornfelder red wine on the basis of the natural concentrations of its key aroma and taste compounds. J. Agric. Food Chem. 2011, 59, 8866–8874.

52. Audouin, V.; Bonnet, F.; Vickers, Z. M.; Reineccius, G. A. Limitations in the use of odor activity values to determine important odorants in foods. In; American Chemical Society, 1999; Vol. 782, pp. 156–171.

53. Rapp, A.; Mandery, H. Wine aroma. Experientia 1986, 42, 873–884.

54. Rebelein, H. Rapid method for the determination of the alcohol, sugar and total SO2 contents (by distillation) in wine and fruit juices and also for determining blood alcohol. Chem Mikrobiol Technol Leb. 1973, 2, 112–121.

55. Tomasino, E. Characterization of regional examples of New Zealand Pinot noir by means of sensory and chemical analysis, Lincoln University: Lincoln, New Zealand, 2012.

56. Callejon, R. M.; Gonzalez, A. G.; Troncoso, A. M.; Morales, M. L. Optimization and validation of headspace sorptive extraction for the analysis of volatile compounds in wine vinegars. J. Chromatogr. A 2008, 1204, 93–103.

57. Miller, J. N.; Miller, J. C. Statistic and chemometrics for analytical chemistry; Pearson Education Limited: Edinburgh, England, 2005.

58. Commission, C. to Regulation (2005).(EC) No 1512/2005 amending Regulation (EC) No 753/2002 laying down certain rules for applying Council Regulation (EC) No 1496/1999 as regards the description, designation, presentation and protection of certain wine sector products (OJ L 241, 17.9. 2005). 2005.

Sample Availability: Samples of the compounds are not available from the authors.

Attribution license (http://creativecommons.org/licenses/by/4.0/).

Table 2.1. Calibration curve information of 15 chiral mono-terpenes in different de- aromatized wine matrices.

De-aromatized Low PG De-aromatized High RS 5 5 Ions (L) base (H) base 1 2 3 L L 4 4 H H Compounds ISTD chosen 4 4 L last H first 4 4 (m/z) first middle middle last Slope Slope Slope Slope Slope Slope 2 1 107,121,136 0.21a 0.12b 0.10b 0.14a 0.11b 0.10b 4 2 107,121,136 0.23a 0.12b 0.10b 0.12a 0.12a 0.11a 5 3 139,69,83 0.14a 0.33c 0.25b 0.21a 0.32c 0.29b 6 3 139,69,83 0.13a 0.28c 0.24b 0.19a 0.30b 0.28b 7 3 94,93,111 0.01a 0.02a 0.02a 0.01a 0.02a 0.03a 8 3 94,93,111 0.01a 0.02a 0.02a 0.01a 0.02a 0.03a 9 3 139,69,83 0.09a 0.17b 0.15b 0.11a 0.14b 0.16b 10 3 139,69,83 0.07a 0.13b 0.13b 0.09a 0.11ab 0.13b 11 3 94,93,111 0.01a 0.02a 0.02a 0.01a 0.02a 0.03a 12 3 94,93,111 0.01a 0.02a 0.02a 0.01a 0.02a 0.03a 14 3 121,93,136 0.01a 0.01a 0.01a 0.01a 0.01a 0.01a 16 4 121,93,136 0.01a 0.01a 0.01a 0.01a 0.01a 0.01a 18 5 59,81,121 0.07a 0.06a 0.06a 0.06a 0.06a 0.06a 20 6 59,81,121 0.05a 0.05a 0.05a 0.05a 0.05a 0.05a 21 6 95,109,123 0.03a 0.04a 0.03a 0.03a 0.03a 0.03a

1 The numbers for compounds are the same with Figure 2.1. 2 ISTD=internal standard 3 Numbers in bold are quantification ions 4 R2 for each curve is 0.99 5 The one way ANOVA test was only performed among fiber age inside each matrix, numbers with different superscripts within each matrix are significantly different from one another at p < 0.05 by Tukey’s HSD test.

Table 2.2. LOD, LOQ, percent spiked recovery, reproducibility and standard stability for wine samples with different matrix.

Spik Spik Spik ed Spik Spik ed Spik ed reco ed ed reco ed reco Stand very reco Pinot Co LO reco very reco very Riesling ards (%) very Gris mp D LOQ very (%) very (%) reproduc stabili in (%) reproduc oun (ug/ (ug/L) (%) in (%) in ibility ty RS in ibility ds L) in PG in RS (RSD)g (RSD Medi RS (RSD )h PG Medi RS Medi )i um Swee Drya um Dryc um Swee tf Dryb Dryd te 2 0.10 0.34 106 94 90 87 103 114 15.60 0.00 12.1

4 0.08 0.27 104 93 93 111 106 112 15.91 0.00 11.1 0.00 5 0.001 101 129 119 135 137 119 0.00 0.00 15.2 02 0.00 6 0.001 99 112 132 103 125 105 12.98 0.00 13.0 03 7 0.73 1.09 72 102 90 118 110 97 18.35 17.27 10.7 8 0.44 0.70 72 101 93 112 113 97 18.13 14.29 11.0 0.00 9 0.003 99 116 126 113 120 123 0.00 0.00 12.9 1 0.00 10 0.002 94 102 114 118 110 114 15.57 0.00 12.8 06 11 0.28 0.93 76 103 103 116 118 100 15.12 0.00 15.6 12 0.33 1.11 72 100 97 115 114 96 0.00 15.26 12.8

14 0.03 0.12 101 98 106 101 102 103 0.00 0.00 9.5

16 0.08 0.25 102 100 109 98 101 102 12.57 0.00 9.5

18 0.19 0.62 100 96 112 104 107 102 13.35 14.21 4.3

20 0.15 0.49 98 95 106 101 103 102 14.85 16.00 4.8 21 0.02 0.08 98 103 96 81 108 107 15.60 11.01 15.0

a Three ‘dry’ style Pinot Gris wines; b Four ‘medium dry’ style Pinot Gris wines; c One ‘dry’ style Riesling wine; d Four ‘medium dry’ style Riesling wine; e Seven ‘medium sweet’ style Riesling wine; f Seven ‘sweet’ style Riesling wine; g 2011 dry Riesling, 10.8% alcohol content (v/v), 0.58 g/L residual sugar; h 2013 Pinot Gris, 11.8% alcohol content (v/v), 16.43 g/L residual sugar; i The fourth level of Standards

Table 2.3. Average variation (peak area ratio) of seven mono-terpene standards based on injection and extraction temperature.

Extraction temperature Injector temperature (°C) Standards (°C) 200 °C 230 °C 250 °C 40 °C 60 °C 20 91.5 94.2 93.8 94.9 93.8 14 97.1 97.9 97.9 98.7 97.9 21 98.5 100.0 99.9 100.0 99.9 4 100.0 100.0 100.0 100.0 100.0 2 88.7 85.8 89.5 89.6 89.5 6 15.8 15.4 14.5 14.3 14.5 8 69.0 62.8 64.7 64.5 64.7

Table 2.4. Multiple Comparisons (Tukey) of the average concentration of 12 chiral mono-terpenes for 12 white wines.

(2) S-(-)-limonene ((p<0.0001) (4) R-(+)-limonene (p<0.0001) (5) Rose oxide isomer (p<0.0001) Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* Wine Conc(µg/L) Conf. Int.* R6 11.88 A R6 10.94 A P6 0.33 A R4 10.56 AB R4 9.10 AB R5 0.30 A R3 9.19 AB R3 8.22 AB R4 0.11 AB R5 8.61 AB R5 7.24 AB P5 0.02 AB R1 4.29 ABC R1 3.62 ABC P1 0.02 AB R2 2.79 ABCD P5 1.71 ABCD P2 nd AB P5 2.33 ABCD P6 1.39 ABCD P3 nd AB P6 2.19 ABCD P1 1.29 ABCD P4 nd AB P1 1.57 ABCD P2 0.75 ABCD R1 nd AB P2 0.83 ABCD R2 0.21 ABCD R2 nd AB P3 nd ABCD P4 nd ABCD R3 nd AB P4 nd ABCD P3 nd ABCD R6 nd AB

(7) Linalool oxide isomer (p<0.001) (8) Linalool oxide isomer (p<0.001) (11) Linalool oxide isomer (p=0.000) Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* R5 44.30 A R5 34.28 A R5 14.42 A R2 42.69 AB R2 22.25 AB R4 6.70 AB R4 34.50 ABC R1 20.03 AB P5 5.06 AB R1 29.01 ABC R4 18.28 AB R1 4.20 AB R3 25.42 ABC R3 16.17 AB P6 4.05 AB P1 9.85 ABC R6 13.62 AB P4 3.40 AB P4 9.73 ABC P4 10.66 AB P1 nd AB P3 9.69 ABC P3 9.89 AB P2 nd AB P6 8.90 ABC P5 9.78 AB P3 nd AB R6 8.37 ABC P1 9.25 AB R2 nd AB P5 4.99 ABC P6 8.58 AB R3 nd AB P2 4.69 ABC P2 7.61 AB R6 nd AB

(12) Linalool oxide isomer (p<0.0001) (14) R-(-)-Linalool (p=0.000) (16) S-(+)-Linalool (p<0.0001) Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* R5 17.82 A R6 58.84 A R6 46.49 A R4 14.86 AB R3 30.61 AB R3 37.99 AB R2 14.23 AB R4 26.93 AB R4 29.17 ABC R1 10.96 ABC R2 12.77 AB R2 13.47 ABC R3 10.35 ABCD P6 12.33 AB P6 12.59 ABC P6 5.10 ABCD P5 12.00 AB P5 12.51 ABC P4 5.03 ABCD R1 11.82 AB R1 11.54 ABC P5 4.35 ABCD R5 7.27 AB R5 9.67 ABC P3 4.26 ABCD P1 5.26 AB P1 5.44 ABC P2 3.69 ABCD P4 nd AB P4 nd ABC P1 3.62 ABCD P3 nd AB P2 nd ABC R6 1.02 ABCD P2` nd AB P3 nd ABC

(20) (+)-α-Terpineol (p<0.0001) (18) (-)-α-Terpineol (18) (p<0.0001) (21) R-(+)-β-citronellol (p<0.0001) Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* Wine Conc (µg/L) Conf. Int.* R4 65.52 A R4 76.12 A P2 8.30 A R3 54.09 AB R6 59.47 AB P6 5.78 AB R6 50.21 AB R5 53.57 ABC R3 5.72 AB R5 47.60 AB R3 51.66 ABCD P5 5.38 ABC R1 31.08 ABC R1 35.71 ABCDE P4 4.64 ABCD R2 27.98 ABC R2 30.28 ABCDE R4 4.03 ABCDE P1 15.12 ABC P1 18.87 ABCDE P1 3.85 AB DEF P5 14.07 ABC P5 17.72 ABCDE R5 3.75 AB DEF P6 13.57 ABC P3 17.29 ABCDE R1 3.62 ABC EF P4 13.45 ABC P4 16.77 ABCDE R6 2.99 ABCD F P2 5.79 ABC P6 15.45 ABCDE P3 2.97 ABCD F P3 5.22 ABC P2 7.70 ABCDE R2 nd ABCD G

* Different letters within each compound are significantly different from one another at p < 0.05 by Tukey’s HSD test. Conf. Int. refers to confident interval.

Table 2.5. Odor descriptors, purity, CAS# and perception threshold (µg/L) for chemical standards.

Perception Purity Compounds odors CAS No.b threshold (%) (µg/L) 1a N/A N/A N/A 500 (Lester harsh, turpentine-like, lemon note (Lester Friedman & 2 89.6 5989-54-8 Friedman & John G Miller, 1971) John G Miller, 1971) 3a N/A N/A N/A 200 (Lester Fresh, slightly orange note (Lester Friedman & 4 99.0 5989-27-5 Friedman & John G Miller, 1971) John G Miller, 1971) 50 (Brenna et Herbal, green, floral, hay al., 2003; 5 99.0 16409-43-1 green, earthy, heavy (Brenna et al., 2003) Yamamoto et al., 2002) 0.5 (Brenna et Floral, green, clean, sharp, al., 2003; 6 99.0 16409-43-1 light, rose green (Brenna et al., 2003) Yamamoto et al., 2002) 3000-4000 7 Earthy, leafy (Dongrnei et al., 1994) 97.0 60047-17-8 (Rapp, 1990) Stronger earthy, leafy (Dongrnei et al., 3000-4000 8 97.0 60047-17-8 1994) (Rapp, 1990) 160 (Brenna et Floral green, green herbal, minty, fruity al., 2003; 9 99.0 16409-43-1 (Brenna et al., 2003) Yamamoto et al., 2002) 80 (Brenna et Herbal, green, floral, fruity, al., 2003; 10 herbal, rose, citrus (bitter 99.0 16409-43-1 Yamamoto et peel) (Brenna et al., 2003) al., 2002) Sweet, floral, creamy (Dongrnei et al., 3000-4000 11 97.0 60047-17-8 1994) (Rapp, 1990) Sweet, floral, creamy (Dongrnei et al., 3000-4000 12 97.0 60047-17-8 1994) (Rapp, 1990) 1216673-02- 13 99.4 N/A 7 0.8 (Barba et 14 Woody, lavender (Brenna et al., 2003) 99.0 78-70-6 al., 2010) 1216673-02- 15 99.4 N/A 7 7.4 (Barba et 16 Sweet, petigrain (Brenna et al., 2003) 99.0 78-70-6 al., 2010)

17 99.9 203633-12-9 N/A 300,000 coniferous odor, tarry, cold pipe like 18 96.0 98-55-5 (Cacho et al., (Boelens et al., 1993) 2012) 19 99.9 203633-12-9 N/A 300,000 heavy floral lilac-like odor (Boelens et al., 20 96.0 98-55-5 (Cacho et al., 1993) 2012) Slightly oily light rosy-leafy, 50 (Yamamoto 21 petal-like odor with 98.0 1117-61-9 et al., 2004) irritating top note (Yamamoto et al., 2004) a synthesized in the lab b compounds with the same CAS No. were from the isomer mixture

Table 2.6. Six point concentration of each compound for calibration.

Standard 1 Standard Standard Standard Standard Standard Compound (µg/L) 2 (µg/L) 3 (µg/L) 4 (µg/L) 5 (µg/L) 6 (µg/L) 2 0.00 0.65 1.29 2.58 5.16 7.74 4 0.00 0.77 1.52 3.04 6.08 9.12 5 0.00 0.04 0.08 0.17 0.34 0.50 6 0.00 0.17 0.33 0.66 1.32 1.98 7 0.00 3.06 6.09 12.14 24.32 36.46 8 0.00 3.17 6.31 12.58 25.20 37.78 9 0.00 0.06 0.12 0.23 0.47 0.71 10 0.00 0.02 0.04 0.09 0.18 0.27 11 0.00 2.33 4.64 9.25 18.53 27.77 12 0.00 2.49 4.95 9.86 19.75 29.62 14 0.00 2.45 4.88 9.72 19.48 29.20 16 0.00 2.36 4.69 9.34 18.71 28.05 18 0.00 2.88 5.72 11.41 22.86 34.28 20 0.00 4.80 9.55 19.05 38.15 57.19 21 0.00 1.02 2.03 4.05 8.12 12.17

Table 2.7. Riesling and Pinot Gris white wine samples from different regions.

Residual Alcohol Wine type Wine sugar Vintage Region Sub-region content (Commission, code content (v/v) 2005) (g/L) P1 2011 Italy Friuli Grave 12.50% 0.86 Dry

P2 2013 Oregon Willamette Valley 13.17% 2.68 Dry P3 2012 Oregon Willamette Valley 13.89% 3.95 Dry P4 2013 Oregon Willamette Valley 12.62% 4.23 Medium dry P5 2013 Australia Limestone Coast 14.06% 5.49 Medium dry New P6 2013 Auckland 12.91% 7.41 Medium dry Zealand R1 2013 Australia Eden valley 11.63% 3.72 Dry R2 2012 Oregon Willamette Valley 13.17% 2.68 Dry

R3 2012 Washington Columbia Valley 12.92% 5.69 Medium dry Medium R4 2012 Washington Yakima valley 12.52% 15.00 sweet Medium R5 2012 New York Finger lakes 11.43% 15.27 sweet R6 2013 Washington Columbia Valley 7.07% 95.83 Sweet

(x10,000,000) TIC (1.00) 2.75 13

2.50 15

2.25 20

2.00 14 16 18 1.75

1.50 7 8 1.25 17 19

1.00 4 1112 2 21 0.75

0.50 6 3 1 0.25 5 9 10 0.00 35.0 37.5 40.0 42.5 45.0 47.5 50.0 52.5 55.0 57.5

Figure 2.1. Separation of chiral monoterpenes and deuterium isotopes mixture using MDGC-MS.

Numbers referred to the compounds: (1) d3-S-(-)-limonene, (2) S-(-)-limonene, (3) d3-R- (+)-limonene, (4) R-(+)-limonene, (5) (-)-(2S,4R)-cis-rose oxide, (6) (+)-(2R,4S)-cis-rose oxide, (7) (2R,5R)-(+)-trans-linalool oxide, (8) (2R,5S)-(-)-cis-linalool oxide, (9) (-)- (2R,4R)-trans-rose oxide, (10) (+)-(2S,4S)-trans-rose oxide, (11) (2S,5S)-(-)-trans- linalool oxide, (12) (2S,5R)-(+)-cis-linalool oxide, (13) d3-R-(-)-linalool, (14) R-(-)- linalool, (15) d3-S-(+)-linalool, (16) S-(+)-linalool, (17) d3-(-)-α-terpineol, (18) (-)-α- terpineol, (19) d3-(+)-α-terpineol, (20) (+)-α-terpineol, (21) R-(+)-β-citronellol

5 14 R6 16 4

3 4 2 R3 2 20 18 1 R4 21 P5 P1 0 6 P2 P3 10 F2 (28.48 %) (28.48 F2 P4 -1 P6 R1 R2 -2 7 -3 8 5 12 -4 9 11 R5

-5 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 F1 (50.87 %)

Figure 2.2. PCA plot of 12 white wines on concentration of chiral mono-terpenes.

Figure 2.3. Chemical structures of the chiral monoterpenes isomers.

CHAPTER 3

Free Monoterpene Isomer Profiles of Eight Vitis vinifera L. cv. White Wines

Mei Song1, Claudio Fuentes2, Athena Loos1 and Elizabeth Tomasino1,*

This paper has been submitted for publication in the Journal of Agricultural and Food

Chemistry.

1 Department of Food Science & Technology, Oregon State University, Wiegand

Hall, Corvallis, Oregon, USA 97331

2 Department of Statistics, Oregon State University, Weniger Hall, Corvallis,

Oregon, USA 97331

*Author to whom correspondence should be addressed; E-Mail:

[email protected]; Tel.: 541-737-4866.

ABSTRACT

Monoterpene compounds contribute floral and fruity characters to wine and are desired by grape growers and winemakers for many white wines. However, monoterpene isomers, especially monoterpene enantiomers, have been little explored. It is possible to identify and quantitate 17 monoterpene isomers in 148 varietal wines from eight grape varieties; Chardonnay, Gewürztraminer, Muscat, Pinot gris, Riesling, Sauvignon blanc,

Torrontes and Viognier in two vintages by HS-SPME-MDGC-MS. Results obtained from general linear models and discriminant analysis showed significant differences for the isomer profiles and enantiomer fractions among the eight grape varieties and four wine styles. The high R2 values from the fitted line show low variation in enantiomeric differences based on variety. These results provide an overview of the monoterpene isomers of wide varietal wines, and support that isomer profiles and enantiomer fractions could differentiate our wines by varietal and wine style.

KEYWORDS:

Chiral; Enantiomer fraction; MDGC-MS; Discriminant analysis; General linear model

3.1. INTRODUCTION

White wines are frequently characterized by floral and fruity aromas, and these characteristics are major factors in determining the white wine character and quality.

Monoterpenes have been widely investigated as they are known to contribute to the flora and fruity aromas typical to aromatic white wines (Marais, 1983). Monoterpenes are secondary metabolites that are primarily derived from grapes and affected by fermentation. Therefore monoterpene profiles including linalool oxide, linalool, hotrienol, nerol oxide, and citronellol have been used for varietal and place of origin classification (Calleja & Falqué, 2005; Rapp, 1990; Schreier & Jennings, 1979; Zamuz &

Vilanova, 2006). For instance, linalool, nerol, geraniol, terpineol, linalool oxide, rose oxide, and nerol oxide have been used to differentiate Muscat wines from different regions (Versini et al., 1990a; Vilanova et al., 2013; Wagner et al., 1977; Williams et al.,

1981). Terpene profile patterns have shown to differentiate Germany Muscat wines from neutral white wines (e.g., Sylvaner) as well (Rapp, 1990; Rapp et al., 1978). However, there is limited information on enantiomeric composition of monoterpenes in white wines, and the differences in isomers have the potential to greatly influence the aroma of these wines. Despite their importance, monoterpenes are generally minor compounds with trace concentrations in grapes and wines and quantitation for these isomers are very limited to date.

There is an increasing interest in the determination of the enantiomeric ratios of chiral compounds in food flavors, fragrances and additives (Armstrong et al., 1990;

Marchelli et al., 1996). Monoterpene enantiomers possess different sensory characteristics, such as R-(-)-linalool with a described aroma of woody or lavender, while

S-(+)-linalool possessing sweet, petigrain-like aroma (Lehmann et al., 1995; Peña et al.,

2005c). These different enantiomers also have very different perception thresholds, R-(-)- linalool (0.8 µg/L) has the odor perception 10 times lower than S-(+)-linalool (7.4 µg/L) in air (Padrayuttawat et al., 1997a). Therefore wines with slight variations in monoterpene compositions, especially enantiomeric ratios, may result in very different aroma perception.

The present study was designed to investigate the monoterpene isomers in white wines produced from eight grape varieties collected from different regions and two vintages. The main objective was to determine the important monoterpenes isomers and enantiomer fractions in varietal wines, including any effect due to wine style. The different profiles of isomers may be important to the sensory differences in wines and can be used by the industry as markers of varietal quality.

3.2. MATERIALS AND METHODS

3.2.1. Chemicals

Chemical standards of S-(-)-limonene (≥99.0%), R-(+)-limonene (≥99.0%), (-)- rose oxide (≥99.0%), furanoid linalool oxide (≥97.0%), R-(-)-linalool (≥98.0%), were used to check the elution order of the isomers. Linalool (≥97.0%), R-(+)-α-terpineol

(≥97.0%), and R-(+)-β-citronellol (98.0%) were purchased from Sigma Chemical Co. (St.

Louis, MO, USA). S-(-)-α-Terpineol (96.0%) was purchased from BOC sciences

(Ramsey Road, Shirley, NY, USA). Nerol oxide (99.0%) was bought from ALFA chemistry (Waverly Avenue, Holtsville, NY, USA). D3-(±)-α-terpineol and d3-(±)- linalool (≥99.4%) were obtained from CDN Isotopes (Pointe-Claire, QC, Canada). D3-

(±)-limonene was synthesized in the lab via Diels-Alder and Wittig reactions (Song et al.,

2015). Milli-Q water was obtained from a Millipore Continental water system (EMD-

Millipore, Billerica, MA, USA). HPLC grade ethyl alcohol was obtained from Pharmco-

AAPER (Vancouver, WA, USA). Residual sugar content was analyzed in duplicate according to the revised Rebelein method (Rebelein, 1973).

