The Pennsylvania State University the Graduate School College Of

The Pennsylvania State University

The Graduate School

College of Agricultural Sciences

NOVEL VINIFICATION TECHNIQUES TO IMPROVE PENNSYLVANIA WINE QUALITY

A Thesis in Food Science by Laurel A. Vernarelli

Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science

August 2018

The thesis of Laurel A. Vernarelli was reviewed and approved* by the following:

Ryan J. Elias

Associate Professor of Food Science

Thesis Advisor

Joshua D. Lambert

Associate Professor of Food Science

Helene Hopfer

Assistant Professor of Food Science

Robert F. Roberts

Head of the Department of Food Science

*Signatures are on file in the Graduate School

Abstract

Laurel A. Vernarelli, Food Science, The Pennsylvania State University

Abstract of Masters Thesis, Submitted July 1, 2018

Novel Vinification Techniques to Improve Pennsylvania Wine Quality

The Commonwealth of Pennsylvania is the fifth largest producer of grapes in the United

States of America and was recently ranked as the tenth largest wine producing state. Wine is an important agricultural commodity to the Commonwealth, with $2 billion dollars in economic impact per year. Due to the cooler and more humid climate of the Northeastern United States, the challenges that Pennsylvania winemakers face differ from those of other wine-grape growing regions. Across the U.S. and globally, winemakers employ many vinification techniques and post-fermentation practices in order to contribute to wine quality and ensure a desirable product. Because wine quality and salability are correlated with freshness and maintenance of desirable sensory attributes, the success of these techniques is essential to the continued growth of the wine industry. The investigation of techniques which enhance or maintain quality, and that result in extended shelf stability of regional wines are of significant interest to the

Pennsylvania winemaker. Novel processing methods for increased quality and shelf stability of wines were investigated. The overall aim of this thesis is to evaluate novel vinification techniques that can improve wine quality with respect to overall oxidative stability.

Interspecific hybrid grapes (Vitis ssp.) are of particular interest to the Pennsylvania wine industry, as these extremely productive and disease-resistant varieties produce high quality wines and are suitable for growth in Northeastern climates. Hybrid grapes differ from traditional

European wine grape Vitis vinifera in several significant ways, many of which impact the quality of finished wine. Unlike vinifera, hybrids have not been subjected to a thorough investigation of III

the factors affecting wine quality and increased shelf stability. An improved understanding of the parameters affecting the production of high quality hybrid wines is extremely valuable to the

Pennsylvania wine industry. Maceration is an important vinification technique known to improve quality and shelf stability of wines due to the increased extraction of phenolic compounds and other beneficial, redox-active grape constituents. The versatile interspecific white-fleshed hybrid varieties Cayuga and Traminette were chosen to evaluate two novel maceration techniques, cryogenic maceration and extended skin contact, on the resulting phenolic content, antioxidant capacity, glutathione concentration, redox status of wine, CIE-LAB color values and conventional juice and wine parameters, in order to evaluate quantitative measures of overall quality and stability. In Cayuga and Traminette wines, both the cryogenic maceration and extended skin contact treatments resulted in significantly increased Folin-Ciocalteu total phenolic content over control wines. Antioxidant capacity, as measured by DPPH radical scavenging assay, was significantly increased in extended skin contact over control wines.

However, extended skin contact resulted in significant decreases in glutathione concentration and lower Fe (II) content for both Cayuga and Traminette wines. CIE-LAB color values indicated that Cayuga extended skin contact wine was significantly darker and more orange in color compared to the cryogenic maceration and control wines. Overall, the quality parameters and shelf stability of the cryogenically treated wines were maintained or increased compared to the control, indicating these maceration techniques may provide a viable and novel technique for the production of high quality, white hybrid wine.

Volatile sulfidic containing compounds (VSCs) have significant impacts on the sensory attributes of wine. Due to exceedingly low detection thresholds, VSCs are easily perceived by the consumer. Volatile sulfidic compounds such as H2S, methanthiol and ethanethiol are reminiscent of rotten eggs, cooked vegetables and sewage. The presence of these “reductive” aromas in wine is considered to be a quality defect. The removal of these off-aromas is typically

achieved by the method of copper fining, where copper in the form of Cu(II) is added directly to the wine. Increasing evidence implicates Cu(II) as playing a significant role in the chemical reactions and pathways governing the loss and formation of sulfhydryls during wine storage.

Several recent studies have shown that under reductive and anaerobic conditions, the reappearance of H2S and methanethiol has been observed post-bottling. Additionally, it has been reported that thiols are able to form complexes with Cu(II), and that the bound forms are reversible. These findings are significant, and together indicate that Cu(II) is a participant in troublesome reactions that liberate or regenerate H2S and thiols post-bottling. Because Cu(II) clearly plays a role in the manifestation of this common wine fault, its direct addition to wine must be avoided or minimized. Therefore, novel techniques that allow for H2S and thiol removal without the inadvertent introduction of Cu(II) that can remain in wine have been investigated.

Alternative fining techniques, such as the use of animal and plant-based proteins have been evaluated for Cu(II) removal post-copper fining. Proteins such as isinglass, gelatin, albumin, casein, and other plant-based proteins were assessed for their efficacy of Cu(II) concentration reduction under model wine conditions. The most substantial decrease in Cu concentration after

5 days was observed among the albumin and potato protein treatments, resulting in a 23 – 25% reduction in Cu concentration. The use of immobilized or bound forms of Cu(II), in which Cu(II) is adsorbed onto an inert substrate have been investigated as a replacement for traditional copper fining methods. Two bound Cu(II) forms, CuO- Alumina and Cu(NO3)2-Celite, were investigated for their ability to remove hydrogen sulfide (H2S), L-cysteine (Cys) and 3- sulfanylhexan-1-ol (3SH) under anaerobic model wine conditions over 4 hour and 24 hour time studies. The Cu concentration resulting from the presence of bound Cu(II) treatments in model wine solutions, Riesling and Lemberger over 24 hours was determined.

The maceration techniques of cryogenic maceration and extended skin contact resulted in chemical composition changes in Traminette and Cayuga wines that would provide benefits

for the production of high quality, shelf stable white hybrid wines. Alternatives to traditional copper fining methods were investigated, including the use of proteins and bound Cu(II) substrates. Alternative fining methods using proteins were proven to be effective at Cu removal in model wine. Two bound Cu(II) substances, CuO-Alumina and Cu(NO3)2-Celite, were shown to successfully decrease the concentrations of H2S, Cys and 3SH under anaerobic model wine conditions over 4-hour and 24-hour time periods, and provide a simple and effective method for

H2S and thiol removal in wine. These novel processing techniques have the potential to provide considerable benefits to the Pennsylvania wine industry.

Contents

List of Figures ...... XII

List of Tables ...... XVII

List of Abbreviations ...... XIX

Dedication ...... XX

Acknowledgements ...... XXI

Chapter 1 Literature Review ...... 1

1.1 Introduction ...... 1

1.1.1 Winemaking in Pennsylvania...... 2

1.2 Maceration Techniques...... 3

1.2.1 Extended Skin Contact ...... 3

1.2.2 Cryogenic Maceration ...... 4

1.3 Introduction to Oxidation Reactions in Wine...... 5

1.4 Glutathione ...... 9

1.4.1 Role in Wine Oxidation ...... 13

1.4.2 Impact on Aroma Compounds ...... 15

1.5 Phenolics ...... 16

1.5.1 Phenolic Compounds in Wine ...... 21

1.5.2 Oxidation of phenolic compounds in wine...... 22

1.6 Volatile Sulfidic Compounds in Wine...... 24

1.6.1 Fermentive Thiols ...... 25

1.6.2 Varietal Thiols ...... 26

1.7 Importance of Transition Metals to Non-Enzymatic Wine Oxidation ...... 27

1.7.1 Iron...... 28 VII

1.7.1.1 Fe(II) Concentration and Redox Status ...... 29

1.7.2 Copper ...... 30

1.7.3 Copper Fining ...... 31

1.7.4 Reactions of Copper in Wine ...... 32

1.7.5 Release of Metal Sulfide and Metal Thiol Complexes ...... 33

1.7.6 Current Methods for Copper Removal in Wine ...... 35

1.7.7 Bound Cu(II) Fining Techniques ...... 35

1.7.8 Potential for Proteins to Remove Copper in Wine ...... 36

1.8 Purpose and Significance ...... 37

1.9 Hypothesis and Objectives ...... 38

Chapter 2 Effect of Maceration Techniques on White Wine Quality Made from

Interspecific Hybrid Grapes (Vitis ssp.) ...... 39

2.1 Abstract ...... 39

2.2 Introduction ...... 40

2.3 Materials and Methods ...... 43

2.3.1 Chemicals ...... 43

2.3.2 Maceration Treatments ...... 44

2.3.2.1 Cryogenic Maceration ...... 44

2.3.2.2 Control ...... 45

2.3.2.3 Extended Skin Contact ...... 45

2.3.3 Vinification...... 45

2.3.4 Juice and Wine Chemical Analysis ...... 48

2.3.5 CIE-LAB Color Measurements ...... 49

2.3.6 Determination of antioxidant capacity ...... 50

2.3.7 Determination of total phenolic content ...... 50

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2.3.8 Glutathione determination ...... 51