3.2.2. Samples

One hundred and forty eight commercial white wines from eight grape varieties;

Chardonnay, Gewürztraminer, Muscat, Pinot gris, Riesling, Sauvignon blanc, Torrontes, and Viognier, from two consecutive vintages, 2012 and 2013, were collected from regions known for those varieties (Maul et al., 2014). All wines were purchased between

February 2015 and March 2016. The wines were sampled into three 40 mL amber vials with PTFE/Silicone-lined caps (Supelco, Bellefonte, PA, USA) and three 50 mL centrifuge tubes (VWR International Corp. Visalia, CA, USA) right after purchased and stored at -20 °C until instrument and residual sugar analysis which started during April

2016.

3.2.3. Sample Preparation

Samples were prepared according to Song et al. (Song et al., 2015) with some modifications described as follows. Each wine (2 mL) was diluted 4.5-fold with milli-Q water (6.85 mL) in 20 mL amber glass vials (Restek Corporation, Bellefonte, PA, USA).

An isotopically-labelled internal standard solution (150 μL) was added, followed by 4.0 g

of sodium chloride (VWR/JT Baker). The SPME vials were tightly capped with 18 mm

PTFE-lined screw caps (Sigma Aldrich).

The standard curves containing each isomer and the internal standard were established using de-aromatized dry Chardonnay wine following the stable isotope dilution analysis method (Siebert et al., 2005). A number of white wines were investigated but Chardonnay was found to be the most appropriate across all the wine styles (data not shown). Dry Chardonnay wine contained less aroma compounds and residual sugar contents which minimized the matrix effects on the monoterpenes (Song et al., 2015). Standard curves were run twice every 32 samples to minimize any fiber effects

(Song et al., 2015).

3.2.4. Head Space Solid Phase Micro-Extraction Coupled with MDGC-MS (HS-SPME-

MDGC-MS)

The three-phase divinylbenzene/carboxen/polydimethylsiloxan

(DVB/CAR/PDMS) Stableflex SPME fiber (50/30 µm thick, 2cm long, 24 Ga, Supelco,

Bellefonte, PA, USA) with Shimadzu heart cut-MDGC-MS fitted with a Shimadzu AOC-

5000 plus auto-sampler was used to perform sample analysis. Prior to SPME fiber extraction, samples were equilibrated with agitation for 20 min (5 sec on, 2 sec off) at 60

°C. They were then extracted for 50 min with no further agitation. The fiber was injected into the MDGC-MS for 5 min at 250 °C followed by further conditioning in an NDL heater for 3 min at 250 °C.

An Rtx-wax column (Restek Corporation, PA, USA) was applied in the first GC.

An Rt®-βDEXsm connected using a zero dead volume internal union (Valco Instruments

Co. Inc. Texas, USA) to a Rt®-βDEXse column (Restek Corporation, PA, USA) in series in the second GC. Method parameters were altered from Song et al.,(Song et al.,

2015) due to the inclusion of nerol oxide isomers, as follows. Injector temperature was at

250 °C. The column oven for the first GC was held at 65 °C for 2 min, and then increased to 80 °C at 8 °C/min, following ramp to 125 °C at 2 °C/min for 20 min, then further increased to 230 °C at 8 °C/min and held at this temperature for 10 min. The column oven for the second GC was held at 40 °C for 2 min, then increased to 95 °C at 5.0

°C/min, held for 45 min, followed by an increase of 2.0 °C/min to 100 °C for 10 min, then further increased to 130 °C at 4.0 °C/min for 4 min, finally increased to 220 °C at

20.0 °C/min and held at this temperature for 3 min. Quantifier, qualifier ions and heart- cut timings in the first GC selected for monoterpene isomers can be found in Table S 3.1.

3.2.5. Statistical Analysis

Collected data was analyzed using general linear models (GLM) and discriminant analysis (DA) to study the relationship between the monoterpene isomer profiles, grape varieties and wine style. One way ANOVA and Tukey’s honest significant difference

(HSD) were used to compare mean differences among groups. All analyses were performed using IBM SPSS statistic 20 (SPSS Inc., Chicago, IL).

3.3. RESULTS

3.3.1. Varietal Wines

Eight white grape varieties were selected and sampled from various regions

(Table 3.1). Samples were balanced for all grape varietals over region and vintage except

for Torrontes wines. Argentina is the most well-known growing region for this grape variety and wines from this varietal could not be found from other regions.

Wine style was categorized according to European regulation (Commission,

2005). Wine with residual sugar content less than 4 g/L can be considered as “dry”; between 4 g/L and 12 g/L as “medium dry”; between 12 g/L and 45 g/L as “medium sweet”, and above 45 g/L as “sweet” wine. As can be seen in Table 3.1, most of the

Chardonnay, Pinot gris, Riesling, Sauvignon blanc, Torrontes and Viognier wines were dry and medium dry; Muscat wines were sweet; and Gewürztraminer wines were abundant in medium dry and medium sweet styles.

3.3.2. Monoterpene Content in Varietal Wines

Seventeen monoterpene isomers, found in common across all wines, were well separated in single MDGC-MS run (Figure S 3.2 A-B). Standards for rose oxide, linalool oxide and nerol oxide were isomer mixtures due to a lack of commercial resources for the singe isomers. The enantiomeric ratio was determined by the peak area ratio from three

MDGC-MS injections of each isomer standard. The elution order for these isomers were determined from previous research using the same column ("A guide to the analysis of chiral compounds by GC," 1997). Of the monoterpenes quantitated, two were monoterpene hydrocarbons, S-(-)-limonene and R-(+)-limonene; ten were monoterpene oxides, (2R, 4S)-(+)-cis-rose oxide, (2S, 4R)-(-)-cis-rose oxide, (2R, 4R)-(-)-trans-rose oxide, (2S, 4S)-(+)-trans-rose oxide, (2R, 5R)-(+)-trans-linalool oxide, (2R, 5S)-(-)-cis- linalool oxide, (2S, 5S)-(-)-trans-linalool oxide, (2S, 5R)-(+)-cis-linalool oxide, S-(-)-

nerol oxide, and R-(+)-nerol oxide; five were monoterpene alcohols, R-(-)-linalool, S-(+)- linalool, S-(-)-α-terpineol, R-(+)-α-terpineol, and R-(+)-β-citronellol (Table 3.2).

Significant differences (ANOVA, p<0.05) for all monoterpene isomer concentrations were found among the eight varieties (Table 3.2). Higher concentrations of total isomers were found in Muscat and Torrontes wines (> 1.2 mg/L) compared to other varieties, and the monoterpene constituents of these two varieties were very similar.

The lowest concentrations of total isomers (< 40 µg/L) were found in Chardonnay and

Pinot gris wines, which also had similar monoterpene profiles.

Total monoterpene hydrocarbons, which contribute citrus-like aromas (Brenna et al., 2003), were abundant in Muscat (18.7 µg/L) and Torrontes (15.1 µg/L) wines. Rose oxides, described as a rose-like aroma (Peña et al., 2005b), occurred at greater concentrations in Torrontes (4.0 µg/L), Gewürztraminer (1.2 µg/L), and Muscat wines

(1.1 µg/L). Linalool oxide and nerol oxide isomers with their green, leafy, spicy, floral characters (Ohloff et al., 1980; Perkins et al., 2005), occurred at greater quantities in wines from Torrontes (604.9 µg/L) and Muscat (405.2 µg/L), followed by Riesling wines

(103.6 µg/L). Monoterpene alcohols with their floral and fruity aromas (Garneau et al.,

2014b; Z. Gunata et al., 1988; Peña et al., 2005b) showed the highest concentrations in

Muscat (779.9 µg/L) and Torrontes (636.6 µg/L) wines.

Not only did the isomer concentrations differ for all eight varieties, the monoterpene isomers with the greatest concentration in each varietal wine also differed

(Figure 3.1, p<0.05). Total monoterpene alcohols were dominant in Gewürztraminer,

Viognier, Muscat and Torrontes wines. Total linalool oxides and nerol oxide isomers had higher percentage in Sauvignon blanc, Pinot gris, Riesling and Chardonnay wines.

All wines were selected from different wineries, grape varieties and regions and were made in different ‘styles’ with varied amount of residual sugar. In order to determine any varietal and style effects that may influence monoterpene content, we considered a GLM procedure to model the monoterpene isomer profiles in wines in terms of two factors (no vintage effect was found, data not shown): grape variety and wine style. Due to restrictions with the degrees of freedom, additive models were used for most of the isomers, with the exception of the (2R, 4S)-(+)-cis-rose oxide, (2S,5R)-(+)-cis- linalool oxide and S-(-)-nerol oxide isomers, for which we explicitly considered the variety-style interaction term. The results showed that the mean concentration of each isomer had significant differences among the eight grape varieties and four wine styles

(Table 3.3).

3.3.3. Classification of the Grape Variety and Wine Style Based on Monoterpene Isomer

Concentrations

According to GLM results, grape variety and style were significant factors for the model. For the discriminant analysis, the concentrations of 17 isomers were regarded as the independent variables, while the classes of grape varieties and styles were treated as categorical variables. The functions summarized in DA used a step-wise selection procedure based on the Wilks’ Lambda method.

Two statistically significant discriminant functions were found, explaining 86% of the variability, with F1 and F2 contributing 66% and 20%, respectively (Figure 3.2). A separation between varietal wines was achieved in spite of the high variability coming from styles, resulting in three groupings. Muscat and Torrontes wines, grouped on the

positive F1 direction, were clearly separated from the other wines (group 1). All compound vectors were in the positive F1 & F2 relating to the wines with the highest monoterpene isomer concentrations, Muscat and Torrontes (Figure S 3.4). Linalool isomers were located in the same quadrant with Muscat wines, while rose oxide and nerol oxide isomers were located with Torrontes wines, so they could be the most important variables for the differentiation of these wines. All other wines were separated based on the F2 axis. Gewürztraminer had high positive scores on the F2 axis (group 2). Wines from Chardonnay, Pinot gris, Viognier, Riesling and Sauvignon blanc were classified in one group which had negative scores along F2 (group 3).

DA was also used to determine wine style based on monoterpene content. Three separated groups can be easily identified (Figure 3.3). Sweet wines were rich in monoterpene hydrocarbons, α-terpineol and linalool oxide isomers and had the highest positive score in the F1 direction. Medium sweet wines contained greater concentrations of (-)-cis-rose oxide, R-(+)-β-citronellol and linalool isomers with lower positive score along F1 axis. Medium sweet wines were separated from sweet wine by the F2 axis. Dry and medium dry wines had similar profiles with relative high concentrations of rose oxide and nerol oxide isomers. This was shown in the structure matrix (Table S 3.5) as well.

3.3.4. Enantiomer Fraction (EF) in Varietal Wines

Enantiomeric ratios have been investigated by other researchers (C. Askari,

Hener, U., Schmarr, H.G., Rapp, A. and Mosandl, A., 1991; Tominaga et al., 2006).

However, when the concentration of the enantiomer in the ratio denominator was zero or

non-detectable, the results were difficult to interpret. Our chosen method of investigating enantiomer differences, using enantiomer fraction (EF) (Harner et al., 2000), avoids this issue. EFs were calculated by dividing the first eluting enantiomer by the total enantiomers of each compound (enantiomer pairs) (Table 3.4, the elution order can be found in Figure S 3.2), for example, S-(-)-limonene enantiomer fraction was calculated by the following equation:

S    limonene S   limonene (EF)  SR  limonene   (  )  limonene

As can be seen in Table 3.4, S-(-)-limonene EF was 0.39 in Chardonnay and Pinot gris, and 0.50 in Sauvignon blanc wines, which were significantly different from other varietal wines (p < 0.05). (2R, 4S)-(+)-cis-Rose oxide EF was lower than 0.50 for all wines which indicates that (2S, 4R)-(-)-cis-rose oxide was the main cis-rose oxide enantiomer in all varietal wines. (2R, 4R)-(-)-trans-Rose oxide EF was greater than 0.50 in all varietal wines and implies that (2R, 4R)-(-)-trans-Rose oxide was the main trans- rose oxide enantiomer. (2R, 5R)-(+)-trans-Linalool oxide and (2R, 5S)-(-)-cis-linalool oxide had EFs greater than 0.50 in all varietal wines except Viognier wines (0.37). S-(-)- nerol oxide and R-(+)-nerol oxide had very similar EF in all varietal wines. R-(-)-linalool and S-(-)-α-terpineol were both more than or equal to the corresponding enantiomer pair in all of the wines.

The enantiomeric differences in the wines from different varieties can be seen vividly in Figure 3.4 and Figure S 3.6. Varieties were separated into two scatterplots

(Figure 3.4 and S 3.6) for the same enantiomer pair. The fitted lines were plotted for all wines from a single variety with some exceptions (Table 3.5), for example, Chardonnay,

Pinot gris and Sauvignon blanc wines in S-(-)-limonene vs. R-(+)-limonene scatterplot did not have fitted lines since there were only one or two data points in the scatterplot for these varieties.

The coefficient of determination, R2, is the square of correlation between the actual value and the predicted value in a linear model, and can be interpreted as a measure of the variability in the response variable of enantiomeric ratios in each variety

(higher R2 values indicating less variability of the response with respect to the fitted line).

Most of the varieties showed high R2 values in enantiomer pairs, with R2 values greater than 0.8 (Table 3.5). Only one enantiomer pair had low R2 values (lower than 0.8) in

Chardonnay, Pinot gris and Viognier wines. The low R2 values in S-(-)-limonene pair of

Riesling and Torrontes wines were all from medium sweet and sweet styles. The low R2 values in (2R, 4S)-(+)-cis-rose oxide pair of Gewürztraminer and Riesling wines were mainly from the variations caused in the wines with higher monoterpene concentrations, for example, the large variation in Gewürztraminer was from concentrations of (2R, 4S)-

(+)-cis-rose oxide or (2S, 4R)-(-)-cis-rose oxide higher than 0.8 µg/L. Most of trans-rose oxide enantiomers in Gewürztraminer wines, trans-linalool oxide enantiomers in

Sauvignon blanc wines, α-terpineol enantiomers in Chardonnay, Pinot gris and

Sauvignon blanc wines were undetectable, therefore the variations (low R2 values) were caused by the concentrations from two groups in single variety. One group was the non- detectable enantiomers with concentrations assigned to LOD/2; the other group was detectable isomers with higher concentrations.

The difference between enantiomer fractions among wines from different varieties can be seen from the slope of the fitted line in the X-Y scatterplots (Table 3.5).

The slopes were very close for all or most of varietal wines in S-(-)-limonene, S-(-)-nerol oxide, R-(-)-linalool or in S-(-)-α-terpineol scatterplots which implied the EF was similar in these enantiomer pairs for all varietal wines. However, the EF was quite different in rose oxide and linalool oxide enantiomer pairs, e.g., (2R, 5R)-(+)-trans-linalool oxide.

3.3.5 Classification of the Grape Variety and Wine Style Based on Enantiomer Fractions

Classification of varietal wines using EF calculation was different than by isomer concentrations (Figure 3.5 A and B). The 86% of variability was explained by two statistically significant discriminant functions, with F1 and F2 contributing 55% and

31%, respectively. Muscat, Torrontes and Riesling wines had similar EF profiles found in the lower positive or negative F1 direction with S-(-)-limonene and (2R, 4S)-(+)-cis-rose oxide EFs as the important variables. Gewürztraminer and Viognier wines were separated from Muscat and Torrontes wines along the F2 axis, with profiles that were slightly different and characterized by (2R, 5S)-(-)-cis-linalool oxide EF. Chardonnay and Pinot gris wines were clustered in the positive F1 and F2 direction with (2R, 4R)-(-)-trans-rose oxide, S-(-)-nerol oxide, S-(-)-α-terpineol and R-(-)-linalool enantiomer fraction as important variables (Figure 3.5 A and B). Sauvignon blanc wines located in the positive

F1 direction with high positive scores, therefore (2R, 5R)-(+)-trans-linalool oxide EF could be important variable to separate this varietal wine from others (Figure 3.5 B).

Style classification based on EFs for sweet and medium sweet wines were mainly distributed in the F1 function (75% of the variability) with high negative scores (Figure

3.5 C). S-(-)-limonene EF were the separating variables (Figure 3.5 D). Dry wines were located in the opposite direction along the positive F1 axis with most of the EFs as the important variables. Medium dry wines were separated in the middle of F1 axis from other styles by (2R, 5S)-(-)-cis-linalool oxide EF (Figure 3.5 D).

3.4. DISCUSSION

Monoterpene concentrations varied substantially between varietal wines. The total concentration of monoterpenes in Muscat and Torrontes wines were about four times greater than in Gewürztraminer wines, six times greater than in Riesling and Viognier wines, and over 30 times greater than in Chardonnay and Pinot gris wines (Table 3.2). In addition, limonene and nerol oxide were seldom reported in these varietal wines. Similar results have been found when investigating free terpene concentrations of linalool, α- terpineol, citronellol and linalool oxides (Mateo & Jiménez, 2000; Ribéreau-Gayon et al.,

1975), Muscat monoterpene content was 10 times higher than in other varieties, including

Chardonnay, Gewürztraminer and Riesling (Mateo & Jiménez, 2000; Ribéreau-Gayon et al., 1975). Recent studies found that rose oxide was highly correlated with Muscat and

Gewürztraminer aroma (Guth, 1997; Ruiz-García et al., 2014). Ong et al. (1999) reported higher cis-rose oxide contents in Gewürztraminer wines compared to our study in older vintages, 1994, 1995 and 1997 (Ong & Acree, 1999). Moreover, (2S, 4R)-(-)-cis-rose oxide was found as the main stereoisomer with high enantiomeric ratios (higher than

90%) in all V. vinifera L. cv. Morio-Muskat must (F. Luan et al., 2006). In our study, the largest concentrations of rose oxide were found in Torrontes wines, followed by

Gewürztraminer and Muscat wines (Table 3.2). However lower enantiomeric differences

(EF: 0.23-0.49) of (2R, 4S)-(+)-cis-rose oxide vs. (2S, 4R)-(-)-cis-rose oxide was detected in our study compared to Luan et al. 2006 (Table 3.4). This may be due to fermentation differences. (2S, 4R)-(-)-cis-Rose oxide is formed through a reduction pathway during yeast fermentation and which may alter the enantiomeric ratio, thus forming more (2R,

4S)-(+)-cis-rose oxide (Koslitz et al., 2008).

Low monoterpene concentrations in Chardonnay wines found in this study are in agreement with other research (Arrhenius et al., 1996; Dimitriadis & Williams, 1984;

Sefton et al., 1993). Specifically, that monoterpene content of Chardonnay must and juice makes up only 5% of the free volatiles (Arrhenius et al., 1996; Dimitriadis & Williams,

1984; Sefton et al., 1993). This was anticipated as Chardonnay is considered more a neutral white wine grape and winemakers use oak and other techniques to increase the wine’s complexity (Guchu et al., 2006; Swipson & Miller, 1984).

The dominant monoterpene compositions differed among varietal wines. Our research shows that total monoterpene alcohols were abundant in Gewürztraminer,

Viognier, Muscat and Torrontes wines (Figure 3.1). Monoterpene alcohols play an important role in the aroma of Muscat and other aromatic grape varieties and are thought to contribute to the fruity and floral notes (Ruiz-García et al., 2014; Salinas et al., 2004).

Other researchers found that linalool was abundant in Muscat grapes with highly distinctive fruit character (Bayonove & Cordonnier, 1970a, 1970b; Y. Gunata et al.,

1985; Wagner et al., 1977). Linalool and citronellol have often been considered as important contributors to the aroma of Gewürztraminer, known for its floral, spicy notes

(Marais, 2015). Linalool oxide and nerol oxide were dominant isomers in Sauvignon blanc, Pinot gris, Riesling and Chardonnay wines (Figure 3.1). Other studies showed little

to no terpene content in Chardonnay, Sauvignon blanc and Pinot gris wines (Vilanova et al., 2013). Our results, however, show that these wines are abundant in linalool oxide and nerol oxide isomers. These differences in monoterpene isomers may be due to different biosynthetic pathways in aromatic and less aromatic grapes.

Monoterpene profiles have been used to characterize grape varieties and varietal wines in other research (Câmara et al., 2004; Rapp, 1990; Versini et al., 1990a) Based on our results the wines can be grouped into three classes for the varietal wines (Figure 3.2), very similar to the classification determined by Rapp et al.(Rapp et al., 1978). The most aromatic varietal wines included Torrontes and Muscat (group 1), Gewürztraminer wines

(group 2) and the less aromatic varietal wines including Chardonnay, Pinot gris, Riesling and so forth (group 3). Interestingly, Riesling was grouped into the less aromatic wines in our study although Riesling has been generally considered as an aromatic grape variety.

Many terpene volatiles are direct products of terpene synthases in grapes

(Dudareva et al., 2004), therefore the groupings based on monoterpene isomers could be linked to grape variety genetic information. The eight grape varieties selected are some of the most cultivated varieties in the world (Maul et al., 2014; Vilanova et al., 2013). To date, the parentage information and genetic associations among these grape varieties are very limited. Torrontes possessed a distinct Muscat flavor and is the second most widely planted white grape cultivar in Argentina. It is very possible that Torrontes was the progeny of a cross between Muscat of Alexandria and Mission (Agüero et al., 2003; This et al., 2006). Consequently, Torrontes could contain some similar genetic information with Muscat that is responsible for monoterpene biosynthesis. This would explain our results, with similar monoterpene isomers in Torrontes and Muscat wines. Research using

microsatellite markers has shown that Sauvignon blanc is progeny from Cabernet sauvignon (J. E. Bowers & Meredith, 1997). Gewürztraminer originates from Italy and is a mutation of Sauvignon blanc (Maul et al., 2014). Riesling originates from Germany, descended from the mother plant Heunisch Weiss (Maul et al., 2014). Chardonnay and

Pinot gris originate from France and are both progeny of Pinot noir (J. Bowers et al.,

1999). Restriction fragment length polymorphism analysis showed that Chardonnay is

80% similar with Riesling, 76% with Sauvignon blanc, and 77% with Viognier (J. E.

Bowers & Meredith, 1996). To some extent this parental information does explain the groupings based on monoterpene isomers in this study. However, further parentage information related to these varieties cannot be traced from available resources.

The differences found in monoterpene content that cannot be explained by possible grape genetics may be linked to winemaking practices and known chemical stability at wine conditions (Maicas & Mateo, 2005; Sefton, 1998). Monoterpene formation can occur through different pathways including, grape biosynthesis

(Breitmaier, 2006a), biotransformation by bacteria or fungi (Bock et al., 1988; De

Carvalho & da Fonseca, 2006), alcoholic fermentation (Hock et al., 1984; Palomo et al.,

2005; Zoecklein et al., 1997), and aging (Peña-Alvarez et al., 2006). The low monoterpene content of Chardonnay wines may be due to de novo production of monoterpenes by Saccharomyces cerevisiae (Carrau et al., 2005) or from the grapes (P.