2.3.9 Accelerated aging study ...... 52

2.3.9.1 Measurement of Fe(II):Fe(III) ratios in wine...... 52

2.3.10 Statistical analysis ...... 53

2.4 Results and Discussion...... 54

2.4.1 Juice and Wine Conventional Analysis ...... 54

2.4.2 CIE-LAB Color Values ...... 55

2.4.2.1 CIE-LAB Color Values for Traminette...... 58

2.4.3 Determination of Antioxidant Capacity ...... 61

2.4.4 Determination of Total Phenolic Content ...... 65

2.4.5 Glutathione Determination ...... 69

2.4.6 Accelerated Aging Study ...... 71

Chapter 3 Novel Methods for Copper Removal in Wine ...... 75

3.1 Abstract ...... 75

3.2 Introduction ...... 76

3.3 Materials and Methods ...... 79

3.3.1 Chemicals ...... 79

3.3.2 Vinification...... 79

3.3.3 Juice and wine analysis ...... 81

3.3.4 Simulated Protein Fining Experiments ...... 82

3.3.5 Simulated copper fining with bound Cu(II) in model wine ...... 83

3.3.6 Simulated copper fining with bound Cu(II) in real wine systems ...... 83

3.3.7 Copper determination ...... 84

3.3.8 H2S and thiol reduction by bound Cu(II) ...... 84

3.3.9 Spectrophotometric measurements of thiols and H2S ...... 85

3.3.10 Statistical Analysis ...... 86

3.4 Results and Discussion...... 87

3.4.1 Protein fining as a method of copper removal in model wine ...... 87

3.4.2 Copper Determination of Bound Cu(II) in Model Wine ...... 92

3.4.3 Simulated Copper Fining with Bound Cu(II) Particles in Real Wine Systems .... 94

3.4.3.1 Bound Cu(II) in Riesling over 24h ...... 95

3.4.3.2 Bound Cu(II) in Lemberger over 24h ...... 97

3.4.4 Reduction of thiols and H2S by bound Cu(II) ...... 99

3.4.4.1 H2S Reduction by Bound Cu(II) over 4h ...... 100

3.4.4.2 Cys Reduction by Bound Cu(II) over 4h ...... 100

3.4.4.3 3SH Reduction by Bound Cu(II) over 4h ...... 102

3.4.4.4 H2S Reduction by Bound Cu(II) over 24h ...... 103

3.4.4.5 Cys Reduction by Bound Cu(II) over 24h ...... 104

3.4.4.6 3SH Reduction by Bound Cu(II) over 24h ...... 105

3.4.4.7 Comparison of Each Treatment on Efficacy of H2S/Thiol Removal...... 106

3.4.5 Concluding Remarks ...... 111

Chapter 4 Conclusions and Future Work ...... 113

4.1 Summary ...... 113

4.2 Future work...... 114

4.2.1 Further investigation of the effects of maceration treatments ...... 114

4.2.2 Identification and quantification of volatile aroma compounds in Cayuga and

Traminette wines ...... 115

4.2.3 Copper Fining with Bound Cu(II) Treatments in Real Vinification Setting...... 116

References ...... 117

Appendix A: Supplementary Information for Chapter 2 ...... 124

Appendix B: Supplementary Information for Chapter 2 ...... 127

7.1 Reporting of One Way ANOVA Results ...... 127

7.1.1 Juice and Wine pH ...... 127

7.1.1.1 Cayuga ...... 127

7.1.1.2 Traminette ...... 128

7.1.2 Antioxidant capacity ...... 130

7.1.2.1 Cayuga ...... 130

7.1.2.2 Traminette ...... 131

7.1.3 Total Phenolic Content ...... 132

7.1.3.1 Cayuga ...... 132

7.1.3.2 Traminette ...... 133

7.1.4 Glutathione ...... 134

7.1.4.1 Cayuga ...... 134

7.1.4.2 Traminette ...... 134

Appendix C: Supplementary Information for Chapter 3 ...... 136

8.1 Reporting of Assumption Tests from Two-Way ANOVA ...... 136

8.1.1 Bound Cu(II) in Riesling over 24h ...... 136

8.1.2 Bound Cu(II) in Lemberger over 24h ...... 140

8.2 Reduction of thiols and H2S by bound Cu(II) ...... 144

8.2.1 H2S Reduction by Bound Cu(II) over 4h ...... 144

8.2.2 Cys Reduction by Bound Cu(II) over 4h ...... 147

8.2.3 3SH Reduction by Bound Cu(II) over 4h...... 151

8.2.4 H2S Reduction by Bound Cu(II) over 24h ...... 155

8.2.5 Cys Reduction by Bound Cu(II) over 24h ...... 158

8.2.6 3SH Reduction by Bound Cu(II) over 24h...... 162

List of Figures

Figure 1.1. Four electron steps in the reduction of O2 to H2O via the hydroperoxyl radical HO2•

and the hydroxyl radical, HO•...... 6

Figure 1.2. Reactions involving iron in mediating catechol oxidaiton [14]...... 7

Figure 1.3. Overview of oxidation reactions that occur in wine. Oxygen-driven formation of

quinones, hydrogen peroxides consequent oxidation of ethanol to acetaldehyde and main

reactions of quinones under wine conditions [9]...... 8

Figure 1.4. Proposed mechanisms illustrating SO2 and GSH antioxidant protection in wine [9]. . 9

Figure 1.5. Structure of the glutathione molecule in its reduced (free thiol) form. The important

functional group in terms of chemical activity is its nucleophilic cysteine thiol group...... 10

Figure 1.6. Generalized schematic explaining the formation of colored compounds in wine, and

the role of GSH in the prevention of oxidation...... 15

Figure 1.7. Most common flavonoid compounds found in wine [39]...... 19

Figure 1.8. Most common non-flavonoids found in wine [39]...... 20

Figure 1.9. Enzymatic browning processes observed in grape must [40]...... 23

Figure 1.10. Relationship between the Fe(II):Fe(III) ratio and redox status. Proposed

mechanism by Danilewicz for the interaction of O2 with Fe in wine and the competition of

2+ Fe(III) and Fe(II) for the Fe(III)-superoxide complex ([Fe(III)-O2•] ) [83]...... 30

Figure 1.11. Removal of H2S by the addition of Cu (II), resulting in the formation of insoluble

CuS...... 31

Figure 1.12. Proposed mechanism for the initial reaction of thiols with Cu(II) and Cu(I)-thiol

complex formation [15]...... 33

Figure 2.1. Image of Cayuga wine replicates; from left: control (C), cryogenic maceration (CM)

and extended skin contact ESC...... 58

Figure 2.2. Image of bottled Traminette replicates; from left: control (C), cryogenic maceration

(CM) and extended skin contact ESC...... 61

Figure 2.3. Antioxidant capacity as measured by DPPH, expressed as mg/L Trolox equivalents,

for control (C), cryogenic maceration (CM), and extended skin contact (ESC) for a) Cayuga

juice; b) for Cayuga wine; c) for Traminette juice; and d for Traminette wine. Different

letters indicate statistical significance by one-way ANOVA...... 63

Figure 2.4. Total phenolic content as measured by Folin-Ciocaultau, expressed as mg/L Gallic

acid equivalents, for control (C), cryogenic maceration (CM), and extended skin contact

(ESC) for a) Cayuga juice; b) for Cayuga wine; c) for Traminette juice; and d) for

Traminette wine. Different letters indicate statistical significance by one-way ANOVA...... 67

Figure 2.5. Glutathione concentration, expressed as mg/L, for control (C), cryogenic maceration

(CM), and extended skin contact (ESC) for a) Cayuga juice; b) Cayuga wine; c) Traminette

juice and Traminette wine. Different letters indicate statistical significance by one-way

ANOVA...... 71

Figure 2.6. Change in %Fe(II) concentration of Cayuga wine for control (C), cryogenic

maceration (CM) and extended skin contact (ESC) wines over 96 hours...... 73

Figure 2.7. Change in %Fe(II) concentration in Traminette wine for control (C), cryogenic

maceration (CM) and extended skin contact (ESC) over 96 hours...... 74

Figure 3.1. H2S and thiols used throughout this study...... 85

Figure 3.2. Initial Cu Concentration 30 minutes after protein fining. Different letters indicate

statistical significance by one-way ANOVA. One-way ANOVA revealed statistically

significant differences between treatments...... 88

XIII

Figure 3.3. Concentration of Cu five days after a 1 mg/L Cu addition in the presence of various

fining proteins, as determined by ICP-OES. Different letters indicate statistical significance

by one-way ANOVA, which revealed statistically significant difference between protein

fining treatments for Cu concentration in model wine after five days (F(7,23) = 223.759, p <

.001)...... 90

Figure 3.4. Removal of Cu(II) determined by ICP-OES after the addition of 1 mg/L Cu(II) to

animal and plant fining proteins over five days in model wine. Goldenclar, Finecoll,

Blancoll, Plantis AF, Plantis AF-P, Protoclar and PVPP were prepared and added to model

wine in the dosages found in Table 3.1. Error bars indicate standard deviation of triplicate

measurements...... 90

Figure 3.5. Cu concentration determined by ICP-OES 30 minutes after the addition of CuSO4,

Bound Cu(II) particles and analogous inert substrates to model wine. An effective Cu

concentration of 1 mg/L Cu(II) of CuSO4, CuOAl and CuCelite was added to simulate

conditions in real wine systems. Different letters indicate statistical significance by one-way

ANOVA. There was a statistically significant difference between groups for initial Cu

concentration in model wine as determined by one-way ANOVA, F(5,17) = 13836.316, p <

.001. A Tukey post hoc test revealed that initial Cu concentration in the CuSO4 treated

sample (.89 ± .01 mg/L Cu) was found to be significantly higher than the control CuOAl,

alumina (.006 ± .003 mg/L Cu), CuCelite (.040 ± .001 mg/L Cu) p < .001. Error bars

indicate standard deviation of triplicate measurements...... 94

Figure 3.6. Cu concentration as determined by ICP-OES after the addition of 1 mg/L CuSO4 or

bound Cu(II) treatment in Riesling over 24 hours. A two-way ANOVA was conducted to

examine the effects of treatment and time on Cu concentration. There was a statistically

significant differences between treatment and time for Cu concentration, F(18, 140) =

XIV

13.337, p < .001, partial η2 = .632. For some points, the error bars are shorter than the

height of the symbol and they have not been drawn...... 97

Figure 3.7. Cu concentration as determined by ICP-OES after the addition of 1 mg/L CuSO4 or

bound Cu(II) treatment in in Lemberger over 24 hours. A two-way ANOVA was conducted

to examine the effects of treatment and time on Cu concentration. There was a statistically

significant difference between treatment and time for Cu concentration, F(18, 140) =

44.121, p < .001, partial η2 = .850. For some points, the error bars are shorter than the

height of the symbol and they have not been drawn...... 99

Figure 3.8. Loss of H2S in oxygen-ingress controlled model wine experiments upon addition of

Cu(II) (50 µM) in the form CuSO4 and bound Cu(II) treatments to H2S (300 µM) over 4

hours...... 100

Figure 3.9. Loss of Cys in oxygen-ingress controlled mode wine experiments upon addition of

bound Cu(II) treatments over 4 hours...... 102

Figure 3.10. Loss of 3SH in oxygen-ingress controlled mode wine experiments upon addition of

bound Cu(II) treatments over 4 hours...... 103

Figure 3.11. Loss of H2S in oxygen-ingress controlled mode wine experiments upon addition of

bound Cu(II) treatments over 24 hours...... 104

Figure 3.12. Loss of Cys in oxygen-ingress controlled mode wine experiments upon addition of

bound Cu(II) treatments over 24 hours...... 105

Figure 3.13. Loss of 3SH in oxygen-ingress controlled mode wine experiments upon addition of

bound Cu(II) treatments over 24 hours...... 106

Figure 3.14. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for

oxygen-ingress controlled model wine experiments for samples treated with CuSO4...... 107

Figure 3.15. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for

oxygen-ingress controlled model wine experiments for samples treated with CuOAl...... 108

Figure 3.16. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for

oxygen-ingress controlled model wine experiments for samples treated with Cu-Celite. . 109

Figure 3.17. Cu Concentration determined by ICP-OES, from samples collected during the

oxygen-ingress controlled H2S experiment at 30 minutes and 24 hours...... 110

Figure 3.18 Cu Concentration determined by ICP-OES, from samples collected out of BOD

bottles from Cys experiment at 30 minutes and 24 hours...... 111

Figure 6.1 Traminette Control Juice Full HPLC-ECD Spectrum...... 124

Figure 6.2 Traminette Control juice sample spectrum zoomed to GSH peak at rt = 6.6...... 124

Figure 6.3 Traminette CM juice full HPLC-ECD sample spectrum ...... 125

Figure 6.4 Traminette CM juice sample spectrum zoomed to peak area, which was very small

(17 nA), well beneath the calibration curve (700 nA at the lowest). In the cryogenic

maceration juice samples, glutathione was detected but was below the limit of

quantification...... 125

Figure 6.5. Traminette ESC juice full HPLC-ECD sample spectrum ...... 126

Figure 6.6. Traminette ESC juice sample spectrum zoomed in to observe glutathione peak at rt

= 6.6. Glutathione in the Traminette juice for the ESC samples was below the limit of

detection, and possibly obscured by a peak at rt = 6.8...... 126

XVI

List of Tables

Table 1.1: Structure and associated sensory descriptor of various fermentation-derived thiol

compounds...... 25

Table 1.2: Structures and associated sensory descriptor of various of varietal thiols...... 26

Table 2.1: Juice soluble solids, wine pH and acidity for Traminette and Cayuga White grape

varieties grown at two New York Locations from Cornell University...... 41

Table 2.3: Juice and wine conventional analysis of Cayuga (mean values and standard

deviation) for control (C), cryogenic maceration (CM), and extended skin contact (ESC).

One-way ANOVA indicated significant between-group difference. Different letters indicate

statistical difference...... 54

Table 2.4: Juice and Wine Conventional Analysis of Traminette (mean values and standard

deviation) for control (C), cryogenic maceration (CM), and extended skin contact (ESC).