Williams et al., 1989). Further research into the source of monoterpenes in neutral wines is needed to determine if monoterpene content is due to grape variety or yeast. All other varieties in this study had one or more monoterpene at concentrations above those found by Carrau et al. (2005) (Carrau et al., 2005), supporting the fact that monoterpenes

originate from grapes. Additionally, the profiles of monoterpenes are known to change due to chemical rearrangement (Rapp & Guntert, 1986). Polyols such as 3,7- dimethylocta-l,5-diene-3,7-diol, 3,7-dimethylocta-l,7-diene-3,6-diol, 3,7- dimethyloct-l- ene-3,7-diol, and 3,7-dimethyloct-lene-3,6,7-triol found in grape varieties can be non- enzymatically rearranged under conditions at grape juice pH of 3.2 (P. J. Williams et al.,

1980). The rearrangement results in formation of other monoterpenes, such as nerol oxide and furanoid linalool oxide, which are highly reactive (Williams et al., 1981).

It is well known that certain pairs of enantiomers possess different sensory characteristics which could alter aroma perception in wines. However, there have not been any studies to date on the EFs of monoterpenes in wines. The fitted lines in the X-Y scatterplots of enantiomer pairs had high R2 values for most of varietal wines (Table 3.5).

It implied that the enantiomer difference of each compound is similar in wines from the single variety although these wines were collected from different wineries, regions, vintages and storage conditions. Our work showed that the majority of R2 values were at

0.8 or higher, suggesting that low variation in enantiomeric differences based on variety.

The few low R2 values in the varietal wines may be attributed to several factors, including a low number of data points (e.g., S-(-)-α-terpineol pair in Chardonnay, Pinot gris and Sauvignon blanc wines), equipment error, or some extent of racemization occurred with confounding factors, such as different yeast strains, winemaking procedures, wine pH and storage time (Sefton, 1998). Given that the majority of the R2 values (43 out of 58) were above 0.8 with 41 above 0.9, it seems unlikely that racemization or other differences due to storage or pH effect the EF from our study.

Additional work would be required to completely rule out these factors.

The classification by EFs on varieties was different than by isomer profiles

(Figure 3.2, Figure 3.5). Interestingly, most aromatic wines, such as Muscat, Torrontes,

Gewürztraminer, Riesling and Viognier were in one group, while neutral varietal wines,

Chardonnay and Pinot gris were in another group. It was reported that monoterpene synthases were not completely stereospecific in some species, therefore the accumulation of varied ratios of enantiomers occurred from a single enzyme (Finefield et al., 2012).

The different EFs between aromatic grapes and neutral grape varieties may be related to the degree of stereo-specificity of monoterpene synthases or the differences in

Chardonnay and Pinot gris may be due to yeast rather than grape origins of monoterpenes

(Carrau et al., 2005).

Wine style was also found to impact the isomer profiles and EF of these varietal wines (Figure 3.3, Figure 3.5). Monoterpene isomers in sweeter wines contained greater concentrations of linalool oxides, monoterpene alcohols and hydrocarbons. In addition, despite the differences in grape varieties, sweeter wines (medium sweet and sweet style) had similar EFs. California dessert wines contained the greatest amount of these isomers

(data not shown). Many dessert wines are fermented from overripe, shriveled/dried grapes. This “drying” process could provide an easier transfer of monoterpenes from skins to must during winemaking since monoterpenes are mostly abundant in grape skin

(Genovese et al., 2007). In addition, the increasing concentrations of total bound terpenes and most individual terpenes in wine have been associated with the increase in grape maturity (Marais, 2015). Research conducted on carrots showed a positive correlation between monoterpenes and sugar content (Rosenfeld et al., 2002), suggesting that

monoterpenes may derive from their glycosides by acid-catalyzed reactions during aging

(Di Stefano, 1989; Rapp & Mandery, 1986).

Despite heterogeneity in regions, styles, vintages and even winemaking techniques, varietal distinctiveness was supported by all of the wines studied based on isomer profiles and EFs. The research demonstrates the importance of isomer profiles and

EFs to varietal white wines. This information is important for grape growers and winemakers that are attempting to produce wines with floral and fruity notes, or in specific distinctive styles. Further work is needed to determine the sensory contribution of the various monoterpene isomer profiles and EFs and the origins of monoterpenes in more neutral varieties.

ABBREVIATIONS USED

HS, head space; SPME, Solid Phase Micro-Extraction; MDGC-MS, multidimensional gas chromatography with mass spectrometry; GLM, general linear model; DA, discriminant analysis; ANOVA, analysis of variance; Tukey's HSD, Tukey’s honest significant difference; EF, enantiomer fraction

ACKNOWLEDGMENT

The authors wish to thank Akira Kurniawan Ishii, Vaishnavi Trivedi, and

Hongyan Yu for their help with the residual sugar analysis in all of the wines investigated.

AUTHOR INFORMATION

Corresponding Author

*E-Mail:[email protected]. Tel.: 541-737-4866.

Funding

This project was funded by the Oregon Wine Board #2014-1516 and the Oregon

Wine Research Institute.

The authors declare no competing financial interest.

REFERENCES

Agüero, C. B., Rodríguez, J. G., Martínez, L. E., Dangl, G. S., & Meredith, C. P. (2003). Identity and parentage of Torrontés cultivars in Argentina. American Journal of Enology and Viticulture, 54(4), 318-321.

Armstrong, D. W., Chang, C. D., & Li, W. Y. (1990). Relevance of enantiomeric separations in food and beverage analyses. Journal of Agricultural and Food Chemistry, 38(8), 1674-1677.

Arrhenius, S., McCloskey, L., & Sylvan, M. (1996). Chemical markers for aroma of Vitis vinifera var. Chardonnay regional wines. Journal of Agricultural and Food Chemistry, 44(4), 1085-1090.

Askari, C., Hener, U., Schmarr, H.G., Rapp, A. and Mosandl, A. (1991). Stereodifferentiation of some chiral monoterpenes using multidimensional gas chromatography. Fresenius' Journal of Analytical Chemistry, 340(12), 768-772.

Bayonove, C., & Cordonnier, R. (1970a). Recherches sur l'arôme du muscat. I. Evolution des constituants volatils au cours de la maturation du Muscat d'Alexandrie. Ann. Technol. Agric, 19(2), 79-93.

Bayonove, C., & Cordonnier, R. (1970b). Recherches sur l'arome du muscat. II. Profils aromatiques de cepages muscat et non muscat. importance du linalol chez les muscats. Ann Technol Agr.

Bock, G., Benda, I., & Schreier, P. (1988). Microbial transformation of geraniol and nerol by Botrytis cinerea. Applied Microbiology and Biotechnology, 27(4), 351-357.

Bowers, J., Boursiquot, J.-M., Chu, K., Johansson, H., & Meredith, C. (1999). Historical genetics: the parentage of Chardonnay, Gamay, and other wine grapes of northeastern France. Science, 285(5433), 1562-1565.

Bowers, J. E., & Meredith, C. P. (1996). Genetic similarities among wine grape cultivars revealed by restriction fragment-length polymorphism (RFLP) analysis. Journal of the American Society for Horticultural Science, 121(4), 620-624.

Bowers, J. E., & Meredith, C. P. (1997). The parentage of a classic wine grape, Cabernet Sauvignon. Nature Genetics, 16(1), 84-87.

Breitmaier, E. (2006). Terpenes: flavors, fragrances, pharmaca, pheromones: John Wiley & Sons.

Brenna, E., Fuganti, C., & Serra, S. (2003). Enantioselective perception of chiral odorants. Tetrahedron: Asymmetry, 14(1), 1-42.

Calleja, A., & Falqué, E. (2005). Volatile composition of Mencıa wines. Food Chemistry, 90(3), 357-363.

Câmara, J., Herbert, P., Marques, J., & Alves, M. (2004). Varietal flavour compounds of four grape varieties producing Madeira wines. Analytica Chimica Acta, 513(1), 203-207.

Carrau, F. M., Medina, K., Boido, E., Farina, L., Gaggero, C., Dellacassa, E., Versini, G., & Henschke, P. A. (2005). De novo synthesis of monoterpenes by Saccharomyces cerevisiae wine yeasts. FEMS Microbiology Letters, 243(1), 107-115.

Commission, C. t. (2005). Regulation (2005).(EC) No 1512/2005 amending Regulation (EC) No 753/2002 laying down certain rules for applying Council Regulation (EC) No 1496/1999 as regards the description, designation, presentation and protection of certain wine sector products (OJ L 241, 17.9. 2005). In): Brussels.

Croghan, C., & Egeghy, P. (2003). Methods of dealing with values below the limit of detection using SAS. Southern SAS User Group, 22-24.

De Carvalho, C. C., & da Fonseca, M. M. R. (2006). Biotransformation of terpenes. Biotechnology Advances, 24(2), 134-142.

Di Stefano, R. (1989). The glycoside nature of terpenes of Muscat grape skins. The β- glycosidase activity of grape skins. Viticultural and Enological Sciences/Die Weinwissenschaft, 44, 158-161.

Dimitriadis, E., & Williams, P. (1984). The development and use of a rapid analytical technique for estimation of free and potentially volatile monoterpene flavorants of grapes. American Journal of Enology and Viticulture, 35(2), 66-71.

Dudareva, N., Pichersky, E., & Gershenzon, J. (2004). Biochemistry of plant volatiles. Plant Physiology, 135(4), 1893-1902.

Finefield, J. M., Sherman, D. H., Kreitman, M., & Williams, R. M. (2012). Enantiomeric natural products: occurrence and biogenesis. Angewandte Chemie International Edition, 51(20), 4802-4836.

Garneau, F.-X., Collin, G., & Gagnon, H. (2014). Chemical composition and stability of the hydrosols obtained during essential oil production. II. The case of Picea glauca (Moench) Voss., Solidago puberula Nutt., and Mentha piperita L. American Journal of Essential Oils and Natural Products, 2, 29-35.

Genovese, A., Gambuti, A., Piombino, P., & Moio, L. (2007). Sensory properties and aroma compounds of sweet Fiano wine. Food Chemistry, 103(4), 1228-1236.

Guchu, E., Díaz-Maroto, M., Pérez-Coello, M., González-Viñas, M., & Ibáñez, M. C. (2006). Volatile composition and sensory characteristics of Chardonnay wines treated with American and Hungarian oak chips. Food Chemistry, 99(2), 350-359.

A guide to the analysis of chiral compounds by GC. (1997). Resteck Corporation.

Gunata, Y., Bayonove, C., Baumes, R., & Cordonnier, R. (1985). The aroma of grapes I. Extraction and determination of free and glycosidically bound fractions of some grape aroma components. Journal of Chromatography A, 331, 83-90.

Gunata, Z., Bitteur, S., Brillouet, J.-M., Bayonove, C., & Cordonnier, R. (1988). Sequential enzymatic hydrolysis of potentially aromatic glycosides from grape. Carbohydrate Research, 184, 139-149.

Guth, H. (1997). Identification of character impact odorants of different white wine varieties. Journal of Agricultural and Food Chemistry, 45(8), 3022-3026.

Harner, T., Wiberg, K., & Norstrom, R. (2000). Enantiomer fractions are preferred to enantiomer ratios for describing chiral signatures in environmental analysis. Environmental Science & Technology, 34(1), 218-220.

Hock, R., Benda, I., & Schreier, P. (1984). Formation of terpenes by yeasts during alcoholic fermentation. Zeitschrift für Lebensmittel-Untersuchung und Forschung, 179(6), 450-452.

Luan, F., Mosandl, A., Gubesch, M., & Wüst, M. (2006). Enantioselective analysis of monoterpenes in different grape varieties during berry ripening using stir bar sorptive extraction-and solid phase extraction-enantioselective-multidimensional gas chromatography-mass spectrometry. Journal of Chromatography A, 1112(1), 369-374.

Maicas, S., & Mateo, J. J. (2005). Hydrolysis of terpenyl glycosides in grape juice and other fruit juices: a review. Applied Microbiology and Biotechnology, 67(3), 322-335.

Marais, J. (1983). Terpenes in the aroma of grapes and wines: a review. South African Journal of Enology and Viticulture, 4(2), 49-60.

Marais, J. (2015). Terpene concentrations and wine quality of Vitis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar. VITIS-Journal of Grapevine Research, 26(4), 231.

Marchelli, R., Dossena, A., & Palla, G. (1996). The potential of enantioselective analysis as a quality control tool. Trends in Food Science & Technology, 7(4), 113-119.

Mateo, J., & Jiménez, M. (2000). Monoterpenes in grape juice and wines. Journal of Chromatography A, 881(1), 557-567.

Maul, E., Sudharma, K., Ganesh, A., Hundemer, M., Kecke, S., Marx, G., Schreiber, T., Walk, M., vom Weg, S., & Mahler-Ries, A. (2014). 30 Years VIVC-Vitis international variety catalogue (www. vivc. de).

Ohloff, G., Giersch, W., Schulte-Elte, K. H., Enggist, P., & Demole, E. (1980). Synthesis of (R)-and (R)-4-methyl-6-2′-methylprop-1′-enyl-5, 6-dihydro-2H-pyran (nerol oxide) and natural occurrence of its racemate. Helvetica Chimica Acta, 63(6), 1582-1588.

Ong, P. K., & Acree, T. E. (1999). Similarities in the aroma chemistry of Gewürztraminer variety wines and lychee (Litchi chinesis Sonn.) fruit. Journal of Agricultural and Food Chemistry, 47(2), 665-670.

Palomo, E. S., Hidalgo, M. D. a.-M., Gonzalez-Vinas, M., & Pérez-Coello, M. (2005). Aroma enhancement in wines from different grape varieties using exogenous glycosidases. Food Chemistry, 92(4), 627-635.

Peña-Alvarez, A., Capella, S., Juárez, R., & Labastida, C. (2006). Determination of terpenes in tequila by solid phase microextraction-gas chromatography-mass spectrometry. Journal of Chromatography A, 1134(1), 291-297.

Peña, R. M., Barciela, J., Herrero, C., & García‐Martín, S. (2005a). Optimization of solid‐phase microextraction methods for GC-MS determination of terpenes in wine. Journal of the Science of Food and Agriculture, 85(7), 1227-1234.

Peña, R. M., Barciela, J., Herrero, C., & García‐Martín, S. (2005b). Optimization of solid‐phase microextraction methods for GC‐MS determination of terpenes in wine. Journal of the Science of Food and Agriculture, 85(7), 1227-1234.

Perkins, M. L., D'Arcy, B. R., Lisle, A. T., & Deeth, H. C. (2005). Solid phase microextraction of stale flavour volatiles from the headspace of UHT milk. Journal of the Science of Food and Agriculture, 85(14), 2421-2428.

Poole, C. (2009). Handbook of methods and instrumentation in separation science (Vol. 1): Academic Press.

Rapp, A. (1990). Natural flavours of wine: correlation between instrumental analysis and sensory perception. Fresenius' Journal of Analytical Chemistry, 337(7), 777-785.

Rapp, A., & Guntert, M. (1986). Changes in aroma substances during the storage of white wines in bottles. Developments in food science, 1986.

Rapp, A., Hastrich, H., Engel, L., & Knipser, W. (1978). Possibilities of characterizing wine quality and vine varieties by means of capillary chromatography. Flavor of foods and beverages, 391.

Rapp, A., & Mandery, H. (1986). Wine aroma. Experientia, 42(8), 873-884.

Rebelein, H. (1973). Rapid method for the determination of the alcohol, sugar and total SO2 contents (by distillation) in wine and fruit juices and also for determining blood alcohol. Chemie, Mikrobiologie, Technologie der Lebensmittel, 2(4), 112-121.

Ribéreau-Gayon, P., Boidron, J., & Terrier, A. (1975). Aroma of Muscat grape varieties. Journal of Agricultural and Food Chemistry, 23(6), 1042-1047.

Rosenfeld, H., Vogt, G., Aaby, K., & Olsen, E. (2002). Interaction of terpenes with sweet taste in carrots (Daucus carota L.). In XXVI International Horticultural Congress: Advances in Vegetable Breeding 637, (pp. 377-386).

Ruiz-García, L., Hellín, P., Flores, P., & Fenoll, J. (2014). Prediction of Muscat aroma in table grape by analysis of rose oxide. Food Chemistry, 154, 151-157.

Salinas, M., Zalacain, A., Pardo, F., & Alonso, G. L. (2004). Stir bar sorptive extraction applied to volatile constituents evolution during Vitis vinifera ripening. Journal of Agricultural and Food Chemistry, 52(15), 4821-4827.

Schreier, P., & Jennings, W. G. (1979). Flavor composition of wines: a review. Critical Reviews in Food Science and Nutrition, 12(1), 59-111.

Sefton, M. (1998). Hydrolytically-released volatile secondary metabolites from a juice sample of Vitis vinifera grape cvs Merlot and Cabernet Sauvignon. Australian Journal of Grape and Wine Research, 4(1), 30-38.

Sefton, M., Francis, I., & Williams, P. (1993). The volatile composition of Chardonnay juices: a study by flavor precursor analysis. American Journal of Enology and Viticulture, 44(4), 359-370.

Shrivastava, A., & Gupta, V. B. (2011). Methods for the determination of limit of detection and limit of quantitation of the analytical methods. Chronicles of Young Scientists, 2(1), 21.

Siebert, T. E., Smyth, H. E., Capone, D. L., Neuwöhner, C., Pardon, K. H., Skouroumounis, G. K., Herderich, M. J., Sefton, M. A., & Pollnitz, A. P. (2005). Stable isotope dilution analysis of wine fermentation products by HS-SPME-GC-MS. Analytical and Bioanalytical Chemistry, 381(4), 937-947.

100

Song, M., Xia, Y., & Tomasino, E. (2015). Investigation of a quantitative method for the analysis of chiral monoterpenes in white wine by HS-SPME-MDGC-MS of different wine matrices. Molecules, 20(4), 7359-7378.

Swipson, R., & Miller, G. (1984). Aroma composition of Chardonnay wine. Vitis, 23, 143-158.

This, P., Lacombe, T., & Thomas, M. R. (2006). Historical origins and genetic diversity of wine grapes. Trends in Genetics, 22(9), 511-519.

Tominaga, T., Niclass, Y., Frérot, E., & Dubourdieu, D. (2006). Stereoisomeric distribution of 3-mercaptohexan-1-ol and 3-mercaptohexyl acetate in dry and sweet white wines made from Vitis vinifera (Var. Sauvignon Blanc and Semillon). Journal of Agricultural and Food Chemistry, 54(19), 7251-7255.

Versini, G., Rapp, A., Volkmann, C., & Scienza, A. (1990). Flavour compounds of clones from different grape varieties. Vitis, 513-524.

Williams, Strauss, C., & Wilson, B. (1981). Classification of the monoterpenoid composition of Muscat grapes. American Journal of Enology and Viticulture, 32(3), 230- 235.

Williams, P., Sefton, M. A., & Wilson, B. (1989). Nonvolite conjugates of secondary metabolites as precursors of varietal grape flavor components. In ACS Symposium series- American Chemical Society (USA)).

Williams, P. J., Strauss, C. R., & Wilson, B. (1980). Hydroxylated linalool derivatives as precursors of volatile monoterpenes of Muscat grapes. Journal of Agricultural and Food Chemistry, 28(4), 766-771.

Zamuz, S., & Vilanova, M. (2006). Volatile composition of the Vitis vinifera Albarino musts according to geographic areas from Rias Baixas DO (Spain). Italian journal of food science, 18(3), 323.

Zoecklein, B., Marcy, J., Williams, J., & Jasinski, Y. (1997). Effect of native yeasts and selected strains of Saccharomyces cerevisiae on glycosyl glucose, potential volatile yerpenes, and selected aglycones of white Riesling (Vitis vinifera L.) wines. Journal of Food Composition and Analysis, 10(1), 55-65.

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Table 3.1. Distribution of varietal wines across, region of origin, vintage and wine style.

Style of wine (bottles) Variety Regiona Vintage Medium Medium Dry Sweet dry sweet 2012 3 AU 2013 2 2 2012 4 Chardonnay OR 2013 1 2 1 2012 3 CAL 2013 2 1 2012 1 1 1 OR 2013 1 2 2012 2 1 FR 2013 1 4 Gewürztraminer 2012 1 1 NY 2013 2 1 2012 1 CAL 2013 1 2012 2 2 FR Muscat 2013 2 1 CAL 2012 2

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2013 1 2 2012 2 IT 2013 3 2012 4 OR 2013 3 1 2012 3 Pinot gris FR 2013 3 2012 2 2 IT 2013 2 1 2012 3 OR 2013 1 2012 3 FR Riesling 2013 1 3 2012 1 2 GR 2013 1 1 1 AU 2013 1 1 2012 3 1 NZ 2013 1 3 2012 2 Sauvignon blanc SA 2013 3 2012 3 FR 2013 2 1

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2012 4 1 Torrontes ARG 2013 4 1 2012 3 1 FR 2013 3 2012 1 Viognier OR 2013 1 3 2012 3 1 CAL 2013 3 1 aARG: Argentina, AU: Australia, CAL: California, FR: France, GR: Germany, IT: Italy, NY: New York, NZ: New Zealand, OR: Oregon, SA: South Africa

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Table 3.2. Mean concentrations of isomers*± standard error from different varietal wines (µg/L) using ANOVA with Tukey’s HSD (α= 0.05) **

Chardonna Gewürztramin Pinot Sauvigno Muscat Riesling Torrontes Viognier y er gris n blanc 11.96±2.0 0.03±0.0 0.87±0.20 0.08±0.02 1.53±0.19 S-(-)-limonene 0.03±0.00a 3.17±0.39b 9.70±0.67c 0c 0a ab a ab R-(+)- 0.04±0.0 0.32±0.09 0.05±0.00 0.74±0.10 0.04±0.00a 1.69±0.23a 6.78±1.10b 5.39±0.45b limonene 0a a a a Total 18.74±3.0 0.07±0.0 1.19±0.27 0.13±0.02 15.08±1.0 2.27±0.29 0.07±0.00a 4.86±0.60b hydrocarbon 8c 0a ab a 5c ab (2R, 4S)-(+)- 0.04±0.0 0.07±0.02 0.04±0.01 0.06±0.02 0.02±0.00a 0.20±0.04bc 0.34±0.09c 0.80±0.11d cis-rose oxide 1ab ab ab ab (2S, 4R)-(-)- 0.09±0.0 0.07±0.01 0.07±0.01 0.06±0.00 0.06±0.00a 0.70±0.17bc 0.50±0.08b 0.85±0.13c cis-rose oxide 2a a a a (2R, 4R)-(-)- 0.01±0.0 0.04±0.02 0.02±0.02 0.00±0.00 trans-rose 0.00±0.00a 0.25±0.05a 0.20±0.07a 1.57±0.67b 0a a a a oxide (2S, 4S)-(+)- 0.00±0.0 0.02±0.01 0.01±0.01 0.00±0.00 trans-rose 0.00±0.00a 0.05±0.01a 0.11±0.03a 0.74±0.23b 0a a a a oxide Total rose 1.14±0.17b 0.14±0.0 0.19±0.05 0.15±0.05 0.12±0.02 0.08±0.00a 1.19±0.22c 3.96±1.01d oxide c 3a ab a a (2R,5R)-(+)- 120.55±25 7.11±2.1 32.22±6.4 23.63±4.6 188.60±36 7.51±1.84 trans-linalool 8.53±2.49a 9.70±2.15a .80b 3a 7a 6a .82c a oxide (2R,5S)-(-)-cis- 136.21±28 11.77±2. 19.78±4.1 8.82±1.88 139.63±25 19.32±4.5 6.98±2.05a 20.79±4.78a linalool oxide .73b 38a 2a a .03b 0a (2S,5S)-(-)- 47.32±10. 4.48±1.1 7.78±1.70 2.02±0.79 63.78±13. 9.13±2.21 3.14±1.04a 7.93±1.74a trans-linalool 46b 4a a a 16b a

105

oxide

(2S,5R)-(+)- 67.42±14. 4.53±1.1 14.75±3.4 8.86±1.54 82.39±14. 9.80±2.11 cis-linalool 3.48±1.03a 5.86±1.13a 63b 8a 3a a 63b a oxide S-(-)-nerol 14.41±1.9 0.80±0.4 12.27±2.5 6.33±1.17 53.35±11. 0.33±0.18 0.07±0.07a 1.83±0.30ab oxide 9c 0a 1bc abc 14d a R-(+)-nerol 19.30±2.6 0.88±0.4 16.76±3.4 6.86±1.26 77.12±17. 0.43±0.21 0.00±0.00a 2.53±0.41ab oxide 4c 2ab 7bc abc 49d a Total linalool 22.20±6.5 405.20±80 29.58±7. 103.55±2 56.50±10. 604.87±11 46.51±10. and nerol 48.65±10.34a 5a .48b 40a 1.32a 48a 4.29c 34a oxide 127.63±36 0.14±0.1 2.96±1.02 0.54±0.30 63.35±10. 29.85±5.1 R-(-)-linalool 0.77±0.34a 57.49±4.81bc .88d 3a ab a 94c 9abc 108.24±31 0.08±0.0 2.90±1.05 0.49±0.29 48.26±10. 24.90±4.8 S-(+)-linalool 0.68±0.32a 55.27±5.97b .80c 7a a a 08ab 7ab S-(-)-α- 276.36±39 5.63±0.6 30.31±3.3 10.13±1.4 264.04±15 49.02±4.7 1.80±0.22a 56.35±7.06a terpineol .95b 2a 3a 0a .79b 5a R-(+)-α- 252.72±34 2.87±0.7 26.19±3.2 3.28±0.92 248.49±14 45.36±4.4 0.45±0.16a 58.89±7.62b terpineol .37c 4a 9ab a .22c 3ab R-(+)-β- 14.98±5.7 1.21±0.2 0.44±0.20 0.70±0.23 12.51±1.8 2.70±0.46 1.67±0.27a 17.55±2.69c citronellol 8c 9a a a 2bc ab 779.94±14 9.92±1.0 62.80±8.0 15.13±2.4 636.64±48 151.84±1 Total alcohols 5.36±0.98a 245.56±22.89b 3.43c 8a 3ab 1a .91c 6.01ab 27.71±6.3 1205.02±1 39.71±7. 167.73±2 71.90±11. 1260.55±8 200.74±2 Total isomers 300.26±30.65a 6a 74.02b 71a 2.69a 19a 1.84b 0.32a

*means in the same row with the same letter are not significantly different from each other. ** The value of all non-detectable compounds were assigned to a value of LOD/2 where LOD is calculated from 3.3*(standard deviation of y-intercepts of regression line, SD)/ (slope of the regression line, b) (Croghan & Egeghy, 2003; Poole, 2009; Shrivastava & Gupta, 2011). The detailed information is in Table S 3.3.