One-way ANOVA indicated significant between-group difference. Different letters indicate

statistical difference...... 54

Table 2.5: CIE-LAB color values observed from Cayuga juice and wine for control (C),

cryogenic maceration (CM), and extended skin contact (ESC) treatments. One-way

ANOVA indicated significant between-group difference. Different letters indicate statistical

difference...... 55

Table 2.6: Changes in CIE-LAB color parameters observed between Cayuga juice and wine, in

comparison to the control, due to maceration processes...... 57

Table 2.7: CIE-LAB color values observed from Traminette juice and wine for control (C),

cryogenic maceration (CM), and extended skin contact (ESC) treatments. One-way

ANOVA indicated significant between-group difference. Different letters indicate statistical

difference...... 59

Table 2.8: Changes in CIE-LAB color parameters observed between Traminette juice and wine,

in comparison to the control, due to maceration processes...... 60

Table 2.9: Antioxidant capacity of DPPH radical scavenging, expressed in mg/L Trolox, and

Folin-Ciocalteau (F-C) total phenolic content, expressed as mg/L gallic acid equivalents for

control (C), cryogenic maceration (CM), and extended skin contact (ESC) for Cayuga juice

and wine. One-way ANOVA indicated significant between-group difference. Different letters

indicate statistical difference...... 65

Table 2.10: Antioxidant capacity of DPPH radical scavenging, expressed in mg/L Trolox, and

Folin-Ciocalteau (F-C) total phenolic content, expressed as mg/L gallic acid equivalents for

control (C), cryogenic maceration (CM), and extended skin contact (ESC) for Traminette

juice and wine. One-way ANOVA indicated significant between-group difference. Different

letters indicate statistical difference...... 65

Table 3.1: Protein composition of various fining protein treatments and respective dose in mg/L

added to model wine, as recommended by the manufacturer...... 83

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List of Abbreviations

3SH 3-sulfanylhexan-1-ol; aka 3-mercaptohexan-1-ol (3MH) C Control

CM Cryogenic Maceration

Cu Copper

CuCelite Copper nitrate on Celite (Cu(NO3)2-Cel)

CuOAl Copper oxide on alumina

Cys L-cysteine ESC Extended Skin Contact EtSH Ethanethiol GC Gas chromatography GC-MS Gas chromatography mass spectrometry GC-MS-O Gas chromatography mass spectrometry olfactometry GRP 2-S-glutathionyl caftaric acid or grape reaction product GSH Glutathione HPLC High performance liquid chromatography ICP-OES Inductively Couple Plasma-Optical Emission Spectroscopy kDa Kilodalton LOD Limit of detection LOQ Limit of quantitation MeSH Methanthiol MLF Malolactic fermentation pI Isolectric point PPO Grape polyphenol oxidase PVPP Polyvinylpolypyrrolidone ROS Reactive oxygen species RSD Relative standard deviation

SO2 Sulfur dioxide

XIX

TA Titratable acidity TSS Total soluble solids VA Volatile acidity VSCs Volatile sulfidic containing compounds YAN Yeast assimilable nitrogen

Dedication

“If I have seen further, it is by standing on the shoulders of giants.” – Sir Issac Newton, in a letter written to fellow scientist Robert Hooke in February 1675.

To the long line of Taylors and Vernarellis who have paved the way before me, and whose scientific curiosity was clearly genetic.

XXI

Acknowledgements

I am extremely grateful to Dr. Ryan Elias for his support, guidance and mentorship, and especially for providing me the opportunity to take the plunge into the domain of Food Chemistry in his lab at Penn State (even though he’s a Patriots fan, Go Bills!). I would like to thank my committee members, Dr. Josh Lambert and Dr. Helene Hopfer for their guidance and support.

I am also incredibly grateful to Dr. Wai Fun Leong for her generous support, sharing of her technical knowledge and invaluable assistance during winemaking and analysis of Fall 2017.

Thank you to Happy Valley Vineyard and Winery, especially Dr. Elwin Stewart, Dr. Barb Christ,

Cody Edling and Logan for their collaboration. I also would like to thank Dr. Samantha Reilly and Dr. John Richie at Penn State Hershey College of Medicine for their support and assistance.

I would like to thank the Department of Food Science for providing salary and tuition support. I would also like to thank the Pennsylvania Wine Research and Marketing Board for providing some of the funding support for this project.

I would like to thank the past and current members of the Elias lab for their support, especially Dr. Gal Kreitman, who provided immense guidance and direction throughout my tenure at Penn State. I would like to thank Dr. Frank Dorman for introducing me to the world of chromatography, providing mentorship, guidance and a few wisecracks along the way. I would also like to thank the members of the Dorman lab, especially Paulina Piotrowski, for her invaluable technical assistance, knowledge and expertise.

I would like to thank Dr. Michela Centinari for her guidance and support during my initial harvest and winemaking endeavors during Fall 2016. I would also like to thank the members of the Centinari lab, especially Maria Smith and Drew Harner, for their willingness to provide technical assistance; especially for rolling up their sleeves and providing extra pairs of hands

XXII

during harvest and winemaking of Fall 2016. Thank you to Fero vineyards for providing the

Riesling and Lemberger grapes for this project.

Many, many thanks to the Mrs. Denise Gardner Scheinberg, for graciously sharing her vast knowledge, expertise and winemaking skills, in addition to her continual encouragement and support throughout my tenure at Penn State.

Last but not least, I am incredibly thankful to my friends and family for their love and support.

An especially big thank you to my sister Dr. Jacqueline Vernarelli and brother-in-law Dr. Ross

MacLean for their assistance in statistical analysis, encouragement and astute advice. Thanks to my parents for supporting me in my pursuits and providing wisdom along the way. Finally, thank you to MDF.