106

Table 3.3. GLM multivariate test investigating varietal and style effects.

Effect Test F Sig. Intercept Wilks' Lambda 30.802 .000 varietal Wilks' Lambda 9.032 .000 style Wilks' Lambda 1.852 .001

107

Table 3.4. Enantiomer fractions (EFs)* ± standard error found in different varietal wines determined by ANOVA and Tukey’s HSD (α= 0.05) **.

(2R, 5R)- (2R, 4S)- (2R, 4R)-(- (2R, 5S)-(-)- (+)-trans- S-(-)- (+)-cis-rose )-trans-rose cis-linalool S-(-)-nerol R-(-)- S-(-)-α- linalool limonene/total oxide/total oxide/total oxide/ total oxide/total linalool/total terpineol/total oxide/ total cis trans cis trans Chardonnay 0.39±0.00a 0.23±0.00a 1.00±0.00c 0.78±0.02bc 0.77±0.04d 0.59±0.02d 0.79±0.03bc 0.86±0.05b Gewürztraminer 0.66±0.02b 0.25±0.02ab 0.86±0.03bc 0.49±0.03a 0.75±0.01cd 0.42±0.00ab 0.52±0.01a 0.49±0.00a Muscat 0.63±0.01b 0.41±0.05cd 0.76±0.05b 0.70±0.02bc 0.67±0.01bcd 0.43±0.00ab 0.54±0.01a 0.52±0.00a Pinot gris 0.39±0.00a 0.26±0.02ab 0.98±0.02c 0.65±0.04b 0.79±0.03d 0.52±0.01c 0.85±0.01c 0.75±0.06b Riesling 0.68±0.05b 0.39±0.05bcd 0.86±0.07bc 0.80±0.01c 0.59±0.02ab 0.42±0.00ab 0.71±0.04b 0.55±0.01a Sauvignon 0.50±0.04a 0.28±0.03abc 0.98±0.02c 0.94±0.02d 0.50±0.05a 0.48±0.00bc 0.81±0.03bc 0.82±0.04b blanc Torrontes 0.64±0.01b 0.49±0.02d 0.58±0.07a 0.75±0.01bc 0.63±0.01abc 0.41±0.00a 0.59±0.02a 0.51±0.00a Viognier 0.68±0.02b 0.33±0.05abc 0.99±0.01c 0.37±0.04a 0.64±0.02bc 0.52±0.03c 0.57±0.02a 0.52±0.00a

*means in the same column with the same letter are not significantly different from each other. ** The value of all non-detectable compounds were assigned to a value of LOD/2 where LOD is calculated from 3.3*(standard deviation of y-intercepts of regression line, SD)/ (slope of the regression line, b) (Croghan & Egeghy, 2003; Poole, 2009; Shrivastava & Gupta, 2011). The detailed information is in Table S 3.3.

108

Table 3.5. The R2 value and slope for the fitted line in the X-Y scatterplots of Figure 3.4.

(2R, 4S)-(+)- (2R, 4R)-(-)- (2R, 5R)-(+)- (2R, 5S)-(-)- S-(-)- S-(-)-nerol R-(-)-linalool S-(-)-α- cis-rose trans-rose trans-linalool cis-linalool limonene pair oxide pair pair terpineol pair oxide pair oxide pair oxide pair oxide pair Slop Slop R2 Slope R2 R2 R2 Slope R2 Slope R2 Slope R2 Slope R2 Slope e e - Chardonnay ------0.93 0.40 0.89 0.47 1.00 1.6E- 0.97 0.94 0.35 0.45 34 Gewürztraminer 0.78 0.51 0.27 2.66 0.02 0.06 0.97 0.80 0.82 0.21 1.00 1.39 0.92 1.19 1.00 1.08

Muscat 0.94 0.54 0.27 0.50 0.80 0.42 0.73 0.35 0.88 0.48 1.00 1.32 0.99 0.86 1.00 0.86

Pinot gris - - 0.89 1.91 1.00 0.69 0.90 0.51 0.91 0.47 1.00 1.03 1.00 0.58 0.02 0.32

Riesling 0.40 0.31 0.32 0.29 0.51 0.31 0.92 0.25 0.88 0.78 1.00 1.37 0.97 1.02 0.86 0.92

Sauvignon blanc - - 0.71 0.74 1.00 0.59 0.53 0.13 0.78 0.73 1.00 1.07 0.99 0.95 0.30 0.38

Torrontes 0.48 0.49 0.61 0.97 0.92 0.33 0.88 0.34 0.97 0.58 0.99 1.56 0.85 0.86 0.97 0.88 1.5E Viognier 0.91 0.49 1.00 - - 0.89 1.14 0.60 0.37 0.89 1.07 0.86 0.87 0.96 0.91 -17

109

total monoterpene hydrocarbons percentage 100 total rose oxides percentage total linalool and nerol oxides percentage 90 total monoterpene alcohols percentage c 80 c c

70 c b b c 60 b b b 50 b b b 40

Percentage (%) b 30 b

20 b

10 a a a a a a a a a a a a a a a a 0

Variety

Figure 3.1: Clustered bar for isomers percentages in each varietal wine. Means with the same letter are not significantly different from each other in each varietal wine (Tukey’s HSD, α= 0.05). shows total monoterpene hydrocarbons percentage, shows total rose oxides percentage, shows total linalool and nerol oxides percentage, shows total monoterpene alcohols percentage.

110

Group 2 6

Gewürztraminer

4 Group 1 F2 (20.06 %) (20.06 F2 2 Group 3 Muscat Chardonnay 0 Viognier -4 -2 0 2 4 6 8 10 12 Pinot gris Riesling Torrontes -2 Sauvignon blanc -4

-6 F1 (65.51 %)

Figure 3.2: Discriminant plot of varietal wines on concentration of monoterpene isomers. Varietal wine scores were represented by centroids surrounded by 95% confidence regions (the solid circle). Three groups were separated by the dashed circle

111

2 medium sweet

1 F2 (31.57 %) (31.57 F2 medium dry 0 -3 -2 -1 0 1 2 3 dry sweet -1

-2

1 -3 F1 (60.00 %) 0.75 (2S, 4R)-(-)-cis-rose oxide 0.5 R-(+)-β-citronellol 0.25 (2R, 4S)-(+)-cis-rose oxide S-(+)-linalool

R-(-)-linalool F2 (31.57 %) (31.57 F2 0 S-(-)-limonene (2R, 4R)-(-)-trans-rose oxide R-(+)-limonene (2S, 4S)-(+)-trans-rose oxide (-)-cis-linalool oxide R-(+)-α-terpineol -0.25 R-(+)-nerol oxide S-(-)-α-terpineol S-(-)-nerol oxide (-)-trans-linalool oxide -0.5 (+)-cis-linalool oxide (+)-trans-linalool oxide -0.75

-1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 F1 (60.00 %)

Figure 3.3: Discriminant plot of wine style on concentration of monoterpene isomers. Upper panel, Wines styles scores were represented by centroids surrounded by 95% confidence regions. Bottom panel, all compound vectors were shown.

112

4.5 Chardonnay 20 2 Pinot gris R =0.78 18 2 4.0 Sauvignon blanc Muscat R =0.94 Gewürztraminer 16 Torrontes 3.5 Viognier Riesling 14 3.0 12 2.5

limonene

limonene -

- 2.0

(+)

(+) -

- 8

R R 1.5 2 2 R =0.91 6 R =0.48 1.0 2 4 R =0.40 0.5 2

0.0 0 0 1 2 3 4 5 6 7 8 9 0 5 10 15 20 25 30 35 S-(-)-limonene S-(-)-limonene

50 195 45 180 Viognier 2 165 Muscat 2 40 R =0.89 Gewurztraminer R =0.73 150 Torrontes 35 Pinot gris 2 Chardonnay 135 Riesling R =0.97 2

30 Sauvignon blanc 120 R =0.88

linalool oxide

- -

25 105 trans

trans 90 -

2 -

)

) -

20 - (

R =0.90 ( -

2 - 75

)

) S R =0.93 S

,5 15

,5 60

S (2 (2 45 10 2 R =0.53 30 5 2 15 R =0.92 0 0 0 10 20 30 40 50 60 70 80 0 50 100 150 200 250 300 350 400 450 (2R,5R)-(+)-trans-linalool oxide (2R,5R)-(+)-trans-linalool oxide

Sauvignon blanc Viognier 250 40 Gewürztraminer 2 R =0.60 Riesling Chardonnay 2 Torrontes Pinot gris R =0.88 200 Muscat 2 30 R =0.97 2

R =0.78 linalool oxide

linalool oxide 2 - - 150

R =0.91 2

cis

cis -

- 20 R =0.82

(+)

(+) -

- 2 )

) 100 R

R R =0.89 2 ,5

,5 R =0.88

S (2 (2 10 50

0 0 0 20 40 60 80 100 0 100 200 300 400 (2R,5S)-(-)-cis-linalool oxide (2R,5S)-(-)-cis-linalool oxide

30 Gewürztraminer 2 240 R ≈1.00 Sauvignon blanc Torrontes 2 25 Pinot gris R =0.99 200 Riesling Viognier Muscat 20 Chardonnay 160

nerol oxide 120

nerol oxide

- (+)

(+) 2 -

- 10 R R R ≈1.00 80 2 2 R =0.89 2 5 R ≈1.00 R ≈1.00 40 2 0 2 R ≈1.00 R ≈1.00 0 0 5 10 15 20 25 0 20 40 60 80 100 120 140 S-(-)-nerol oxide S-(-)-nerol oxide

Figure 3.4: X-Y scatterplots of enantiomer pair concentrations (µg/L) in all varietal wines with fitted lines and adjusted R2. In the same enantiomer pair, such as S-(-)-limonene vs. R-(+)- limonene, varietal wines were separated into two scatterplots based on the concentration range. The other four enantiomer pairs were shown in Figure S 3.6.

113

4 2 A C 3 Pinot gris 1

Viognier 2 Chardonnay F2 (18.39 %) F2(18.39 F2 (31.01 %) F2(31.01 1 sweet dry Gewürztraminer 0 0 -4 -3 -2 -1 0 1 2 3 4 -2 -1 0 1 2 medium dry -1 medium sweet Muscat Riesling -2 Sauvignon blanc -1 Torrontes -3 1 -2 1 -4 D B F1 (75.45 %) F1 (54.56 %) 0.75 0.75 S-(-)-nerol oxide/total (2R,5S)-(-)-cis-linalool oxide/total cis (+)-trans-linalool oxide/total trans 0.5S-(-)-limonene/total 0.5 S-(-)-α-terpineol/total %) F2(18.39 (2R,4S)-(+)-cis-rose oxide/total cis (2R,4R)-(-)-trans-rose oxide/total trans 0.25 0.25 S-(-)-α-terpineol/total F2 (31.01 %) F2(31.01 R-(-)-linalool/total 0 0 S-(-)-nerol oxide/total R-(-)-linalool/total S-(-)-limonene/total -0.25 (2R,5S)-(-)-cis-linalool oxide/total cis -0.25 -0.5 -0.5 (+)-trans-linalool oxide/total trans (2R,4R)-(-)-trans-rose oxide/total trans -0.75 -0.75 (2R,4S)-(+)-cis-rose oxide/total cis -1 -1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 F1 (75.45 %) F1 (54.56 %)

Figure 3.5: Discriminant plot of grape variety and wine style on monoterpene enantiomer fractions. Panel A, varietal wine scores were represented by centroids surrounded by 95% confidence regions (the solid circle). Panel B, all enantiomer fractions vectors were shown based on varietal wines. Panel C, wine styles scores were represented by centroids surrounded by 95% confidence regions. Panel D, all enantiomer fractions vectors were shown based on wine style.

114

S 3.1. Quantifier and qualifier ions selected for monoterpene isomers

Heart-cut timings in the Compounds Ions chosen1 (m/z) first GC(min) S-(-)-limonene 107,121,136 16.00-19.75 R-(+)-limonene 107,121,136 (2R, 4S)-(+)-cis-rose oxide 139,69,83 (2S, 4R)-(-)-cis-rose oxide 139,69,83 26.00-29.75 (2R, 4R)-(-)-trans-rose oxide 139,69,83 (2S, 4S)-(+)-trans-rose oxide 139,69,83 (2R,5R)-(+)-trans-linalool 94,93,111 oxide (2R,5S)-(-)-cis-linalool oxide 94,93,111 (2S,5S)-(-)-trans-linalool 94,93,111 oxide 32.00-38.00 (2S,5R)-(+)-cis-linalool oxide 94,93,111 S-(-)-nerol oxide 152, 96,83 R-(+)-nerol oxide 152, 96,83 R-(-)-linalool 121,93,136 41.00-44.50 S-(+)-linalool 121,93,136 S-(-)-α-terpineol 59,81,121 53.00-56.25 R-(+)-α-terpineol 59,81,121 R-(+)-β-citronellol 95,109,123 57.00-58.60

1 Numbers in bold are quantifier ions

115

(x10,000) 107.00 121.00 (x10,000) 136.00 94.00 5.0 7.5 93.00 111.00

5.0 2.5

2.5 0.0 32.25 32.50 32.75 33.00 33.25 (x10,000) 139.00 0.0 2.0 69.00 57.75 58.00 58.25 58.50 58.75

(x1,000,000) 83.00 S

1.5 (2

TIC -

(

- (2 1.0 R

4.0 )

, 5 , R

limonene 0.5

, 5 , S 0.0 5 , A )

54.50 54.75 55.00 55.25 55.50 R

3.5 -

(

)

(+)

cis

(

, 5 ,

(+)

- -

3.0 2

trans -

linalool oxide linalool

cis

, 4 ,

- )

(+)

limonene

S -

(

linalool oxide linalool

- )

2.5 -

(

)

linalool oxide linalool

)

limonene

(+)

)

, 4 ,

trans

, 4 , (

limonene

)

R trans

2.0 )

trans

)

(+)

linalool oxide linalool

(

)

cis -

1.5 oxide rose

cis

rose oxide rose

- rose

1.0 rose

oxide oxide 0.5

0.0 30.0 32.5 35.0 37.5 40.0 42.5 45.0 47.5 50.0 52.5 55.0 57.5 60.0 62.5 65.0

(x1,000,000) R

(+)

( -

TIC )

d3 nerol

6.0 nerol

(+)

(+) oxide oxide B

5.0 S

(

terpineol

)

α d3

4.0 -

terpineol

(

) -

3.0 α

terpineol

(+)

(

(+)

- (

2.0 linalool

)

citronellol

)

linalool

linalool linalool 1.0

0.0 67.5 70.0 72.5 75.0 77.5 80.0 82.5 85.0

116

S 3.3. Limit of detection (LOD)/2 for monoterpene isomers (µg/L) and the number of wines with non-detectable isomer

Chardonnay Gewürztraminer Muscat Pinot gris Riesling Sauvignon Torrontes Viognier LOD/2 (21)* (21)* (17)* (21)* (19)* blanc (19)* (10)* (20)*

S-(-)-limonene 0.02808 21 0 0 21 4 13 0 1

R-(+)-limonene 0.04452 21 0 0 21 12 18 0 1

(2R,4S)-(+)-cis-rose oxide 0.01654 21 6 0 17 10 16 0 16

(2S,4R)-(-)-cis-rose oxide 0.05525 21 4 2 18 15 17 0 20

(2R,4R)-(-)-trans-rose oxide 0.00311 21 4 6 20 16 18 1 20

(2S,4S)-(+)-trans-rose oxide 0.00000 21 13 6 20 15 18 0 20

(2R,5R)-(+)-trans-linalool oxide 0.02211 7 1 0 4 0 1 0 18

(2R,5S)-(-)-cis-linalool oxide 0.01166 6 0 0 2 0 1 0 0

(2S,5S)-(-)-trans-linalool oxide 0.00649 10 0 0 7 0 11 0 0

(2S,5R)-(+)-cis-linalool oxide 0.00169 10 0 0 7 0 2 0 0

S-(-)-nerol oxide 0.00209 20 0 0 12 0 0 0 13

R-(+)-nerol oxide 0.00155 20 0 0 12 0 0 0 13

R-(-)-linalool 0.01450 16 0 0 20 11 16 0 1

117

S-(+)-linalool 0.00231 16 0 0 20 11 16 0 1

S-(-)-α-terpineol 0.00611 1 0 0 0 0 0 0 0

R-(+)-α-terpineol 0.01544 15 0 0 10 0 8 0 0

R-(+)-β-citronellol 0.00008 4 0 0 9 14 11 0 2

* The number in the bracket is the total number of wines for each variety.

118

0.75 R-(+)-β-citronellol S-(+)-linalool 0.5 (2S, 4R)-(-)-cis-rose oxide R-(-)-linalool (2R, 4S)-(+)-cis-rose oxide - S-(-)-limonene R-(+)-limonene

F2 (20.06 %) (20.06 F2 0.25 R-(+)-α-terpineol - S-(-)-α-terpineol (-)-cis-linalool oxide (+)-cis-linalool oxide 0 (+)-trans-linalool oxide R-(+)-nerol oxide (-)-trans-linalool oxide S-(-)-nerol oxide -0.25 (2R, 4R)-(-)-trans-rose oxide

-0.5

-0.75

-1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 F1 (65.51 %)

S 3.4. Monoterpene isomers vector loadings for varietal wines classification by discriminant analysis

119

S 3.5. Structure matrix of variable correlations for wine styles classification by discriminant analysis

F1 F2 F3

S-(-)-limonene 0.723 -0.034 -0.158 R-(+)-limonene 0.670 -0.065 -0.091 (2R,4S)-(+)-cis-rose oxide 0.008 0.018 -0.242 (2S,4R)-(-)-cis-rose oxide 0.232 0.486 -0.317 (2R,4R)-(-)-trans-rose oxide -0.052 -0.040 -0.384 (2S,4S)-(+)-trans-rose oxide -0.049 -0.187 -0.354 (2R,5R)-(+)-trans-linalool oxide 0.267 -0.300 -0.200 (2R,5S)-(-)-cis-linalool oxide 0.412 -0.279 -0.092 (2S,5S)-(-)-trans-linalool oxide 0.445 -0.314 -0.266 (2S,5R)-(+)-cis-linalool oxide 0.256 -0.277 -0.114 S-(-)-nerol oxide -0.014 -0.218 -0.283 R-(+)-nerol oxide -0.018 -0.205 -0.298 R-(-)-linalool 0.615 0.135 -0.087 S-(+)-linalool 0.587 0.189 -0.041 S-(-)-α-terpineol 0.706 -0.108 -0.227 R-(+)-α-terpineol 0.692 -0.083 -0.235 R-(+)-β-citronellol 0.444 0.292 0.041

120

0.6 Chardonnay 3.0 Pinot gris Gewürztraminer 0.5 Sauvignon blanc Muscat Viognier 2.5 2 Torrontes R =0.89 Riesling 2 0.4 R =0.27

2.0

rose oxide

cis

cis -

- 0.3 )

) 2 -

- 1.5 (

( R =0.61

- )

) 2 R R R =0.71

2 , 4 ,

, 4 , 0.2 S

S 1.0 R =0.27 (2 (2 2 R =0.32 0.1 0.5 2 R ≈1.00 0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 (2R, 4S)-(+)-cis-rose oxide (2R, 4S)-(+)-cis-rose oxide

0.25 3.0 Riesling 2 2 R =0.92 R ≈1.00 Gewürztraminer 2.5 0.20 Sauvignon blanc Torrontes Pinot gris Muscat

Viognier 2.0

rose oxide

rose oxide - - 0.15 Chardonnay

2 trans

trans 1.5 - - R =0.51

2 (+)

(+) 2 -

- 0.10 R ≈1.00

) )

R =0.02 S

S 1.0

, 4 ,

(2 (2 0.05 0.5

2 R =0.80 0.00 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 0 1 2 3 4 5 6 7 8 (2R, 4R)-(-)-trans-rose oxide (2R, 4R)-(-)-trans-rose oxide

16 2 600 Riesling R =0.97 550 Chardonnay Gewürztraminer 2 14 500 R =0.99 Sauvignon blanc Muscat 450 12 Pinot gris Viognier 400 Torrontes 10 350

300 linalool

linalool 8

- (+)

(+) 2 -

- 200 S S 6 R =0.99 2 150 R =0.92 4 2 R =0.97 100

2 2 2 50 R =0.85 R ≈1.00 2 R =0.86 0 0 0 2 4 6 8 10 12 14 16 0 50 100 150 200 250 600 R-(-)-linalool R-(-)-linalool

700 90 2 2 R ≈1.00 80 Viognier R =0.96 Riesling 600 70 Pinot gris Gewürztraminer Sauvignon blanc 500 60 Torrontes Chardonnay Muscat 50 400

2 terpineol

terpineol 2 -

- R =0.86 α

α 40 R =0.97 -

- 300

(+)

(+) -

- 30

R R 20 2 200 2 R =0.02 R ≈1.00 10 2 R =0.30 100 0 2 R =0.35 0 0 15 30 45 60 75 90 0 100 200 300 400 500 600 700 800 S-(-)-α-terpineol S-(-)-α-terpineol S 3.6. X-Y scatterplots of enantiomer pair concentrations (µg/L) in all varietal wines with fitted lines and adjusted R2.