XXIII

Chapter 1

Literature Review

1.1 Introduction

Many important parameters affect the quality of white wines. Wine is a complex mixture of chemical compounds which provide the quality and sensory attributes that are enjoyed by the consumer. Aromatic white wines are particularly susceptible to oxidation reactions that can compromise their quality, and any new winemaking techniques that allow these desirable attributes to be preserved would be greatly beneficial to the winemakers. Traditionally, the most powerful tool available to winemakers for the prevention of oxidation in white wine is the addition of sulfur dioxide (SO2). However, there are downsides to the addition of large quantities of SO2 to wine for the prevention of oxidation. High levels of SO2 can mask certain desirable aroma components in white wines and as a result, detract from overall wine quality. Additionally, the legal limit of total SO2 concentration allowed in wines in the United States is 350 mg/L, and total

SO2 is similarly regulated in major winemaking nations with legal limits ranging from 150 – 400 mg/L [1]. Therefore, it is necessary to develop and provide winemakers with more robust techniques to control oxidation, including novel processing methods. In addition, it is important to expand this knowledge for its application and use in other varieties of wine grapes beyond the

European wine grape Vitis vinifera. Interspecific hybrid grapes (Vitis ssp) are extremely important for winemaking in the Northeastern United States, including Pennsylvania, but there is very little current research on novel processing methods for these varieties. The current

literature mostly pertains to vinifera wines, but hybrids are quite different in terms of chemical composition and therefore will respond differently to processing and storage.

1.1.1 Winemaking in Pennsylvania

Interspecific hybrid grapes (Vitis ssp), commonly known as French American hybrid grapes, are an important agricultural commodity to the Commonwealth of Pennsylvania’s $1.8 billion wine industry. These hybrids grapes are products of breeding programs in response to the

North American pests phylloxera (Daktulospharia vitifoliae) and powdery mildew (Uncinula necator) introduced to Europe in the mid-1800’s, which devastated traditional European wine grapes Vitis vinifera primarily used for high quality wine production. Recent hybrids have been selected specifically for their adaption to local climate conditions, as well as the ability to produce high quality wines. This is especially important to the Northeastern United States, a region where relatively few vinifera or European varieties of grapes can be successfully grown due to climate challenges.

Hybrid grapes are more suitable for growth in the cool and humid climates of eastern North

America compared to vinifera grapes. Hybrid grapes offer benefits over vinifera varieties which are susceptible to cold damage, disease and do not grow as productively in the Northeastern climate of the United States. Hybrids are typically distinguished by their noteworthy wine quality compared to native grape species, as well as their partial resistance to several fungal diseases and superior cold hardiness relative to their vinifera counterparts. Previous studies have shown several significant differences between vinifera and hybrid grapes that impact the quality of finished wine, and a more thorough investigation is required [2]. Additionally, because hybrids are not as widely studied as vinifera varieties, an improved understanding of the parameters affecting the production of high quality wine from hybrid grapes is extremely desirable for winemakers. Thus, greater insight into the impact of vinification techniques on quality

enhancement is necessary for wine regions where hybrid grapes are economically important, such as Pennsylvania. 1.2 Maceration Techniques

Maceration is the winemaking process wherein minor grape components are extracted from the grape skin, seeds and stems into the must. These phenolic compounds include anthocyanins, which provide color, as well as polymeric phenolics (e.g., tannin) and aroma active compounds. Historically, maceration during the production of certain white wines is avoided or minimized in order to preserve varietal characteristics and to prevent the extraction of bitter or astringent components, resulting in very limited contact between grape skins and juice prior to pressing. Aromatic white wines (e.g., Sauvignon blanc) are not typically subjected to maceration techniques in order to prevent the loss of volatile and/or oxidatively labile compounds. Performing maceration during winemaking for these varietals can result in bitter and astringent white wines with off-colors and flavors. Maceration of certain varieties may result in white wines that are not typical of their varietal characteristics.

1.2.1 Extended Skin Contact

Skin contact during winemaking is defined as a pre-fermentation process in which skins of crushed and destemmed grapes are macerated in their own juice prior to pressing. Although maceration is not typically employed in traditional white wine production, it is a critical step in the production of many other types of wine. In red wine production, the long skin contact time during fermentation results in a wine that is high in phenolics that contribute antioxidant capacity, deep in color, but may also be astringent. It has previously been shown that skin contact is able to improve the quality of a white wine due to flavor extraction from the skins [3]. It has also been shown that a much greater extraction of phenolic compounds occurs during extended skin contact during winemaking [4]. Phenolic compounds in wine are responsible for some of the

major organoleptic properties of wine, specifically color and astringency. Because of their antioxidant capacity, these compounds are of particular interest to consumers due to their potential health benefits. Phenolic compounds are also responsible for eliciting characteristic aromas and mouthfeel. An increase in phenolic and antioxidant capacity has been associated with increased mouthfeel attributes [5]. Additionally, these compounds contribute to color stability because of their ability to act as antioxidants.

1.2.2 Cryogenic Maceration

Cryogenic maceration is a maceration process by which grapes or grape must is frozen for a period of time prior to the start of fermentation; the cold temperature is thought to minimize the loss of aroma compounds and increase the extraction of phenolic compounds [6]. Cryogenic maceration is technique that has recently been shown to provide significant advantages in white wine production without negatively affecting the sensory properties of the wine [4]. It has previously been shown in Sauvignon blanc wines that cryogenic maceration resulted in an increase in phenolics, antioxidant capacity and the level of several varietal aroma compounds

[5]. The benefit of cryogenic maceration is thought to be due to two aspects. Because of the cell wall disruption of the grape that occurs during cryogenic maceration, the phenolic content of the wine is increased, as more phenolics are extracted from the grape than in a typical white winemaking process. As previously discussed in section 1.2.1, this increase in phenolics is associated with increased antioxidant capacity in the wine. Additionally, the evolution of carbon dioxide gas as it sublimes from solid dry ice during the maceration process leads to an air-free headspace above the must. This provides a protective barrier which is free of reactive oxygen species. It has been shown previously that cryogenic maceration increases phenolics not only due to increased extraction, but also prevents loss due to the ability to protect against oxidation

[5, 7]. Cryogenic maceration is effective in liberating grape skin and seed phenolics without the

need of ethanol to increase extraction, as in the extended skin contact method. Because of the disruption of the cellular membrane, the juice is easier to extract from the grapes, leading to a decrease in press time and pressure. The juice and must are especially susceptible to oxidation during pressing operations, and decreased air contact time during pressing allows for less of a chance of oxidation [8]. Additionally, the low temperature during cryomaceration inhibits the polyphenol oxidase (PPO) enzymes that are released from the grape as cell walls are disrupted

[5].