121

CHAPTER 4

Chemo-diversity in chiral monoterpenes of Riesling wine from different regions and

wine styles

Mei Songa, Michael Qiana, Claudio Fuentesb, Elizabeth Tomasinoa*

This paper has been prepared for submission to Food Chemistry.

a Department of Food Science & Technology, Oregon State University, Wiegand

Hall, Corvallis, Oregon, USA 97331

b Department of Statistics, Oregon State University, Weniger Hall, Corvallis,

Oregon, USA 97331

*Author to whom correspondence should be addressed;

E- Mail: [email protected]; Tel.: 541-737-4866.

122

ABSTRACT

Monoterpenes are important characteristic compounds for aromatic white wines, including Riesling, but their enantiomers have been little explored in wine. Enantiomers may differ based on region and style as they are sensitive to environmental factors and thus could be used for wine authentication. Thirteen monoterpene isomers were quantitated by HS-SPME-MDGC-MS in fifty-four commercial Riesling wines from three wine styles (dry, medium dry, medium sweet) and four well-established regions including

Germany, France, New York and Oregon. Significant differences were found for nine out of the 13 isomer compositions among different regions and eight isomers among styles.

X-Y scatterplots of enantiomer pair concentrations, with excellent fitted lines, implies low variation of enantiomeric ratios from each region. The study suggests that wines from different regions and styles could be differentiated by chiral monoterpene profiles.

Chiral monoterpene analyses could provide supporting information in Riesling wine authentication by offering an objective measure of flavor quality.

KEYWORDS:

SPME-MDGC-MS, enantiomer fraction, white wine, discriminant analysis,

123

4.1. INTRODUCTION

Riesling is one of the world’s widely planted white grape varieties with a total of more than 50,000 hectares worldwide as of 2015 (Haeger, 2016). The first documentation of Riesling cultivation was around 1350 AD in the Rhine Valley (Liu et al., 2008;

Sechrist, 2012). The wines produced from old world regions, Mosel and Rhine rivers of

Germany and the Alsace region of France, are considered to be the world’s top Rieslings

(Jacobson, 2006). Riesling is also grown in new world regions including New Zealand,

Australia, New York and Oregon in the United States, and other locations since 1955

(Sechrist, 2012).

Riesling is the result of a cross of Heunisch (the dominant cultivar) and Vitis sylvestris (wild cultivar) (Anhalt et al., 2011). The resulting wines are very diverse as the composition of grapes can be altered by environmental characteristics and viticultural practices. The sensitivity to environmental factors, for example, the climate and soil in which it is grown, results in distinctly different flavors in wines. It was reported that

Riesling wines from Ontario, Canada showed distinctly different sensory profiles based on two terroirs, ‘bench’ and ‘plains’. Wines from ‘bench’ had greater lemon/lime aroma than from ‘plains’(Douglas et al., 2001). Riesling is also characterized by enological practices, specifically relating to residual sugar, as these wines are found in many styles based on sugar content, e.g. dry, medium dry, medium sweet or sweet wines (Sweet,

2009).

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There has been growing interest in monoterpene compounds due to the important impact of these compounds on the variety distinctiveness (Peña et al., 2005a).

Additionally, understanding grape-derived wine aroma compounds (e.g. monoterpenes) has been a keystone to wine flavor chemistry over many years. For example, monoterpene alcohols can contribute subtle floral and citrus aroma to Riesling wines

(Peña et al., 2005a). It was reported that cis-rose oxide, citronellol, linalool and α- terpineol were important monoterpenes in Riesling wines with more than three years aging (Black et al., 2015). Simpson and Miller (1983) found linalool, hotrienol and α- terpineol were major monoterpenes in young Riesling wines, with concentrations decreasing with age (Simpson & Miller, 1983; C. R. Strauss et al., 1986).

Interest in enantiomer differentiation is due to the fact that enantiomers display different aroma descriptors and sensory detection threshold (Russell & Hills, 1971).

Enantiomeric composition has been used to assess information in foods by geographic origin (S. Ebeler et al., 2001b; Marchelli et al., 1996), and authenticity of fruit beverages

(S. E. Ebeler, 2007; Ruiz del Castillo et al., 2003). Region of origin is an important factor for many wine consumers. In France, wine quality categories on the label are determined by a geographic classification system and are used to ensure wine quality (Fischer et al.,

1999). As the adulteration of wine becomes more and more sophisticated, there is a need for accurate methods of wine characterization that could be used to prevent adulteration, assuring that wines are from the stated geographical origins or countries (Cordella et al.,

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2002; González & Peña-Méndez, 2000; Kallio et al., 1915; Liu et al., 2008; Versari et al.,

2014).

Rapp and Hastrich (1978) have shown that the ratios among the various monoterpenes can be used to distinguish not only one cultivar from another but also by region or origin (Rapp et al., 1978). Such ‘terpene profiles’ are useful for the separation of Riesling wines from other so-called “Riesling wines” (e.g. Welsch Riesling, Kap

Riesling, Emerald Riesling) but are not actually produced from true Riesling grapes due to monoterpene contents in grapes can be affected by varieties, environmental factors and others. Rapp (1998) reported a significant analytical differentiation between Riesling and

Welsch Riesling from different growing regions (Austria, Italy and Yugoslavia) based on terpene profiles. Specifically, significant higher concentrations of selected monoterpene compounds (e. g. linalool, trans-linalool oxide, α-terpineol) were present in true Riesling wines compared with Welsch Riesling (Rapp, 1998). The objective of this study was to determine the effect of regions and styles on chiral monoterpene profiles and enantiomer fractions, to determine if monoterpene enantiomers could be possible to authenticate

Riesling wines.

4.2. MATERIALS AND METHODS

4.2.1. Chemicals

Standards, S-(-)-limonene (≥99.0%), R-(+)-limonene (≥99.0%), furanoid linalool oxide (≥97.0%), and R-(-)-linalool (≥98.0%), were used to check the elution order of the

126 isomers. Linalool (≥97.0%), R-(+)-α-terpineol (≥97.0%), and R-(+)-β-citronellol (98.0%) were obtained from Sigma Chemical Co. (St. Louis, MO, USA). S-(-)- α-Terpineol

(96.0%) from BOC sciences (Ramsey Road, Shirley, NY, USA), and nerol oxide (99.0%) was obtained from ALFA chemistry (Waverly Avenue, Holtsville, NY, USA). Isotopic standards, d3-(±)-α-terpineol and d3-(±)-linalool (≥99.4%) were purchased from CDN

Isotopes (Pointe-Claire, QC, Canada), while d3-(±)-limonene was synthesized as described in (Song et al., 2015). Milli-Q water was obtained from a Millipore Continental water system (EMD-Millipore, Billerica, MA, USA). HPLC grade ethyl alcohol was from Pharmco-AAPER (Vancouver, WA, USA). Sodium chloride was supplied from J.T.

Baker (Avantor Performance Materials, PA, USA).

4.2.2. MDGC-MS/SPME/wine preparation

Wine sample preparation and quantitation method by head space-SPME-MDGC-

MS for: S-(-)-limonene, R-(+)-limonene, (2R, 5R)-(+)-trans-linalool oxide, (2R, 5S)-(-)- cis-linalool oxide, (2S, 5S)-(-)-trans-linalool oxide, (2S, 5R)-(+)-cis-linalool oxide, R-(-)- linalool, S-(+)-linalool, S-(-)-α-terpineol, R-(+)-α-terpineol, and R-(+)-β-citronellol can be found in Song et al. (2015). Quantitation of the isomers was established by the standard curves following the stable isotope dilution analysis method (S. Ebeler et al., 2001b;

Lindenmeier et al., 2004; Siebert et al., 2005). All of the wines were run in three groups based on styles (dry, medium dry and medium sweet) according to the wine label or available information for instrument analysis. Each group was run in triplicate. The

127 standard curves for each style wines were run in the de-aromatized corresponding wine matrices respectively in order to minimize the matrix effects, and were run in each batch to minimize any SPME fiber effects (Song et al., 2015).

4.2.3. Wine

Fifty four commercial Riesling wines (2012 vintage) in three wine styles, dry, medium dry and medium sweet, were randomly selected from four well established regions: old world producers from Germany (Pfalz and the Mosel), France (Alsace), and new world producers from New York (Finger lakes region) and Oregon (Willamette valley AVA) in the United States (Table 4.1). Sample sizes were not well balanced over styles as differences were found between label style and actual style based on residual sugar measurement which was measured by the revised Rebelein method in duplicate

(Rebelein, 1973). Moreover, medium sweet wine could not be obtained from France during the course of this study. France typically produces many dry style Rieslings and researchers had difficulty obtaining medium-sweet French wines in the USA. Wine style was categorized according to ((EC), 2002) with revisions based on the measured residual sugar content. Wine with residual sugar content less than 7 g/L can be considered as

“dry”; between 7 g/L and 12 g/L as “medium dry”; between 12 g/L and 45 g/L as

“medium sweet”. The wines were sampled into three 40 mL amber vials (Supelco,

Bellefonte, PA, USA) and three 50 mL centrifuge tubes (VWR International Corp.

Visalia, CA, USA) and stored at -20 °C until analysis.

128

4.2.4. Statistical analysis

One way ANOVA and Tukey’s honest significant difference (HSD) were performed to compare the mean differences among groups. General linear models (GLM) were used to study the effect of region and wine style on chiral monoterpene profiles or enantiomer fraction of Riesling wines. Statistics were calculated using IBM SPSS statistic 20 (SPSS Inc., Chicago, IL). Discriminant analysis (DA) was calculated using

XLSTAT 2014. 6. 01 software (Addinsoft, New York, USA).

4.3. RESULTS AND DISCUSSION

4.3.1. Separation and identification of chiral monoterpenes in Riesling wines

Thirteen chiral monoterpenes were investigated in 54 bottles of Riesling wines from four regions and three wines styles. As can been seen in Figure 4.1, significant differences were found in mean concentrations of these compounds in all of the wines investigated. (2R, 5R)-(+)-trans-Linalool oxide contained the highest mean concentration,

46.54 µg/L, in agreement with Webster et al. (1993) who reported that linalool oxides were the dominant monoterpenes in Riesling wine (Webster et al., 1993). R-(+)-β-

Citronellol had the lowest concentration of 0.47 µg/L. This was of interest as Dziadas and

Jeleń (2010) reported that α-terpineol was one of the dominant monoterpenes in 2006,

2007 Riesling wines from France, Germany and Hungary. The difference found in our study may be due to vintage or region differences. Cis/trans-linalool oxides were not detected in their study (M. Dziadas & Jeleń, 2010). Many of the enantiomer pairs showed

129 similar mean concentrations with exception of (2R, 5R)-(+)-trans-linalool oxide vs. (2S,

5S)-(-)-trans-linalool oxide. The instability of linalool oxide is discussed and can be found in section 4.4.

4.3.2. Quantification of chiral monoterpenes in Riesling wines at regions and styles

Rieslings’ sensitivity to environmental factors produce wines with distinctly different flavors (Sweet, 2009). The effect of region, style and the region x style interaction on chiral monoterpene contents was performed by general linear model.

Significant differences were found on chiral monoterpenes among regions and styles

(Table 4.2). However, no interaction effect of region and style was found. (±)-Limonene and (±)-α-terpineol were not found to be important for region differentiation. Germany wines contained high concentrations of (±)-linalool and R-(+)-β-citronellol isomers which have low aroma threshold values (Garneau et al., 2014a; Z. Gunata et al., 1988). Wines from New York and France had very similar chiral monoterpene profiles composed primarily of the linalool and nerol oxides and R-(+)-β-citronellol. Oregon wines contained great concentrations of all oxide isomers which have high aroma threshold values(Garrido-Frenich et al., 2006). The dominant monoterpene groups in each region may contribute to specific aromas of these wines (Marais, 1983).

Significant differences found between the three styles from all regions were due to all monoterpene enantiomer concentrations except (±)-limonene, (±)-α-terpineol and

(2S, 5R)-(+)-cis-linalool oxide. Medium dry wines contained the greatest concentrations

130 of isomers compared to the other two styles (data not shown). Within France, the concentration of linalool oxide enantiomers were significantly greater in medium dry style compared to dry style. Monoterpene alcohols had low concentration in medium dry style wines from France. For German wines, there were no significant differences for all of the isomer concentrations among the three styles. However, medium dry style wines had the highest concentrations for most of the isomers, except for (2R, 5S)-(-)-cis-linalool oxide, (2S, 5R)-(+)-cis-linalool oxide and R-(+)-β-citronellol. Medium dry wines from

New York showed significant differences from dry and medium sweet wines based on linalool enantiomers. Different styles of wines from Oregon showed significant differences for all oxide isomers and R-(+)-α-terpineol in concentration. Medium sweet wines had the most amounts of oxide isomers and R-(+)-α-terpineol, while dry wines had the high concentration of other isomers.

Riesling grapes and monoterpenes biosynthesis in grapes are known to be very sensitive to environmental factors (Burbott & Loomis, 1967; Sweet, 2009), and genetic factors, such as clones from Riesling grape (Marais & Rapp, 2017; Versini et al., 1990b).

Higher temperature and solar exposure linearly increased monoterpene contents in grapes

(Marais et al., 1999). The differences between monoterpene isomers in the wines resulting from region and style may be due to these factors.

4.3.3. Discriminant plot (DA) on concentration of monoterpene isomers of Riesling wines in regions and styles

131

Research has proposed that if monoterpenes are characteristic compounds to specific grape varieties and are not modified considerably during the fermentation processes they could be markers of region of origin (Rapp et al., 1978; Ruiz del Castillo et al., 2003; Wen et al., 2015). Characteristic chemical profiles combined with multivariate analysis (e.g. discriminant analysis, DA) allowed the successful classification of the wines according to region of origin (Marais et al., 1992). The distribution of chiral monoterpene as affected by region and style can be visualized in a

DA plot. DA was performed on isomer concentrations (mean of the three replications) from all samples. Ninety-four percent of the variation can be obtained in the first two discriminant functions for regions, with F1 and F2 contributing 67% and 27%, respectively (Figure 4.2). France and New York wines were separated from other wines along the F1 axis. New York wines were characterized by (±)-limonene and (±)-α- terpineol compounds. German wines had high negative scores along the F2 axis, characterized by (±)-linalool and R-(+)-β-citronellol isomers, whereas Oregon wines on the opposite side of the F2 axis were characterized by all of the oxides, especially (+)- linalool oxides. This study was in agreement with the work done by Rapp et al. (1985) which characteristic varietal terpene profile in concentrations in Riesling wines could differentiate regions (Rapp et al., 1985a).

Likewise two statistically significant discriminant functions were obtained for styles, with F1 and F2 contributing 72% and 28%, respectively (Figure 4.2). All three styles were significantly separated from each other into three of the four quadrants of the

132

DA. Medium dry wines were on the positive side of F1 separated from the other two styles, and characterized by the majority of the isomers. Dry and medium sweet wines were separated by F2 axis and characterized by lower R-(+)-β-citronellol concentration in medium sweet wines. (±)-α-Terpineol enantiomers were not an important variable to separate wines by style.

4.3.4. Quantification of enantiomer fractions in Riesling wines by region and style

The enantiomeric ratios of key aroma compounds have been used successfully to distinguish between natural and synthetic food products, classify geography area, and plant variety. Therefore, enantiomeric ratios could offer an interesting alternative to conventional flavor analysis methods for product authentication (S. Ebeler et al., 2001b;

Marais & Rapp, 1991b; Ruiz del Castillo et al., 2003). Enantiomer fractions (EF) were calculated by dividing the first eluting enantiomer by the total enantiomers of each compound (enantiomer pairs) (Harner et al., 2000). The effect of region, style and the interaction of region × style on enantiomer fractions were performed by general linear model. Significant differences were found among regions, but not from style and interaction effect (Table 4.3). For example in New York and Oregon wines, (2R, 5S)-(-)- cis-linalool oxide EF and R-(-)-linalool EF were significantly higher in medium dry New

York wines, (2R, 5R)-(+)-trans-linalool oxide EF and S-(-)-α-terpineol EF had the highest values in medium dry Oregon wines. The S-(-)-nerol oxide and R-(-)-linalool concentrations observed from all regions and styles were lower or equal to the

133 corresponding enantiomers (EFs ≤ 0.50). Likewise, (2R, 5S)-(-)-cis-linalool oxide was lower or equal to the enantiomer pair in German wines.

The differences in enantiomer fractions among regions can be seen vividly in the

X-Y scatterplots of six enantiomer pairs (Figure 4.3). The fitted lines with slope and R2 were plotted for all wines from the same region. The slope was used to compare the similarity of enantiomer fractions among different regions (there was no significant differences from styles). As can be seen in Figure 4.3, the slopes for the four regions in

(2R, 5R)-(+)-trans-linalool oxide and (2R, 5S)-(-)-cis-linalool oxide pairs were quite different. The larger slope from France wines compared to German wines implied that

German wines had greater (2R, 5R)-(+)-trans-linalool oxide EF. Results from GLM analysis showed that there were significant differences for S-(-)-limonene EF and S-(-)-α- terpineol EF among regions. All of the regions contained similar S-(-)-nerol oxide and R-

(-)-linalool EFs.

The coefficient of determination, R2, indicates the variation of enantiomeric ratios in each region (higher R2 values indicate less variations). Most of the regions showed high R2 value in enantiomer pairs, with R2 values greater than 0.8 except for (2R, 5R)-

(+)-trans-linalool oxide pair and (2R, 5S)-(-)-cis-linalool oxide pair. Low R2 values were found for (2R, 5R)-(+)-trans-linalool oxide pair for France, New York and Oregon wine and (2R, 5S)-(-)-cis-linalool oxide pair for France, Germany and New York. The low R2 for these were due to one data point in the fitted line was that deviated from the others in each region. This implies that there was only one wine in each region that had

134 significantly different EFs for these two pairs (data now shown). However, (2R, 5R)-(+)- trans-linalool oxide EF for Germany wines did vary. Wines from New York and

Germany showed lower R2 values (lower than 0.68) in these two pairs, but higher R2 values (greater than 0.97) in other pairs.

The low R2 values in linalool oxide EFs may due to racemization or rearrangement at wine pH (S. K. Park & Noble, 1993; C. R. Strauss et al., 1986). The sensitivity of some chiral monoterpenes to acidic conditions and to increases in temperature and storage time may cause the variation of linalool oxide concentrations

(Whittaker, 1972). Linalool can easily be oxidized via an epoxide into four linalool oxides (Ribéreau-Gayon et al., 1975). It was reported that linalool oxide increased in wine held at room temperature compared with at 10 °C (C. R. Strauss et al., 1986).

Similar reports in Riesling wines during aging were observed in other research (Di

Stefano, 1985; Rapp et al., 1985b; C. R. Strauss et al., 1986). The storage time and conditions of wines in this study were unknown prior to purchase of the wines. The sensitivity of some chiral monoterpenes to acidic conditions and to increases in temperature and storage time may cause the variation of linalool oxide concentrations.

However the fact that the majority of EFs had high R2 values suggest that despite this potential variation Riesling wines can be authenticated based on chiral monoterpene EF.

4.3.5 Discriminant plot on monoterpene enantiomer fractions of Riesling wines in regions and styles.

135

Enantiomeric ratios have been reported to differentiate geographic origin in fruits other than grapes, such as from yellow passion fruit (S. Ebeler et al., 2001b; Weber et al.,

1995). In our study, there was less variation among regions and styles based on enantiomer fractions than compared to differentiation based on chiral monoterpene contents (Figure 4.2 & 4.4). Two statistically significant discriminant functions were obtained for region, with F1 and F2 contributing 87% and 11%, respectively. German wines were separated from others along the F1 axis. S-(-)-limonene, S-(-)-α-terpineol,

(2R, 5R)-(+)-trans-linalool oxide and R-(-)-linalool EFs had positive loadings along F1

(Figure 4.4), indicating greater amounts of these enantiomer fractions in German wines.

France, New York and Oregon had similar EFs, characterized by (2R, 5S)-(-)-cis-linalool oxide EF. The opposite position of (2R, 5R)-(+)-trans-linalool oxide EF and (2R, 5S)-(-)- cis-linalool oxide EF on the plot indicated that these two EFs were important variables to classify regions. No significant differences were found in the three styles based on EFs.

4.4. CONCLUSION

The results of this study suggest that it is possible to classify Riesling wines according to their geographical origin and style on the basis of the chiral monoterpene profile and enantiomer fractions. The ANOVA and discriminant analysis showed a clear impact of region and style on the chiral monoterpene profiles in Riesling wines. The majority of the wines studied contained similar EFs based on region and style, except for

German wines. However, many monoterpenes are affected by confounding factors, such

136 as light and temperature, providing additional challenges to researchers, winemakers and viticulturists. Hence, there is a strong recommendation to study further the region and style effects over several seasons and bigger sample size.

ABBREVIATIONS USED

HS, head space; SPME, solid phase micro-extraction; MDGC-MS, multidimensional gas chromatography with mass spectrometry; GLM, general linear model; DA, discriminant analysis; ANOVA, analysis of variance; Tukey's HSD, Tukey’s honest significant difference; EF, enantiomer fraction

ACKNOWLEDGMENT

The authors wish to thank Athena Loos and Hongyan Yu for their help with the wine sampling and residual sugar analysis.

AUTHOR INFORMATION

Corresponding Author

*E-Mail:[email protected]. Tel.: 541-737-4866.

Funding

This project was funded by the Oregon Wine Board #2014-1516 and the Oregon

Wine Research Institute.

The authors declare no competing financial interest.

137

REFERENCES

(EC), C. R. (2002). Commission Regulation (EC) No 753/2002 of 29 April 2002 laying down certain rules for applying Council Regulation (EC) No 1493/1999 as regards the description, designation, presentation and protection of certain wine sector products

Anhalt, U. C., Martínez, S. C., Rühl, E., & Forneck, A. (2011). Dynamic grapevine clones—an AFLP-marker study of the Vitis vinifera cultivar Riesling comprising 86 clones. Tree Genetics & Genomes, 7(4), 739-746.

Black, C., Parker, M., Siebert, T., Capone, D., & Francis, I. (2015). Terpenoids and their role in wine flavour: recent advances. Australian Journal of Grape and Wine Research, 21(S1), 582-600.

Burbott, A. J., & Loomis, W. D. (1967). Effects of light and temperature on the monoterpenes of peppermint. Plant Physiology, 42(1), 20-28.