The potential benefit of these maceration techniques on hybrid grape varieties in particular is significant. The effect of maceration techniques on tannin extractability was studied on red hybrid grapes, and the findings suggest that differing concentration of tannins between hybrid and vinifera wine may be due to differences in tannin extractability rather than differing initial tanning concentration in grape seeds and skins between varieties [2]. Because extractability of certain compounds from grapes is tissue specific and cultivar dependent, hybrid white varieties may benefit from maceration to increase the phenolic content, preserve aromatic profile and quality parameters. Other studies have reported that a significant amount of tannins remain bound to insoluble cell wall materials post-fermentation, potentially bound to both the berry skin and flesh, which could indicate a greater tannin-cell wall interaction causing the lower tannin extractability in red hybrid wines [2]. The disruption of the cell wall during cryogenic maceration and subsequent release of bound phenolic compounds could be exploited and leveraged in hybrid varieties for a resulting increase in wine quality. Previous studies have shown maceration needs to be controlled in order to maximize the benefits and minimize any resulting undesirable attributes [4]. 1.3 Introduction to Oxidation Reactions in Wine

Wine oxidation is a long-standing problem and is of particular consequence in white

wines. The underlying mechanisms of non-enzymatic oxidation reactions that occur in wine

have undergone extensive investigation by wine researchers, which has resulted in the more

recent focus on the role of transition metals and radical intermediates in these processes.

Although it has been observed that increasing rates of O2 ingress dictate the overall rate of

non-enzymatic wine oxidation, the direct reaction of wine constituents with oxygen in its stable

3 triplicate ground state ( O2) does not occur, due to its electron configuration and spin state [9].

However, O2 may be reduced by transition metals to form reactive oxygen species (ROS)

which are able to undergo direct reaction with organic compounds in wine. Reactive oxygen

species is a collective term that describes oxygen radicals. A few examples of ROS include

− superoxide anion (O2• ) and its conjugate acid hydroperoxyl (HOO•), hydroxyl (HO•), peroxyl

(ROO•), alkoxyl (RO•) radicals, and other non-radicals that are either potential oxidizing

agents or are easily converted into radicals, such as hydrogen peroxide (H2O2), ozone (O3),

1 hypochlorous acid (HOCl), singlet oxygen ( O2), and lipid peroxide (LOOH) [10]. In many

biological systems, free radical species are known to participate in the chemical reactions

governing food spoilage, and play a particularly significant role in the non-enzymatic oxidation

of wine. Under wine conditions, the reduction of oxygen can occur in four discrete one-

electron steps catalyzed by transition metals, as shown in Figure 1.1 [11].

e- / H+ e- / H+ e- / H+ e- / H+ O2 HO2 H2O2 H2O + HO 2H2O

Figure 1.1. Four electron steps in the reduction of O2 to H2O via the hydroperoxyl radical HO2• and the hydroxyl radical, HO•.

In wine, ROS are produced by reduced transition metals, such as Fe(II) present in wine through a stepwise addition of a single electron to triplet oxygen. This reaction generates at

(III)- 2+ singlet superoxide species ([Fe O2•] . Initially, it was proposed by Danilewicz that the mechanism of oxidation is due to the reaction of ortho-diphenol (catechol) groups with hydroperoxyl radicals, resulting in the generation of a quinone and H2O2 [12] [13]. More recent studies by Danilewicz and Kreitman et al, have found that Fe(II) and Cu(II), in concert, are able to mediate reduction of O2 to H2O2 without release of hydroperoxyl radicals or oxidation of catechols [14] [15], as shown in Figure 1.2.

Monocatecol OH CH3CH2OH 3+ - - Fe O2• /HO2• H2O2 HO• R OH CH3CHOH Fe2+ Fe3+ O CH3CHO 2+ H O Fe O2 2 Semiquinone R O ortho-Quinone

Figure 1.2. Reactions involving iron in mediating catechol oxidaiton [14].

- Upon generation of H2O2, it may be consumed by bisulfite (HSO3 ) which is present in

wine due to both endogenous (yeast-derived) or exogenous (additives) sources; or it may

undergo metal-catalyzed reduction via the Fenton reaction and generate highly reactive

hydroxyl radicals (HO•) [12, 16]. The hydroxyl radicals may then react indiscriminately with

organic compounds present in wine, governed by diffusion limiting rates proportional to their

concentration, with the most likely target being ethanol due to its abundance in wine. The

oxidation of ethanol results in the formation of the reactive intermediate 1-hydroxylethyl

radical (1-HER) which may undergo subsequent oxidation to acetaldehyde [17] as shown by

Figure 1.3. In addition, the overall rate of non-enzymatic wine oxidation is strongly dependent

on the reduction potential of Fe(III)/Fe(II) couple, which is discussed in detail in section

1.7.1.1.

2+ 3+ Fe2+ Fe3+ Fe Fe Ethanol OH

- - O2 OH + OH-O + H2O2 OH + O H Acetaldehyde

O Quinone

Trapping of -SH Phenolic compounds polymerization Strecker reaction with amino acids

Figure 1.3. Overview of oxidation reactions that occur in wine. Oxygen-driven formation of quinones, hydrogen peroxides consequent oxidation of ethanol to acetaldehyde and main reactions of quinones under wine conditions [9].

Overall, in wine the process of O2 reduction results in the oxidation of transition metals,

which may then subsequently oxidize polyphenols or sulfhydryls, chemical compounds

directly related to wine quality. Oxidation of these chemical components of wine has serious

consequences in the resulting wine quality and stability, and is discussed in detail in sections

1.5 and 1.6. Invariably, the oxidative spoilage of wine is strongly correlated with decreased

quality attributes and shelf stability in white wines. The non-enzymatic oxidation mechanism

also highlights the critical role of transition metals and their ability to mediate wine oxidation,

as well as participate in reactions with sulfhydryls, which is further discussed in section 1.7.