Cordella, C., Moussa, I., Martel, A.-C., Sbirrazzuoli, N., & Lizzani-Cuvelier, L. (2002). Recent developments in food characterization and adulteration detection: Technique- oriented perspectives. Journal of Agricultural and Food Chemistry, 50(7), 1751-1764.

Di Stefano, R. (1985). Occurrence of favorable organoleptic properties of aged wines. Investigation about the composition of volatile aromatic compounds and about the chemical and physical properties of German Riesling wine. Rivista di Viticoltura e di Enologia, 38, 228-241.

Douglas, D., Cliff, M. A., & Reynolds, A. G. (2001). Canadian terroir: characterization of Riesling wines from the Niagara Peninsula. Food Research International, 34(7), 559-563.

Dziadas, M., & Jeleń, H. H. (2010). Analysis of terpenes in white wines using SPE– SPME–GC/MS approach. Analytica Chimica Acta, 677(1), 43-49.

Ebeler, S., Sun, G. M., Vickers, A. K., & Stremple, P. (2001). Gas chromatographic analysis of chiral aroma compounds in wine using modified cyclodextrin stationary phases and solid phase microextraction. In): ACS Publications.

Ebeler, S. E. (2007). Enantiomeric analysis as a tool for authentication of foods and beverages. In ACS Symposium Series, vol. 952 (pp. 39-49): Oxford University Press.

Fischer, U., Roth, D., & Christmann, M. (1999). The impact of geographic origin, vintage and wine estate on sensory properties of Vitis vinifera cv. Riesling wines. Food quality and preference, 10(4), 281-288.

138

Garneau, F.-X., Collin, G., & Gagnon, H. (2014). Chemical composition and stability of the hydrosols obtained during essential oil production. I. The case of Melissa officinalis L. and Asarum canadense L. American Journal of Essential Oils and Natural Products, 2, 54-62.

Garrido-Frenich, A., Romero-González, R., Martínez-Vidal, J., Plaza-Bolaños, P., Cuadros-Rodríguez, L., & Herrera-Abdo, M. (2006). Characterization of recovery profiles using gas chromatography-triple quadrupole mass spectrometry for the determination of pesticide residues in meat samples. Journal of Chromatography A, 1133(1), 315-321.

González, G., & Peña-Méndez, E. (2000). Multivariate data analysis in classification of must and wine from chemical measurements. European Food Research and Technology, 212(1), 100-107.

Gunata, Z., Bitteur, S., Brillouet, J.-M., Bayonove, C., & Cordonnier, R. (1988). Sequential enzymatic hydrolysis of potentially aromatic glycosides from grape. Carbohydrate Research, 184, 139-149.

Haeger, J. W. (2016). Riesling rediscovered: bold, bright, and dry: Univ of California Press.

Jacobson, J. L. (2006). Berry to bottle. Introduction to Wine Laboratory Practices and Procedures, 83-117.

Kallio, M., Viikari, J., Kallonen, R., Lehtonen, P., Patrikainen, E., & Hyötyläinen, T. (1915). Characterisation of wines by comprehensive two-dimensional gas chromatography and chemometric methods. Alcohol, 358(9), 0252.

Lindenmeier, M., Schieberle, P., & Rychlik, M. (2004). Quantification of ochratoxin A in foods by a stable isotope dilution assay using high-performance liquid chromatography– tandem mass spectrometry. Journal of Chromatography A, 1023(1), 57-66.

Liu, L., Cozzolino, D., Cynkar, W., Dambergs, R., Janik, L., O’neill, B., Colby, C., & Gishen, M. (2008). Preliminary study on the application of visible–near infrared spectroscopy and chemometrics to classify Riesling wines from different countries. Food Chemistry, 106(2), 781-786.

Marais, J. (1983). Terpenes in the aroma of grapes and wines: a review. South African Journal of Enology and Viticulture, 4(2), 49-60.

139

Marais, J., Hunter, J., & Haasbroek, P. (1999). Effect of canopy microclimate, season and region on Sauvignon blanc grape composition and wine quality. South African Journal for Enology and Viticulture, 20, 19-30.

Marais, J., & Rapp, A. (1991). The selection of aroma-rich clones of Vitis vinifera L. cv. Gewürztraminer and Weisser Riesling by means of terpene analyses. South African Journal of Enology and Viticulture, 12(1), 51-56.

Marais, J., & Rapp, A. (2017). The selection of aroma-rich clones of Vitis vinifera L. cv. Gewtirztraminer and Weisser Riesling by means of terpene analyses. South African Journal of Enology and Viticulture, 12(1), 51-56.

Marais, J., Versini, G., Van Wyk, C., & Rapp, A. (1992). Effect of region of free and bound monoterpene and C13-norisoprenoid concentrations in Weisser Riesling wines. South African Journal of Enology and Viticulture, 13(2), 71-77.

Marchelli, R., Dossena, A., & Palla, G. (1996). The potential of enantioselective analysis as a quality control tool. Trends in Food Science & Technology, 7(4), 113-119.

Park, S. K., & Noble, A. C. (1993). Monoterpenes and monoterpene glycosides in wine aromas. In): ACS Publications.

Peña, R. M., Barciela, J., Herrero, C., & García‐Martín, S. (2005). Optimization of solid-phase microextraction methods for GC-MS determination of terpenes in wine. Journal of the Science of Food and Agriculture, 85(7), 1227-1234.

Rapp, A. (1998). Volatile flavour of wine: correlation between instrumental analysis and sensory perception. Die Nahrung, 42(6), 351-363.

Rapp, A., Güntert, M., & Heimann, W. (1985a). Beitrag zur Sortencharakterisierung der Rebsorte Weißer Riesling. Zeitschrift für Lebensmitteluntersuchung und-Forschung A, 181(5), 357-361.

Rapp, A., Güntert, M., & Ullemeyer, H. (1985b). Changes in aroma substances during the storage in bottles of white wines of the Riesling variety. Zeitschrift fuer Lebensmittel- Untersuchung und-Forschung (Germany, FR).

Rapp, A., Hastrich, H., Engel, L., & Knipser, W. (1978). Possibilities of characterizing wine quality and vine varieties by means of capillary chromatography. Flavor of foods and beverages, 391.

140

Ribéreau-Gayon, P., Boidron, J., & Terrier, A. (1975). Aroma of Muscat grape varieties. Journal of Agricultural and Food Chemistry, 23(6), 1042-1047.

Ruiz del Castillo, M. L., Caja, M. M., & Herraiz, M. (2003). Use of the enantiomeric composition for the assessment of the authenticity of fruit beverages. Journal of Agricultural and Food Chemistry, 51(5), 1284-1288.

Russell, G., & Hills, J. (1971). Odor differences between enantiomeric isomers. Science, 172(3987), 1043-1044.

Sechrist, R. (2012). The origin, diffusion, and globalization of Riesling. In The Geography of Wine, (pp. 195-206): Springer.

Simpson, R., & Miller, G. (1983). Aroma composition of aged Riesling wine. Vitis, 22(1), 51-63.

Strauss, C. R., Wilson, B., Gooley, P. R., & Williams, P. J. (1986). Role of monoterpenes in grape and wine flavor. In): ACS Publications.

Sweet, N. (2009). Riesling Selections. In): FPS.

Versari, A., Laurie, V. F., Ricci, A., Laghi, L., & Parpinello, G. P. (2014). Progress in authentication, typification and traceability of grapes and wines by chemometric approaches. Food Research International, 60, 2-18.

Versini, G., Rapp, A., Volkmann, C., & Scienza, A. (1990). Flavour compounds of clones from different grape varieties. In Proceedings of the 5 th International Symposium on Grape Breeding. G. Alleweldt (Ed.), (pp. 513-524).

Weber, B., Maas, B., & Mosandl, A. (1995). Steroisomeric flavor compounds. LXXII: Stereoisomeric distribution of some chiral sulfur-containing trace components of yellow passion fruits. Journal of Agricultural and Food Chemistry, 43(9), 2438-2441.

Webster, D. R., Edwards, C. G., Spayd, S. E., Peterson, J. C., & Seymour, B. J. (1993). Influence of vineyard nitrogen fertilization on the concentrations of monoterpenes, higher

141 alcohols, and esters in aged Riesling wines. American Journal of Enology and Viticulture, 44(3), 275-284.

Wen, Y.-Q., Zhong, G.-Y., Gao, Y., Lan, Y.-B., Duan, C.-Q., & Pan, Q.-H. (2015). Using the combined analysis of transcripts and metabolites to propose key genes for differential terpene accumulation across two regions. BMC Plant Biology, 15(1), 240.

Whittaker, D. (1972). The monoterpenes: Academic Press: London, UK.

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Table 4.1. Distribution of Riesling wines across region of origin, vintage and wine style.

Style of wine (bottles) Variety Regiona Vintage Medium Dry Medium dry sweet

FR 2012 10 6

GR 2012 2 5 5 Riesling NY, USA 2012 4 3 4

OR, USA 2012 3 8 4

a FR: France, GR: Germany, NY: New York, OR: Oregon

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Table 4.2. Effect of region and style on chiral monoterpene contents for Riesling determined by ANOVA and Tukey’s HSD (α= 0.05).

F value FR GR NY OR (significance)# Isomers Medium Medium Medium Medium Medium Medium Medium Dry Dry Dry Dry Region Style dry dry sweet dry sweet dry sweet

S-(-)- 1.42a 1.50a 1.72a 2.58a 0.92a 1.74a 2.77a 1.86a 1.54a 1.39a 1.25a 1.88 3.01 limonene

R-(+)- 0.78a 0.74a 0.81a 1.55a 0.37a 1.11a 1.71a 1.21a 0.90a 0.60a 0.77a 2.28 1.73 limonene (2R,5R)- (+)-trans- 35.26a 62.93b 28.91a 38.89a 28.56a 32.49a 50.26a 35.79a 24.19a 73.10b 76.65b 3.35* 6.21** linalool oxide (2R,5S)-(- )-cis- 16.06a 39.05b 14.06a 11.85a 8.62a 15.62a 29.60a 25.01a 15.55a 31.52b 46.32c 7.38*** 6.58** linalool oxide (2S,5S)-(- )-trans- 6.68a 15.56b 3.62a 5.00a 4.27a 7.28a 9.41a 10.88a 6.83a 12.30b 15.25b 6.60*** 5.05* linalool oxide (2S,5R)- (+)-cis- 10.06a 23.55b 19.37a 9.75a 9.08a 11.52a 12.52a 14.63a 12.60a 23.34b 32.43c 5.538* 2.18 linalool oxide S-(-)- nerol 20.85a 32.41a 11.96a 16.31a 11.33a 19.11a 30.65a 29.39a 12.07a 32.63b 33.92b 4.41** 5.54** oxide R-(+)- nerol 22.58a 36.00a 12.69a 16.84a 12.61a 21.83a 32.49a 30.18a 14.20a 35.45b 36.99b 5.37** 5.73** oxide

144

R-(-)- 5.34a 1.19a 16.75a 30.11a 5.19a 4.31a 19.72b 0.02a 8.40a 5.96a 4.45a 3.59* 4.43* linalool

S-(+)- 4.86a 1.15a 15.32a 27.25a 7.80a 4.21a 17.59b 0.03a 9.50a 5.15a 4.30a 3.92* 3.61* linalool

S-(-)-α- 26.98a 24.69a 34.30a 45.61a 20.91a 36.48a 42.77a 44.57a 27.31a 19.98a 26.97a 2.41 0.26 terpineol

R-(+)-α- 22.64a 21.00a 24.92a 38.75a 14.73a 34.02a 39.99a 38.96a 24.02ab 12.00a 25.13b 2.22 0.13 terpineol

R-(+)-β- 0.39a 0.42a 2.02a 1.46a 0.01a 0.44a 0.78a 0.01a 0.43a 0.23a 0.01a 3.70* 5.01* citronellol

Numbers in a row within each region with the same letter are not are not significantly different from each other.

#, Significant difference level: * p<0.05, ** p<0.01, *** p<0.001

145

Table 4.3. Effect of region and style on enantiomer fraction for Riesling determined by ANOVA and Tukey’s HSD (α= 0.05).

F value FR GR NY OR (significance)# Enantiomer fraction Medium Medium Medium Medium Medium Medium Medium Dry Dry Dry Dry Region Style dry dry sweet dry sweet dry sweet

S-(-)- 0.65a 0.68a 0.68a 0.67a 0.72a 0.61a 0.63a 0.61a 0.63a 0.71a 0.63a 3.77* 1.26 limonene/total (2R, 5R)-(+)- trans-linalool 0.82a 0.80a 0.86a 0.91a 0.86a 0.80a 0.84a 0.79a 0.77a 0.85b 0.83ab 3.78* 2.00 oxide/ total trans (2R, 5S)-(-)-cis- * a a a a a a b a a a a 11.20 linalool oxide/ 0.63 0.62 0.41 0.47 0.50 0.59 0.71 0.62 0.55 0.58 0.59 ** 1.76 total cis S-(-)-nerol 0.47a 0.47a 0.48a 0.48a 0.47a 0.46a 0.49a 0.49a 0.46a 0.48a 0.48a 0.25 1.60 oxide/total

R-(-)- 0.44a 0.44a 0.39a 0.52a 0.46a 0.50a 0.53b 0.37a 0.44a 0.46a 0.41a 1.27 0.75 linalool/total b

S-(-)-α- 0.55a 0.54a 0.59a 0.60a 0.60a 0.52a 0.54a 0.54a 0.53a 0.63b 0.52a 3.29* 2.04 terpineol/total

Numbers in a row within each region with the same letter are not are not significantly different from each other.

#, Significant difference level: * p<0.05, ** p<0.01, *** p<0.001

146

f 50

30 e e de de

20 cd Mean concentration (µg/L) bc abc abc 10

ab ab a 0

Figure 4.1. Mean concentrations of chiral monoterpene isomers in Riesling wines (µg/L). Means with the same letter are not significantly different from each other (Tukey’s HSD, α= 0.05).

146

147

3 3 C A

2 2 medium sweet

F2 (27.28 %) (27.28 F2 OR 1 medium dry

1 %) (28.26 F2 FR 0 0 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 3 NY dry -1 -1 GR

-2 -2

1 -3 1 -3 D S-(-)-nerol oxide B (-)-cis-linalool oxide R-(+)-nerol oxide (+)-trans-linalool oxideF1 (67.39 %) (-)-cis-linaloolF1 oxide(71.74 %)(-)-trans-linalool oxide 0.75 (-)-trans-linalool oxide 0.75 R-(+)-nerol oxide (+)-cis-linalool oxide (+)-cis-linalool oxide S-(-)-nerol oxide (+)-trans-linalool oxide

0.5 0.5 F2 (28.26 %) (28.26 F2 F2 (27.28 %) (27.28 F2 0.25 0.25 S-(-)-α-terpineol S-(+)-linalool R-(-)-linalool 0 0 S-(-)-limonene R-(-)-linalool R-(+)-limonene -0.25 R-(+)-α-terpineol -0.25 S-(-)-limonene R-(+)-limonene R-(+)-β-citronellol R-(+)-α-terpineol -0.5 S-(+)-linalool -0.5 R-(+)-β-citronellol -0.75 S-(-)-α-terpineol -0.75

-1 -1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 F1 (71.74 %) F1 (67.39 %)

Figure 4.2. Discriminant plot on concentration of chiral monoterpene contents of Riesling wines in regions and styles. Panel A, regions scores were represented by centroids surrounded by 95% confidence regions (the solid circle). Panel B, all isomers vectors were shown based on regions. Panel C, wine styles scores were represented by centroids surrounded by 95% confident regions. Panel D, all isomer vectors were shown based on wine style.

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148

GR 2 FR A R =0.98 GR Slope=0.72 B NY FR 4 25 GR OR FR NY 2 OR R =0.73 20 Slope=0.21 OR NY 2 2 NY R =0.63 R =0.97 2 Slope=0.11 15 R =0.29

Slope=0.65 linalool oxide

- limonene

- Slope=0.20 2 OR

(+) 2 trans

- GR

R =0.77 - 10 2

)

R -

( R =0.28

Slope=0.60 - ) Slope=0.10

FR S 2

,5 5

R =0.77 S

Slope=0.61 (2 0 0 0 1 2 3 4 5 6 7 0 20 40 60 80 100 S-(-)-limonene (2R,5R)-(+)-trans-linalool oxide

FR R2=0.98 45 OR FR 2 Slope=1.02 FR C R2=0.84 R =0.70 40 GR Slope=0.63 Slope=0.50 50 FR D OR NY GR 2 35 OR R =0.92 NY Slope=1.02 40 OR NY 30 2 R =0.98 Slope=0.96 25 GR NY linalool oxide 2 30 - 2 20 R =0.57 R =0.68 GR

cis 2 nerol oxide - Slope=0.46 Slope=0.71 - R =0.99

(+) 15 20 Slope=0.96

(+)

) R

R 10 ,5

S 10

(2 5

0 0 0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 (2R,5S)-(-)-cis-linalool oxide S-(-)-nerol oxide

GR GR 80 E 2 2 FR R =0.98 120 FR F R =0.99 70 GR Slope=0.86 GR Slope=1.06 NY NY OR OR 60 100

50 80 NY R2=0.98

40 OR linalool

2 terpineol 60 Slope=0.99 - R =0.98 - FR α 2 NY - (+) 30 Slope=0.96 R =0.85

- 2 S (+) 40 R ≈1.00 - Slope=0.92 20 Slope=0.89 R OR FR 20 2 10 2 R =0.99 R =0.77 Slope=0.95 Slope=0.93 0 0 0 10 20 30 40 50 60 70 80 90 100 0 20 40 60 80 100 120 R-(-)-linalool S-(-)-α-terpineol

Figure 4.3. X-Y scatterplots of enantiomer pair concentrations (µg/L) in the 4 regions with fitted lines.

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149

2.5 2.5 A C 2

1.5 1.5 medium sweet

1 F2 (10.78 %) (10.78 F2 F2 (21.03 %) (21.03 F2 0.5 FR 0.5 OR 0 -2.5 -1.5 -0.5 0.5 1.5 GR 2.5 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 -0.5 -0.5 medium dry NY dry -1

-1.5 -1.5 -2

1 -2.5 1 -2.5 B D F1 (87.23 %)S-(-)-limonene/total F1 (78.97S-(- %))-nerol oxide/total 0.75 0.75

0.5 0.5 (2R,5S)-(-)-cis-

F2 (10.78 %) (10.78 F2 S-(-)-α-terpineol/total 0.25 linalool oxide/total cis (21.03 F2 %) 0.25 (+)-trans-linalool oxide/total trans 0 0 S-(-)-limonene/total -0.25 -0.25 R-(-)-linalool/total (+)-trans-linalool R-(-)-linalool/total (2R,5S)-(-)-cis-linalool oxide/total trans -0.5 -0.5 S-(-)-nerol oxide/total oxide/total cis S-(-)-α-terpineol/total -0.75 -0.75

-1 -1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 F1 (78.97 %) F1 (87.23 %)

Figure 4.4. Discriminant plot on monoterpene enantiomer fractions of Riesling wines in regions and styles. Panel A, regions scores were represented by centroids surrounded by 95% confidence regions (the solid circle). Panel B, all enantiomer fractions vectors were shown based on varietal wines. Panel C, wine styles scores were represented by centroids surrounded by 95% confident regions. Panel D, all enantiomer fractions vectors were shown based on wine style.

149

150 CHAPTER 5

Odor perception interactions between free monoterpene isomers and wine

composition of Pinot gris wines

Mei Song1, Claudio Fuentes2, James Osborne1, and Elizabeth Tomasino1,*

This paper has been submitted to Analytica Chimica Acta

1 Oregon State University, Food Science & Technology, Corvallis, Oregon, USA,

97331

2 Oregon State University, Department of Statistics, Corvallis, Oregon, USA

97331

* Corresponding author. Department of Food Science & Technology, Oregon

State University, Wiegand Hall, room 220A, Corvallis, Oregon, USA 97331; E-

mail address: [email protected]. Tel.: 541-737-4866.

150

151 ABSTRACT

Monoterpenes are aromatic compounds that contribute to the characteristic aromas of white wines. These compounds are of great interest to wine as they are related to the unique sensory identity of varietal wine. However, there is little information available about monoterpene isomer profiles and their impact on wine odor perception at sub- or peri-threshold concentrations, concentrations at which many of these compounds are found. The aim of this study was to investigate odor perception of monoterpene isomers in Pinot gris wine and determine any possible compositional matrix effects.

Monoterpene isomers were identified and quantitated in 46 Pinot gris wines from different regions using HS-SPME-MDGC-MS. Ten profiles containing different combinations of monoterpene isomers were classified based on concentrations from the

46 Pinot gris wines. Monoterpenes in these profiles where added to three different matrices; a model wine solution, de-aromatized Pinot gris and original Pinot gris wine.

Triangle tests were performed by 42 panelists to examine the effect of the 10 profiles to odor perception in matrix. Results show that the non-volatile compositions in Pinot gris wine strongly increased the volatility of monoterpene isomers, while other aroma compounds suppressed odor perception, especially with the more complex monoterpene profiles. These results support the fact that the aroma compounds at sub-threshold concentrations, such as the chosen monoterpene isomers, may impact odor perception due to interactions with other compositional elements by enhancement or suppression.

The knowledge of these interactions will further help in the development of wine styles and our understanding of wine quality.

151

152 KEYWORDS:

HS-SPME-MDGC-MS; Odor enhancement; Odor suppression; Enantiomers;

Triangle test

152

153 5.1. INTRODUCTION

The acceptability of wines by consumers mainly depends on the wines flavour, organoleptic properties, and aroma (Gierczynski et al., 2011). Monoterpene isomers are important varietal aroma compounds for white wines and are responsible for floral and citrus aromas. Therefore, it is of importance to identify and quantitate monoterpene isomers in white wines as they are linked to sensory qualities. Previous studies have shown that the monoterpene isomers important specifically to Pinot gris wines were: R-

(+)-limonene, with an aroma describes as fresh, citrus and orange-like; S-(-)-limonene with harsh, turpentine-like, lemon aroma (L. Friedman & J. G. Miller, 1971); linalool oxide with earthy, leafy sensory aroma (Wang et al., 1994); linalool described as woody, lavender, sweet (Brenna et al., 2003; Mikulíková et al., 2009); and α-terpineol with a terpene, heavy floral lilac-like aroma (Boelens et al., 1993).

The majority of the measured monoterpene isomer concentrations found in Pinot gris were below their known perception thresholds, with an odor activity value (OAV) less than 1 (Song et al., 2015). These compounds, known as low impact odorants, are generally considered unimportant for odor perception. However, the significance of low impact compounds have been established in global odour perception research (Ryan et al., 2008). In addition, many of the aroma compounds in wines, even those considered as high impact odorants (with OAV>1), have been found to have no individual direct effect on wine aroma (Ryan et al., 2008). This implies that perceived wine aroma is not impacted by only the addition of individual compounds but also significantly impacted by the matrix or mixture of components (Escudero et al., 2004).

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154 Wine is a highly complex alcoholic beverage composed of both volatile and non- volatile components, such as water, ethanol, organic acids, phenolic compounds, polysaccharides, residual sugars, nitrogenous compounds and numerous aroma compounds (Diako et al., 2016; Muñoz-González et al., 2013; Villamor & Ross, 2013).

Aroma characteristics of wine cannot be understood only from the knowledge of aroma composition alone (Sáenz-Navajas et al., 2010). Aroma-aroma and aroma-non-volatile interactions play an important role in determining the cause of different wine qualities

(Sereni et al., 2016; Waterhouse & Ebeler, 1998).

In recent years, the influence of ethanol (Diako et al., 2016; Jones et al., 2008; A.

L. Robinson et al., 2009; Ryan et al., 2008; Villamor & Ross, 2013; Voilley & Lubbers,

1998; A. Williams & Rosser, 1981), and the non-volatile compositions, such as polysaccharides (Dufour & Bayonove, 1999; Jones et al., 2008; A. L. Robinson et al.,

2009), polyphenols (Diako et al., 2016; Dufour & Bayonove, 1999; Goldner et al., 2011), glycerol (Lubbers et al., 2001), and proteins (Diako et al., 2016; Dufour & Bayonove,

1999; Jones et al., 2008; A. L. Robinson et al., 2009) on specific aroma compounds has been clearly investigated and are known to influence wine aroma release. This type of interaction depends on the physicochemical properties of the aroma compounds (e.g., molecular weight, functional group, and polarity) and chemical binding via covalent, hydrophobic, or hydrogen bonds with other components in the wine matrix (Charles-

Bernard et al., 2002; Gierczynski et al., 2011; Noble, 1996). The extent of interactions can break the aroma compound equilibrium between headspace and liquid phase in wine by altering the partitioning coefficient of aroma compounds and form a new equilibrium

154

155 and consequently, change the perception of wine aroma (Sáenz-Navajas et al., 2010).

However, few studies have determined the effect of interactions among monoterpenes and non-volatile components on the sensory perception of wines.

Interactions between aroma-aroma compounds have been reported in several studies (Diako et al., 2016; Kopjar et al., 2010; Ryan et al., 2008; Takoi et al., 2010;

Villamor & Ross, 2013). The perception of high impact odorants could be modified by sub- and peri-threshold odorants (Ryan et al., 2008). The impact of β-damascenone to

Pinot noir aroma was found to vary depending on the aromatic content of the wine

(Bolman & Tomasino, 2015). Esters responsible for red and black berry fruit aromas in red wines could influence aroma based on ester groupings and not by individual compounds (Pineau et al., 2009). The threshold of linalool is known to decrease when in combination with other terpenes (Ribéreau-Gayon et al., 1975). It is these interactions which may be what drives many of the aroma differences in wine rather than individual aroma compounds.

Perceptual interactions between multiple components in combination remain difficult to predict in complex matrices (Lytra et al., 2012). The use of gas chromatography-olfactometry (GC-O) techniques for estimating the relative importance of isolated aroma compounds overlooks the joint effects between odor active volatiles and the wine matrix (Lorrain et al., 2006; Ryan et al., 2008). Reconstitution, addition and omission methods for estimating the interactions in most studies have seldom gone beyond that of model solutions, often examining compounds in binary and tertiary model systems with a reduced number of components (Atanasova et al., 2005; Harrison & Hills,

155

156 1997; Jones et al., 2008; Voilley & Lubbers, 1998; Yoder et al., 2012). To date, little research has focused on the impact of sensory interactions of monoterpene isomers with complete wine compositions, in the concentration range normally found in wines.

In order to fully evaluate the importance of monoterpene isomers, diverse profiles of monoterpene isomers were added at concentrations normally found in Pinot gris wines, to three different matrices: a model solution (ethanol aqueous), a de-aromatized Pinot gris wine, and an original Pinot gris wine. The objective of this study was to determine the effect of monoterpene isomers at sub-threshold or peri-threshold levels on odor perception. An additional objective was to observe the impact of the matrix and determine any possible interactions.

5.2. MATERIALS AND METHODS

5.2.1. Wine samples

Forty six commercial Pinot gris wines were randomly selected from 6 well established regions including Australia, Italy, New Zealand, New York, Oregon and

Washington from different vintages (Table 5.1). The wines were sampled into three 40 mL amber vials (Supelco, Bellefonte, PA, USA) and three 50 mL centrifuge tubes (VWR

International Corp. Visalia, CA, USA) and stored at -20 °C until analysis.

5.2.2. Chemicals

Standards. The following chemical standards were obtained from Sigma Chemical

Co. (St. Louis, MO, USA): S-(-)-limonene (≥99.0%), R-(+)-limonene (≥99.0%), (-)-rose

156

157 oxide (≥99.0%), furanoid linalool oxide (≥97.0%), R-(-)-linalool (≥98.0%), linalool

(≥97.0%), R-(+)-α-terpineol (≥97.0%), and R-(+)-β-citronellol (98.0%). S-(-)- α-

Terpineol (96.0%) was purchased from BOC sciences (Ramsey Road, Shirley, NY,

USA). D3-(±)-α-terpineol and d3-(±)-linalool (≥99.4%) were purchased from CDN

Isotopes (Pointe-Claire, QC, Canada). D3-(±)-limonene was synthesized as described in

(Song et al., 2015).

Solvents. Milli-Q water was obtained from a Millipore Continental water system

(EMD-Millipore, Billerica, MA, USA). HPLC grade ethyl alcohol was obtained from

Pharmco-AAPER (Vancouver, WA, USA).

Reagents. Tartaric acid was supplied by Davison Winery Supplies (McMinnville,

OR, USA). Sodium chloride was obtained from J.T. Baker (Avantor Performance

Materials, PA, USA).

5.2.3. Monoterpene compositions of Pinot gris wines

All monoterpene isomers: S-(-)-limonene, R-(+)-limonene, (2R, 4S)-(+)-cis-rose oxide, (2S, 4R)-(-)-cis-rose oxide, (2R, 4R)-(-)-trans-rose oxide, (2S, 4S)-(+)-trans-rose oxide, (2R, 5R)-(+)-trans-linalool oxide, (2R, 5S)-(-)-cis-linalool oxide, (2S, 5S)-(-)- trans-linalool oxide, (2S, 5R)-(+)-cis-linalool oxide, R-(-)-linalool, S-(+)-linalool, S-(-)-α- terpineol, R-(+)-α-terpineol, and R-(+)-β-citronellol were identified and quantitated in

Pinot gris wines by head space-solid phase micro-extraction-multi-dimensional GC-MS

(HS-SPME-MDGC-MS). The detailed qualification and quantitation method can be found in Song et al. (Song et al., 2015).

157

158 5.2.4. Wine matrix preparation

Three matrices used in sensory analysis were prepared accordingly:

Model solution (matrix 1): 14.0% ethanol solution (v/v) at pH 3.2 adjusted by tartaric acid was prepared. The solution was bottled in 375 mL green bottles

(TricorBraun, OR, USA) with screw caps (Amcor, Melbourne, Australia) and stored at 4

°C for later use.

De-aromatized wine (matrix 2): Original Pinot gris wine (400 mL) was de- aromatized using a rotary evaporator (Buchi heating bath B-490, Newcastle, DE, USA) for 1 hr with a 32 °C water bath and 135 rpm rotation. Ethanol and distilled water were added to adjust to its original alcohol content (14.0%) and volume (400 mL), ensuring the non-aromatic content was unchanged. The de-aromatized wine was bottled in 375 mL volume as described for matrix 1 and stored at 4 °C for later use. The de-aromatized wine was detected free of monoterpene isomers investigated using the previously mentioned

HS-SPME-MDGC-MS method.

Original wine (matrix 3): Pinot gris grapes was harvested and fermented to dry by standard winemaking procedure. A fining agent, bentonite at 0.12 g L-1, was used at the end of fermentation to reduce the aroma composition. Bentonite was removed by filtering through a 1 μm nylon cartridge filtration (G.W Kent, MI, USA) prior to bottling. This neutral wine was bottled in 375 mL volume and stored at 4 °C for later use. The wine pH was 3.2 as analyzed by a pH meter (Mettler-Toledo GmbH, Schwerzenbach,

Switzerland), and alcohol content was 14.0% (v/v) as determined by an alcohol meter

(Anton Paar DMA 4500 M-EC). The original wine was determined to be free of

158

159 monoterpene isomers investigated by MDGC-MS. Preliminary sensory tests determined it still had an aroma characteristic of Pinot gris wines (data not shown).

5.2.5. Sensory analysis

5.2.5.1. Participants

Approval for this work was granted by Institutional Review Board at Oregon

State University. A total of forty two participants (14 men and 28 women, all above 21 years old) were recruited for this study. Among them, 40 were non-smokers, 31 were from the OSU campus, and only 9 participants had previous formal training on sensory evaluation of foods or wine. All of the subjects were screened to be free of allergies to wine or wine components, and were regular white wine consumers (on average consumed

1 glass or more of white wine a week). Participants were told that the study investigated white wine aroma.

5.2.5.2. Stimuli

Stock standards for each compound was made in pure ethanol as follows: 2.126 g

L-1 for S-(-)-limonene, 1.905 g L-1 for R-(+)-limonene, 1.318 g L-1 for (-)-rose oxide,

2.103 g L-1 for linalool oxide, 1.181 g L-1 for R-(-)-linalool, 1.206 g L-1 for linalool, 1.989 g L-1 for S-(-)-α-terpineol, 2.204 g L-1 for R-(+)-α-terpineol, and 2.031 g L-1 for R-(+)-β- citronellol.

159

160 Ten working standards (WS) were prepared fresh in milli-Q water according to the mean monoterpene concentration analysed by MDGC-MS (Table S 5.1). All standards were stored frozen at -20 °C.

5.2.5.3. Triangle test procedure

Thirty series of triangle tests in three matrices (10 profiles×3 matrices) were performed by each panelist over six weeks. Panelists participated in one session a week where they evaluated five triangle tests. Samples were presented in ascending order of concentrations from profile 1 to profile 10 to avoid any sensory adaption. The matrices were also presented in ascending order of compound compositions from least complex, matrix 1, to most complex, matrix 3. Therefore panelists evaluated profiles 1-5 in matrix

1 for week 1 and profiles 6-10 in matrix 1 for week 2. Weeks 3 and 4 followed this pattern except profiles were evaluated in matrix 2. Similarly for weeks 5 and 6, profiles were evaluated in matrix 3.

Three hundred micro-liter of each working standard was added into 375 mL bottle of matrix solution one hour prior to each sensory test. The final concentrations for each profile can be found in Table 5.2. The control did not contain any added monoterpenes. Participants were presented with 5 series of triangle tests. Each test contained either two controls and one spiked sample or one control and two spiked samples. The order of the three samples was randomized. For all tests, 20 mL of sample

(21 ± 2°C) were served in INAO standard clear wineglasses (Elizabeth, 2011) labelled with 3-digit random codes and covered with plastic petri dishes. Panelists were instructed

160

161 to gently swirl the wine glass and sniff the three samples from left to right and indicate the sample which was different from the other two. A one minute break between each test was required to avoid any carryover effects and fatigue.

5.2.6. Statistical Analysis

D-prime values (d’) derived from Thurstonian modelling (Ennis, 1993) which indicate absolute levels of sensory differentiation, were used to compare the means between distributions of the treatment and the control. Larger d’ values represent bigger differences between the two means, and therefore a sharper sensitivity of the panelists to tell the differences. For each d’ value, we used a z-test to determine whether the true difference between the means is not equal to zero (Bi, 2007; BI et al., 1997), or equivalently to determine the sensitivity of panelists to differentiate between the control and spiked sample in each profile and matrix (Results are considered significant if p<0.05) (BI et al., 1997).

All statistical analyses were performed using IBM SPSS statistic 20 (SPSS Inc.,

Chicago, IL). One way ANOVA was used to compare differences among mean concentration of monoterpene isomers. Multiple comparisons among monoterpene isomers were adjusted using Tukey’s HSD.

5.3. RESULTS AND DISCUSSION

5.3.1. Mean concentrations of monoterpene isomers in Pinot gris wines

161

162 The knowledge of the chemical profile in wine has greatly increased during the past decade. The monoterpene profile with different isomers is critical in oenology as this is related to the unique sensory identity of varietal wines (Marais & Rapp, 1991a; Rapp,

1990). Monoterpene isomers including S-(-)-limonene, R-(+)-limonene, (2S, 4R)-(-)-cis- rose oxide, (2R, 4R)-(-)-trans-rose oxide, furanoid (2R, 5R)-(+)-trans-linalool oxide, (2R,

5S)-(-)-cis-linalool oxide, (2S, 5S)-(-)-trans-linalool oxide, (2S, 5R)-(+)-cis-linalool oxide, R-(-)-linalool, S-(+)-linalool, S-(-)-α-terpineol, R-(+)-α-terpineol, and R-(+)-β- citronellol were identified and quantitated by HS-SPME-MDGC-MS using stable isotopic dilution method (Song et al., 2015). Even though the 46 wines in this study were from the same varietal, Pinot gris, variability was observed among their isomer profiles

(Figure 5.1). This variability is most likely due to the region of origin and wine style

(Rapp, 1990).

(2R, 5S)-(-)-Cis-linalool oxide (9.7 µg L-1) and R-(+)-α-terpineol (8.4 µg L-1) showed the highest concentrations of the monoterpene isomers. (2R, 5R)-(+)-trans-

Linalool oxide (6.6 µg L-1), S-(-)-α-terpineol (6.2 µg L-1), R-(+)-β-citronellol (5.1µg L-1) and (2S, 5R)-(+)-cis-linalool oxide (4.7 µg L-1) had intermediate concentrations and isomers of (2S, 4R)-(-)-cis-rose oxide (0.1 µg L-1), R-(+)-limonene (0.3 µg L-1), S-(-)- limonene (0.4 µg L-1), and (2S, 5S)-(-)-trans-linalool oxide (0.6 µg L-1) had the lowest concentrations of the measured monoterpene isomers. According to Mikulíková et al.

(2009), the greatest concentrations among monoterpenes investigated in Pinot gris were terpineol and linalool (Mikulíková et al., 2009). This is in agreement with our research except linalool oxide was not reported in the Mikulíková et al. study. Additionally, (2R,

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163 4R)-(-)-trans-rose oxide was not detected in the wines, only (2S, 4R)-(-)-cis-rose oxide was found. Luan et al. (2006) also found that (2S, 4R)-(-)-cis-rose oxide was the main enantiomer in V. vinifera L. cv. Morio-Muskat must (F. Luan, Mosandl, A., Gubesch, M. and Wüst, M., 2006).

5.3.2. Monoterpene isomer profiles classification

The monoterpene profiles varied among wine samples mentioned above. In order to investigate the impact of monoterpene isomers, all wine samples were sorted based on the isomer profiles from the least amount of constituents to the greatest, resulting in 10 different profiles (Table 5.2). Nine compounds were used in these 10 profiles. At the time of the sensory study we did not have individual isomers for (-)-rose oxide, linalool oxide and S-(+)-linalool available. Therefore, racemic mixtures were used for these compounds.

For example, concentration of linalool oxide was calculated by adding up the four enantiomers: (2R, 5R)-(+)-trans-linalool oxide, (2R, 5S)-(-)-cis-linalool oxide, (2S, 5S)-(-

)-trans-linalool oxide and (2S, 5R)-(+)-cis-linalool oxide.

Profile 1 contained the least concentration and constituents of isomers with only 3 isomers, both (±)-α-terpineol isomers and (+)-β-citronellol. This was considered the most basic monoterpene profile for Pinot gris wines. The isomer profiles and concentrations were increased from profile 2 to profile 10. Profile 10 had the highest concentrations and the most constituents. In general, most of the isomer concentrations in the profiles were at lower concentrations than their reported odor thresholds, except for (2S, 4R)-(-)-cis-rose oxide (0.5 µg/L in an aqueous–ethanol solution) (Yamamoto et al., 2002), R-(-)-linalool

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164 (0.8 µg/L in methanol solution) (Garneau et al., 2014a; Padrayuttawat et al., 1997b) and

S-(+)-linalool (7.4 µg/L in methanol solution) (Garneau et al., 2014a; Padrayuttawat et al., 1997b). Therefore, profiles 4, 7, 8, 9 and 10 contained at least 1 compound that was above its known perception threshold.

5.3.3. Sensory results

Traditionally, it was thought that such low levels of isomers (considered low impact compounds), would not contribute to the Pinot gris wine aroma (Jelen, 2011).

Recently, researchers have proposed that compounds with relatively low OAVs may act as significant impact odorants in mixtures (Escudero et al., 2004; Ryan et al., 2008).

These low OAV compounds interact with other wine components to alter odor perception. Therefore, despite the potential low amounts of monoterpenes in Pinot gris wines, it was of interest to determine the impact of these compounds to odor perception by looking at both non-aromatic and aroma interactions as little is known about interactions between monoterpenes and other wine components (Voilley & Lubbers,

1998).

Several methods have been reported to investigate the significance of aroma compounds in wine using OAV (Li et al., 2008; Villamor & Ross, 2013), Gas chromatography-Olfactometry (GC-O) techniques (Martí et al., 2003; Villamor & Ross,

2013), reconstructions analysis, and addition and omission tests (Mayr et al., 2014;

Tomasino et al., 2015). However most of these methods have limitations. For example,

OAVs are calculated from detection thresholds, which are typically determined in

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165 different matrices, e.g., aqueous ethanol solution, water or air (Plotto et al., 2004; Rychlik et al., 1998). Little information is known about detection thresholds in a wine matrix.

GC-O techniques attempt to estimate impact in a food matrix. However monoterpenes may not be captured by sniffing due to the low concentration. Moreover GC-O techniques overlook the joint effect between odor active volatiles and the matrix (Lorrain et al., 2006; Ryan et al., 2008). Most of the reconstruction, addition/omission tests were performed in simple solutions, such as binary or ternary mixtures (Adhikari et al., 2006;

Atanasova et al., 2005; Tandon et al., 2000; Yoder et al., 2012). Such results reported from these methods may not sufficiently indicate monoterpenes impact on wine aroma.

Perceptual interactions of sub- and peri-threshold components must be considered in order to ascertain the total odor intensity of the particular matrix (Ryan et al., 2008).

In our study, addition tests and matrix effects were considered. Three matrices, model solution (ethanol aqueous), de-aromatized Pinot gris wine, and original Pinot gris wine were selected. The model solution, as the simplest matrix, contained ethanol and water (pH was adjusted to 3.2). De-aromatized Pinot gris wine contained not only the same amount of ethanol & water as the model solution, but also contained the non- volatiles portion from Pinot gris wine. The original Pinot gris wine contained not only the same amount of ethanol, water and non-volatiles as the previous 2 matrices, but also other aroma compounds present in Pinot gris wine. Concentrations and combinations of monoterpenes added to these three matrices mimicked those found in wines. Table 5.3 shows d’ values associated with the proportion of panelists correctly determining the 10 monoterpene profiles in 3 matrices compared to control samples.

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166 Significant differences were found in all 3 matrices (Table 5.3). In matrix 1, significant differences were found when comparing the control to profiles 3, 4, 5, 7 and

10. Interestingly (-)-rose oxide was present in 4 of these 5 profiles. Therefore it is possible that the presence of (-)-rose oxide is responsible for odor perception in these samples. Triangle tests only show differences and not the odor quality and it is unknown if the odor difference is due to the odor of (-)-rose oxide or if this compound interacts with other monoterpene isomers in these profiles and enhances odor perception.

Synergism among monoterpenes has been studied previously. For example, the perception thresholds of terpenes, such as β-citronellol, linalool oxide and geraniol were lower in the presence of other terpene compounds than in isolation (Villamor & Ross,

2013). Another study has shown an additive effect among geraniol, β-citronellol and linalool in beer (Takoi et al., 2010).

A significant difference was also noticed when comparing the control to profile 4, which did not contain (-)-rose oxide. The difference in odor perception for profile 4 may be due to linalool. The amount of linalool added was above the reported perception threshold of this compound. Profiles 6, 8 and 9, were not perceived as different from the control. This was unexpected as profiles 8 and 9 had linalool isomers at concentrations above its perception threshold. Perhaps another monoterpene, such as limonene, is suppressing odor in these samples, as limonene was common amongst these profiles.

In matrix 2, significant differences were found in all profiles excluded profile 1, the most basic profile. All of these profiles that were perceived as different from the control contained linalool oxide. The concentrations of linalool oxides found in Pinot gris

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167 are not likely to have a direct effect on aroma (Song et al., 2015). However linalool oxide may interact with non-volatiles, resulting in a change in odor perception found in matrix

In matrix 3, significant differences were found between the control and profiles 1,

2, 3, 7 and 9. Interestingly, panelists could not tell the difference from the control compared to profile 10, which contained the highest concentration and most diverse compositions of monoterpenes. This is likely due to the suppression from some compounds that were different in other profiles. The physico-chemical interactions between monoterpenes and other aroma compounds or between monoterpenes and non- volatile matrix could affect odorant volatility or solubility in wine matrix. This effect can alter headspace partition coefficient of odorants, thus exert a powerful effect on odor perception (Mitropoulou et al., 2011; Polášková et al., 2008).

Odor perception can be better understood by considering the effects of food matrix. Research has found that odor thresholds were the lowest in deionized water for all characteristic aroma compounds investigated in tomato than in the ethanol : methanol : water mixture and deodorized tomato homogenate. Additionally, odor perception was suppressed in deodorized homogenate (Tandon et al., 2000). These results highlight the significant perceptual impact of matrix in determining the overall profile of odorants in the headspace (Ryan et al., 2008). In our study, the same amount of monoterpene isomers were added across 3 matrices for each profile. For profile 1: a significant difference was only found in matrix 3, which implies an odor enhancement between monoterpene isomers and other aroma compounds. For profiles 2, 3 and 9: significant differences were

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168 found in matrix 2 and 3, with similar d’ values. There odor enhancement is most likely due to an interaction between monoterpene isomers and non-volatile components. For profiles 4, 5, 6, 8 and 10: d’ value were greatest in matrix 2 and decreased in matrix 3, indicating odor enhancement occurring between monoterpene isomers and non-volatile components, and then some suppression or masking due to the aroma compounds in the matrix. The study showed that wine matrix effects on odor perception depended on the monoterpene composition and concentration in the profiles. It is of interest to investigate the interactions in other varietal wines in the future, e.g. Riesling.

5.4. CONCLUSIONS

In conclusion, this study investigates the interactions between monoterpene isomers and wine components that influence odor perception in one simple matrix and two complex matrices. Sensory discrimination tests were performed to elucidate the significance of monoterpene isomers at sub-threshold concentrations. Our study has shown that the non-volatile compositions in Pinot gris wine strongly increase the volatility of monoterpene isomers, while other aroma compounds suppressed odor perception, especially in the most complex profiles. This implies that monoterpene isomers may act as impact odorants by interacting with other wine components through a combination of enhancing and suppression effects. In addition, the matrix has a great influence on the odor perception of monoterpene isomers; odor perception changed when more components were present. We suggest that threshold determination of monoterpenes should be done by using the original matrix whenever possible, or matrix

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169 composed of components closely to the original one. These results are likely to improve our understanding of perceived aroma of wine. Future sensory analysis, especially descriptive tests will be performed in order to further understand the implications of the monoterpene isomers-wine component interactions.

ABBREVIATIONS

HS, head space; SPME, Solid Phase Micro-Extraction; MDGC-MS, multidimensional gas chromatography with mass spectrometry; OAV, odor activity value; GC-O, gas chromatography-Olfactometry; ANOVA, analysis of variance; Tukey's

HSD, Tukey’s honest significant difference

ACKNOWLEDGEMENT

The authors wish to thank Nadine Skyllingstad, Samuel Hoffman, Kiyomi Ide,

Chase E Jutzi, Anthony Le, and Vaishnavi Trivedi for their help with the sensory analysis in this study.

FUNDING

This project was funded by the Oregon Wine Board #2014-1516 and the Oregon

Wine Research Institute.

The authors declare no competing financial interest.

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170 REFERENCES

Adhikari, K., Hein, K. A., Elmore, J. R., Heymann, H., & Willott, A. M. (2006). Flavor threshold as affected by interaction among three diary-related flavor compounds. Journal of Sensory Studies, 21(6), 626-643.

Atanasova, B., Thomas-Danguin, T., Chabanet, C., Langlois, D., Nicklaus, S., & Etiévant, P. (2005). Perceptual interactions in odour mixtures: odour quality in binary mixtures of woody and fruity wine odorants. Chemical Senses, 30(3), 209-217.

Bi, J. (2007). Sensory discrimination tests and measurements. In): Wiley Online Library.

BI, J., ENNIS, D. M., & O'MAHONY, M. (1997). How to estimate and use the variance of d’from difference tests. Journal of Sensory Studies, 12(2), 87-104.

Boelens, M., Boelens, H., & Van Gemert, L. (1993). Sensory properties of optical isomers. Perfumer & Flavorist, 18(6), 1-16.

Bolman, S., & Tomasino, E. (2015). The direct effect of β-damascenone and β-ionone on sensory perception of Pinot noir wine quality. In 66th ASEV National Conference). Portland, OR.

Brenna, E., Fuganti, C., & Serra, S. (2003). Enantioselective perception of chiral odorants. Tetrahedron: Asymmetry, 14(1), 1-42.

Charles-Bernard, M., Kraehenbuehl, K., & Roberts, D. (2002). Interactions between volatile and non-volatile coffee components. Melanoidins in Food and Health, 4, 51-58.

Croghan, C., & Egeghy, P. (2003). Methods of dealing with values below the limit of detection using SAS. Southern SAS User Group, 22-24.

Diako, C., McMahon, K., Mattinson, S., Evans, M., & Ross, C. (2016). Alcohol, tannins, and mannoprotein and their interactions influence the sensory properties of selected commercial Merlot wines: A preliminary study. Journal of Food Science, 81(8).

Dufour, C., & Bayonove, C. L. (1999). Influence of wine structurally different polysaccharides on the volatility of aroma substances in a model system. Journal of Agricultural and Food Chemistry, 47(2), 671-677.

Elizabeth, T. (2011). Characterization of regional examples of New Zealand Pinot noir by means of sensory and chemical analysis. Lincoln University.

Ennis, D. M. (1993). The power of sensory discrimination methods. Journal of Sensory Studies, 8(4), 353-370.

170

171 Escudero, A., Gogorza, B., Melus, M., Ortin, N., Cacho, J., & Ferreira, V. (2004). Characterization of the aroma of a wine from Maccabeo. Key role played by compounds with low odor activity values. Journal of Agricultural and Food Chemistry, 52(11), 3516- 3524.

Friedman, L., & Miller, J. G. (1971). Odor incongruity and chirality. Science, 172(3987), 1044-1046.

Gierczynski, I., Guichard, E., & Laboure, H. (2011). Aroma perception in dairy products: the roles of texture, aroma release and consumer physiology. A review. Flavour and Fragrance Journal, 26(3), 141-152.

Goldner, M., di Leo Lira, P., van Baren, C., & Bandoni, A. (2011). Influence of polyphenol levels on the perception of aroma in Vitis vinifera cv. Malbec wines. South African Journal of Enology and Viticulture, 32, 21-27.

Harrison, M., & Hills, B. P. (1997). Mathematical model of flavor release from liquids containing aroma-binding macromolecules. Journal of Agricultural and Food Chemistry, 45(5), 1883-1890.

Jelen, H. (2011). Food flavors: chemical, sensory and technological properties: CRC Press.

Jones, P., Gawel, R., Francis, I., & Waters, E. (2008). The influence of interactions between major white wine components on the aroma, flavour and texture of model white wine. Food quality and preference, 19(6), 596-607.

Kopjar, M., Andriot, I., Saint-Eve, A., Souchon, I., & Guichard, E. (2010). Retention of aroma compounds: an interlaboratory study on the effect of the composition of food matrices on thermodynamic parameters in comparison with water. Journal of the Science of Food and Agriculture, 90(8), 1285-1292.

Li, H., Tao, Y.-S., Wang, H., & Zhang, L. (2008). Impact odorants of Chardonnay dry white wine from Changli County (China). European Food Research and Technology, 227(1), 287-292.

Lorrain, B., Ballester, J., Thomas-Danguin, T., Blanquet, J., Meunier, J. M., & Le Fur, Y. (2006). Selection of potential impact odorants and sensory validation of their importance in typical Chardonnay wines. Journal of Agricultural and Food Chemistry, 54(11), 3973- 3981.

171

172 Luan, F., Mosandl, A., Gubesch, M. and Wüst, M. (2006). Enantioselective analysis of monoterpenes in different grape varieties during berry ripening using stir bar sorptive extraction-and solid phase extraction-enantioselective-multidimensional gas chromatography-mass spectrometry. Journal of Chromatography A, 1112(1), 369-374.

Lubbers, S., Verret, C., & Voilley, A. (2001). The effect of glycerol on the perceived aroma of a model wine and a white wine. LWT-Food Science and Technology, 34(4), 262-265.

Lytra, G., Tempere, S., Revel, G. d., & Barbe, J.-C. (2012). Impact of perceptive interactions on red wine fruity aroma. Journal of Agricultural and Food Chemistry, 60(50), 12260-12269.

Marais, J., & Rapp, A. (1991). The selection of aroma-rich clones of Vitis vinifera L. cv. Gewurztraminer and Weisser Riesling by means of terpene analyses. South African Journal of Enology and Viticulture, 12(1), 51.

Martí, M. P., Mestres, M., Sala, C., Busto, O., & Guasch, J. (2003). Solid-phase microextraction and gas chromatography olfactometry analysis of successively diluted samples. A new approach of the aroma extract dilution analysis applied to the characterization of wine aroma. Journal of Agricultural and Food Chemistry, 51(27), 7861-7865.

Mayr, C. M., Geue, J. P., Holt, H. E., Pearson, W. P., Jeffery, D. W., & Francis, I. L. (2014). Characterization of the key aroma compounds in Shiraz wine by quantitation, aroma reconstitution, and omission studies. Journal of Agricultural and Food Chemistry, 62(20), 4528-4536.

Mikulíková, R., Golias, J., & Mrázová, V. (2009). SPME-GC-MS analysis of volatile compounds in Czech white wines from five grape varieties. Mitteilungen Klosterneuburg, Rebe und Wein, Obstbau und Früchteverwertung, 59(3), 159-165.

Mitropoulou, A., Hatzidimitriou, E., & Paraskevopoulou, A. (2011). Aroma release of a model wine solution as influenced by the presence of non-volatile components. Effect of commercial tannin extracts, polysaccharides and artificial saliva. Food Research International, 44(5), 1561-1570.

Noble, A. C. (1996). Taste-aroma interactions. Trends in Food Science & Technology, 7(12), 439-444.

172

173 Pineau, B. n. d., Barbe, J.-C., Van Leeuwen, C., & Dubourdieu, D. (2009). Examples of perceptive interactions involved in specific “red-” and “black-berry” aromas in red wines. Journal of Agricultural and Food Chemistry, 57(9), 3702-3708.

Plotto, A., Margaría, C. A., Goodner, K. L., Goodrich, R., & Baldwin, E. A. (2004). Odour and ﬂavour thresholds for key aroma components in an orange juice matrix: terpenes and aldehydes. Flavour and Fragrance Journal, 19(6), 491-498.

Polášková, P., Herszage, J., & Ebeler, S. E. (2008). Wine flavor: chemistry in a glass. Chemical Society Reviews, 37(11), 2478-2489.

Poole, C. (2009). Handbook of methods and instrumentation in separation science (Vol. 1): Academic Press.

Rapp, A. (1990). Natural flavours of wine: correlation between instrumental analysis and sensory perception. Fresenius' Journal of Analytical Chemistry, 337(7), 777-785.

Ribéreau-Gayon, P., Boidron, J., & Terrier, A. (1975). Aroma of Muscat grape varieties. Journal of Agricultural and Food Chemistry, 23(6), 1042-1047.

Robinson, A. L., Ebeler, S. E., Heymann, H., Boss, P. K., Solomon, P. S., & Trengove, R. D. (2009). Interactions between wine volatile compounds and grape and wine matrix components influence aroma compound headspace partitioning. Journal of Agricultural and Food Chemistry, 57(21), 10313-10322.

Ryan, D., Prenzler, P. D., Saliba, A. J., & Scollary, G. R. (2008). The significance of low impact odorants in global odour perception. Trends in Food Science & Technology, 19(7), 383-389.

Rychlik, M., Schieberle, P., & Grosch, W. (1998). Compilation of odor thresholds, odor qualities and retention indices of key food odorants: Dt. Forschungsanst. für Lebensmittelchemie.

Sáenz-Navajas, M.-P., Campo, E., Culleré, L., Fernández-Zurbano, P. n., Valentin, D., & Ferreira, V. (2010). Effects of the nonvolatile matrix on the aroma perception of wine. Journal of Agricultural and Food Chemistry, 58(9), 5574-5585.

Sereni, A., Osborne, J., & Tomasino, E. (2016). Exploring retro-nasal aroma’s influence on mouthfeel perception of Chardonnay wines. Beverages, 2(1), 7.

Shrivastava, A., & Gupta, V. B. (2011). Methods for the determination of limit of detection and limit of quantitation of the analytical methods. Chronicles of Young Scientists, 2(1), 21.

173

174 Song, M., Xia, Y., & Tomasino, E. (2015). Investigation of a quantitative method for the analysis of chiral monoterpenes in white wine by HS-SPME-MDGC-MS of different wine matrices. Molecules, 20(4), 7359-7378.

Takoi, K., Itoga, Y., Koie, K., Kosugi, T., Shimase, M., Katayama, Y., Nakayama, Y., & Watari, J. (2010). The contribution of geraniol metabolism to the citrus flavour of beer: synergy of geraniol and β-citronellol under coexistence with excess linalool. Journal of the Institute of Brewing, 116(3), 251-260.

Tandon, K., Baldwin, E., & Shewfelt, R. (2000). Aroma perception of individual volatile compounds in fresh tomatoes (Lycopersicon esculentum, Mill.) as affected by the medium of evaluation. Postharvest Biology and Technology, 20(3), 261-268.

Tomasino, E., Harrison, R., Breitmeyer, J., Sedcole, R., Sherlock, R., & Frost, A. (2015). Aroma composition of 2-year-old New Zealand Pinot Noir wine and its relationship to sensory characteristics using canonical correlation analysis and addition/omission tests. Australian Journal of Grape and Wine Research, 21(3), 376-388.

Villamor, R. R., & Ross, C. F. (2013). Wine matrix compounds affect perception of wine aromas. Annual review of food science and technology, 4, 1-20.

Voilley, A., & Lubbers, S. (1998). Flavor-matrix interactions in wine. In).

Wang, D., Ando, K., Morita, K., Kubota, K., & Kobayashi, A. (1994). Optical isomers of linalool and linalool oxides in tea aroma. Bioscience, Biotechnology, and Biochemistry, 58(11), 2050-2053.

Waterhouse, A. L., & Ebeler, S. E. (1998). Chemistry of wine flavor: American Chemical Society; Distributed by Oxford University Press.

Williams, A., & Rosser, P. (1981). Aroma enhancing effects of ethanol. Chemical Senses, 6(2), 149-153.

Yamamoto, T., Matsuda, H., Utsumi, Y., Hagiwara, T., & Kanisawa, T. (2002). Synthesis and odor of optically active rose oxide. Tetrahedron Letters, 43(50), 9077-9080.

Yoder, W. M., Currlin, S. W., Larue, A., Fernandez, K. M., King, D., & Smith, D. W. (2012). Interaction of guaiacol and methyl salicylate in binary mixture significantly lowers perceptual threshold in human observers. Journal of Sensory Studies, 27(3), 161- 167.

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175 Table 5.1. Selection of 46 bottles of Pinot gris wines.

Bottles of wines Region Vintage

Australia 2013 5 2011 1 Italy 2012 1 2010 1 New York, USA 2012 2 2013 2 2009 1 2011 1 New Zealand 2012 2 2013 8 2010 1 2011 3 Oregon, USA 2012 7 2013 9 2012 1 Washington, USA 2013 1

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176 Table 5.2. Profiles of monoterpene isomers in Pinot gris wines (µg L-1)*.

S-(-)- R-(+)- S-(-)-α- R-(+)-α- R-(+)-β- (-)-rose Linalool R-(-)- limonen limonen Linalool terpineo terpineo citronell oxide oxide linalool e e l l ol

Profile 1 1.89 3.04 7.46 Profile 2 19.36 5.01 7.04 4.44 Profile 3 0.36 18.63 4.94 8.30 4.11 Profile 4 21.92 5.83 4.78 7.36 5.05 Profile 5 0.25 23.11 5.14 8.57 3.03 Profile 6 1.48 1.53 20.11 6.80 8.58 5.63 Profile 7 0.50 27.74 12.83 6.86 8.77 6.38 Profile 8 0.63 0.17 18.31 5.54 7.10 9.59 3.88 Profile 9 1.54 1.58 22.63 16.22 8.24 10.57 6.02 Profile 10 4.90 4.02 0.34 46.46 45.74 29.02 33.25 5.39

* Numbers in bold are compound concentrations above their known detection threshold

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177 Table 5.3. d’ value between added samples and control in the 10 monoterpene profiles through 3 matrices performed by z-test.

profile Model solution De-aromatized wine Original wine Profile 1 0.74 0.51 1.21** Profile 2 0.00 1.47** 1.34*** Profile 3 1.21** 1.71*** 1.71*** Profile 4 0.91* 2.07*** 0.00 Profile 5 1.47*** 1.95*** 0.51 Profile 6 0.00 1.83*** 0.74 Profile 7 1.83*** 1.07* 0.91* Profile 8 0.00 1.71*** 0.00 Profile 9 0.74 1.95*** 1.95*** Profile 10 1.71*** 2.58*** 0.00

Significant difference level: * p<0.05, ** p<0.01, *** p<0.001

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178

R-(+)-ß-citronellol de R-(+)-a-terpineol fg S-(-)-a-terpineol ef S-(+)-linalool cd R-(-)-linalool bc (2S,5R)-(+)-cis-linalool oxide cde (2S,5S)-(-)-trans-linalool oxide ab (2R,5S)-(-)-cis-linalool oxide g (2R,5R)-(+)-trans-linalool oxide ef (2R,4R)-(-)-trans-rose oxide a (2S,4R)-(-)-cis-rose oxide a R-(+)-limonene a S-(-)-limonene a

0 2 4 6 8 10 Mean concentration (µg L-1)

Figure 5.1. Mean concentration of monoterpene isomers from 46 Pinot gris wines. Means with the same letter are not significantly different from each other (Tukey’s HSD, α= 0.05). The value of all non-detectable compounds were assigned to a value of LOD/2 where LOD is calculated from 3.3*(standard deviation of y-intercepts of regression line, SD)/ (slope of the regression line, b) (Croghan & Egeghy, 2003; Poole, 2009; Shrivastava & Gupta, 2011). The detailed information is in Table S 5.2.

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179 S 5.1. Working standards (WS) for sensory test (mg L-1).

S-(-)- R-(+)- S-(-)-α- R-(+)-α- R-(+)-β- (-)-rose Linalool R-(-)- limonen limonen Linalool terpineo terpineo citronell oxide oxide linalool e e l l ol

WS 1 2.36 3.80 9.33 WS 2 24.20 6.26 8.80 5.55 WS 3 0.45 23.29 6.18 10.38 5.14 WS 4 27.40 7.29 5.98 9.20 6.31 WS 5 0.31 28.89 6.43 10.71 3.79 WS 6 1.85 1.91 25.14 8.50 10.73 7.04 WS 7 0.63 34.68 16.04 8.58 10.96 7.98 WS 8 0.79 0.21 22.89 6.93 8.88 11.99 4.85 WS 9 1.93 1.98 28.29 20.28 10.30 13.21 7.53 WS 10 6.13 5.03 0.43 58.08 57.18 36.28 41.56 6.74

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180 S 5.2. Limit of detection (LOD)/2 for monoterpene isomers (µg L-1) and the number of wines with non-detectable isomer.

LOD/2 Pinot gris (46)*

S-(-)-limonene 0.0244 36

R-(+)-limonene 0.0156 36

(2S,4R)-(-)-cis-rose oxide 0.0026 35

(2R,4R)-(-)-trans-rose oxide 0.0000 46

(2R,5R)-(+)-trans-linalool oxide 0.0205 1

(2R,5S)-(-)-cis-linalool oxide 0.0276 1

(2S,5S)-(-)-trans-linalool oxide 0.0046 41

(2S,5R)-(+)-cis-linalool oxide 0.0111 1

R-(-)-linalool 0.0019 29

S-(+)-linalool 0.0017 30

S-(-)-α-terpineol 0.0135 0

R-(+)-α-terpineol 0.0160 1

R-(+)-β-citronellol 0.0093 1

* The number in the bracket is the total number of wines.

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181 CHAPTER 6

General conclusion and future work

6.1. GENERAL CONCLUSION

Monoterpenes are important floral and fruity contributors and are of great interest in white wines. Grape breeders, grape growers, viticulturist, winemakers and wine researchers have dedicated their effort in order to make high quality wines with balanced floral and fruity characters. Monoterpenes are one of aroma families composed of many different compounds (isomers or enantiomers) with diverse sensory characters. It is important to know the characteristic monoterpene profiles from different grape varieties, regions and wine styles, and the impact of monoterpene profiles on wine odor perception.

This study has aimed to investigate these aspects. All of the findings and results are summarized as follows:

Monoterpene enantiomers can be satisfactory separated using a HS-SPME-

MDGC-MS (chapter 2). With maximum separation in the first GC, then compound transfer to the second GC using heart-cutting, identification and measurement of these compounds have better sensitivity and resolution. The separation method has been validated with good wine reproducibility, standard stability and accuracy. Interestingly, fiber and matrix effect were found during extraction of monoterpenes using SPME from the wine matrix. The extraction ability of SPME fiber for monoterpenes varied during fiber lifetime, especially for limonene and rose oxide isomers. Rose oxides seemed to have lower vapor pressure in the wine matrix with high residual sugar content, therefore they tended to be easily released and had higher concentration in the headspace compared

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182 to the wine matrix with low residual sugar content. Different calibration curves were established in order to eliminate or minimize the impact from these two effects.

Monoterpene isomer profiles in final wines are affected by many factors, including grape variety, winemaking technique, aging or storage condition. The study showed that isomer profiles and enantiomer fractions were significant different between grape varieties and wine styles (chapter 3). The groupings by grape variety were different based on isomer profiles and enantiomer fractions. Three groups were classified due to total isomer contents, for example Muscat and Torrontes wines contained the highest concentration of monoterpene contents, followed by Gewurztraminer wines, and other varietal wines contained lower monoterpene content. The groupings based on enantiomer fractions were more specific, for example, Muscat, Torrontes and Riesling were classified as one group with S-(-)-limonene and (2R, 4S)-(+)-cis-rose oxide EFs as the important variables; Sauvignon blanc wines were characterized by (2R, 5R)-(+)-trans-linalool oxide

EF. A concern relating to the validity of groupings was the racemization or rearrangement of isomers during winemaking or storage, which may cause inconsistent changing of isomers. This results in uncertainty of variation of monoterpenes in wines due solely to grape variety. Low variation in enantiomeric fraction differences due to a single variety suggest that racemization is not an issue, suggesting very consistent enantiomer fraction during winemaking, aging and storage.

For a single grape variety, e.g. Riesling, region of origin and wine style affected monoterpene isomer profiles and enantiomer fractions (chapter 4). The high R2 value on the enantiomer pair plot fitted line implies low variation among enantiomer fractions in

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183 wines from a single region. Therefore the major differences of monoterpene isomers among regions were not owing to racemization or rearrangement of compounds during storage. Significant differences were found among the four regions and three wines styles.

Interestingly, German wines were dominant in (±)-linalool and R-(+)-β-citronellol isomers that show floral and fruity note and have low sensory thresholds. Oregon wines were characterized by all investigated monoterpene oxides which possess green, grassy, creamy or floral aroma and have high sensory thresholds. The most interesting finding was the differences among regions and styles based on enantiomer fractions. Enantiomer fraction differences were much smaller compared to differences due to isomer profiles.

All wines from France, New York and Oregon had similar enantiomer fractions distribution except German wines had different distributions. There were no significant differences of enantiomer fractions among the three styles.

The above conclusions were all related to chemical composition and provide additional knowledge of monoterpene isomers or enantiomers in wine. Monoterpenes as characteristic compounds contribute to the aroma of white wines. However, other white wines, especially neutral wines, e.g. Pinot gris contained monoterpenes at or lower than sensory threshold concentrations (chapter 5). The significance of monoterpenes on wine aroma has been addressed in chapter 5. Interactions between monoterpenes and other wine component to odor perception were investigated. The results showed that there were enhancement or suppression effects in a matrix among monoterpenes and other wine components, namely that odor perception was changed by these effects. The modification of odor perception varied among monoterpene profiles and matrices. The interactions

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184 between most of the monoterpene profiles and non-volatiles enhanced monoterpene odor perception in matrix 2, while masking effect occurred when monoterpenes added in matrix 3, suggesting interactions between some of the monoterpene profiles and other aroma compounds in the wine.

6.2. FUTURE WORK

The study can provide supporting information for the monoterpene chemistry and wine aroma interactions. However, there is much that can be further researched:

It would be very interesting to investigate monoterpene isomers or enantiomers in grapes. The changing of monoterpene isomer profiles during winemaking and aging could be monitored and the results in grapes and in final wines could be compared at the same level.

The study supported that enantiomer fractions could remain similar from a single grape variety. However, it would be much more convincing if we could systematically investigate the enantiomer fractions with a larger wine sample size, e.g. more regions and more styles of wines from single grape variety.

The impact of monoterpene profiles on odor perception is an ongoing project. The odor perception changes found across the matrices were previously unknown. Descriptive analysis is anticipated in order to describe the differences in odor quality and odor quantity by the interactions between monoterpene profiles and other wine components.

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Bibliography

A.A. Newman (Hrsg.). (1972). Chemistry of terpenes and terpenoids. Academic Press.

Armstrong, D. W., Chang, C. D., & Li, W. Y. (1990). Relevance of enantiomeric separations in food and beverage analyses. Journal of Agricultural and Food Chemistry, 38(8), 1674-1677.

Arrhenius, S., McCloskey, L., & Sylvan, M. (1996). Chemical markers for aroma of Vitis vinifera var. Chardonnay regional wines. Journal of Agricultural and Food Chemistry, 44(4), 1085-1090.

Barba, C., Flores, G., & Herraiz, M. (2010). Stereodifferentiation of some chiral aroma compounds in wine using solid phase microextraction and multidimensional gas chromatography. Food Chemistry, 123(3), 846-851.

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186 Bauer, K., Garbe, D., & Surburg, H. (2008). Common fragrance and flavor materials: preparation, properties and uses: John Wiley & Sons.