In addition, wine contains antioxidant compounds that serve as the first level of protection

against these oxidation reactions. Antioxidants are able to mitigate the extent of detrimental

oxidation reactions in wine, as observed in Figure 1.4. As noted in section 1.1, sulfur dioxide

(SO2) is present in wine, both as a product of yeast metabolism and its direct addition by the

winemaker for antioxidant and antimicrobial protection. Direct reaction between O2 and SO2 is

slow and thus not typically a driving force behind oxidation prevention in wine [9]. The

powerful antioxidant capacity of SO2 is attributed to its ability to reduce the oxidant H2O2 to

water, reconvert quinones to phenols, as well as form adducts with quinone [9]. In addition,

wines contain the antioxidant glutathione, which is present in significant amounts in wine and

is a naturally occurring by-product of grape and yeast metabolism [9]. Further discussion of

glutathione and its role in wine oxidation is discussed in section 1.4.

Quinone-GSH adducts

GSH

Fe2+ Fe3+ O OH

H2O2 H2O + O2, H R O R OH 2- - Monocatecol ortho-Quinone SO4 HSO3

- HSO3 H2O

2- - Quinone-SO2 SO4 HSO3 adducts

Figure 1.4. Proposed mechanisms illustrating SO2 and GSH antioxidant protection in wine [9].

1.4 Glutathione

Glutathione (GSH) is a tripeptide of L-glutamate, L –cysteine and glycine, and is the most abundant non-protein intracellular thiol (0.2 – 10 mM) present in mammalian and many prokaryotic organisms [18]. Its prevalence in biological systems may be attributed to the free sulfhydryl moiety of the cysteine residue, which confers unique redox and nucleophilic properties [19]. The majority (>90%) of GSH present in the cell is in its reduced form, which allows it to act as a powerful, versatile and important molecular in defense of oxidative stress

[20]. Glutathione is an important constituent of grapes, must and wine, and due to its redox active and antioxidant properties, it plays a significant role in grape and wine systems.

NH3 O H N

O2C N CO2 H

O SH

Figure 1.5. Structure of the glutathione molecule in its reduced (free thiol) form. The important functional group in terms of chemical activity is its nucleophilic cysteine thiol group.

GSH plays many physiological and biochemical roles in plants, specific to redox control, detoxification and sulfur metabolism. In 1989, GSH was first quantified in grapes, and one study analyzed the content of both berries and respective musts of 28 Vitis vinifera grape varieties and found the concentration varied from 56 to 372 µMol/kg (17 -114 mg/kg) among grape varieties [21]. Variation in the GSH concentration was not dependent on varietal alone, but was also influenced by vintage, location, and technological practices [21]. Upon ripening, 90% of

GSH is present in the reduced form, and it was found that GSH content increased at higher sugar levels, but was not influenced by berry diameter or bunch exposure[22, 23] [24] In must, the concentration of GSH is highly variable and has been reported at levels ranging from

nondetectable to 100 mg/L. In one study, GSH levels in South African juice ranged from 1.1 to

71 mg/L with correlates well with other previous studies [8] [25] [26] [27] [28]. The GSH concentration in must is influenced by several factors, including exposure to oxygen, tyrosinase activity, grape skin maceration during the pre-fermentation period and pressing [8] [25] [29].

Free-run juice, which is the majority (~60-70%) of the available juice within the grape berry that is released during the crushing process and does not require use of the press, has been characterized by having higher GSH content compared to higher press fractions [8] [29]. In one study, after one hour of skin contact in Sauvignon blanc juice, GSH concentration had decreased by up to half [8]. Additionally, only one of three juice pressings obtained at 0.4 atm had any detectable GSH remaining [8]. Another study found a correlation between reductive and oxidative treatments during winemaking and the resulting GSH level, with the reductive treatment (<0.3 mg/L dissolved O2 during pressing) resulting in the highest GSH levels and the control (1 – 1.5 mg/L dissolved O2) and oxidative (3.5 – 4 mg/L dissolved O2) resulting in significantly lower GSH levels [25].

During winemaking, contradictory results have been obtained regarding the evolution of

GSH concentration, and both increases and decreases in GSH concentrations have been observed [3] [25] [28] [29] [30] [31] [32] [33]. GSH has been implicated in many stress response mechanisms in Saccharomyces cerevisiae such as sulfur and nitrogen starvation, oxidative stress, among others, may be assimilated during alcoholic fermentation through transporters which have been characterized [34] [35]. Additionally, a transporter for GSH secretion has been characterized in S. cerevisiae [36]. From these studies, it can be suggested that yeast may be able to alter the GSH concentration during alcoholic fermentation through both uptake and secretion. Other studies have indicated that specific yeast strains result in highly variable GSH concentrations at the end of fermentation, with some strains resulting in 7-fold higher GSH

concentrations; but when selected strains were inoculated in grape juice, expected trends in the final GSH content were not confirmed [28]. The reason for the final GSH levels observed in this study remained unexplained, but it is likely linked to complex grape juice metabolism [28]. The same study showed that GSH content fluctuated during fermentation, with the degree of fluctuation dependent on the yeast strain and initial GSH content of the juice, with small but significant differences in GSH content observed for wines fermented with different yeast strains.

This suggests that not only do yeast strains differ in GSH metabolism, but also that the metabolism is influenced by the extracellular GSH content [28].

In wines, GSH levels have been observed ranging from non-detectable to 70 mg/L [27]

[28]. In one study of 28 young Sauvignon blanc wines, the GSH level was found to be 12.5 mg/L

[26]. The concentration of GSH generally decreases during wine aging [28] [31] [37] [38]. The concentration or status of glutathione in wine is an indicator or predictor of oxidation history or oxidation susceptibility [28]. In one study, Sauvignon blanc wines that were exposed to lower oxygen levels during bottle aging consistently showed higher GSH concentrations compared to wines exposed to higher levels of oxygen during storage [37]. Glutathione is an especially important compound in white wine, which is more sensitive to oxidation. The loss of glutathione, and subsequent oxidation of wine, may result in a loss of characteristic aroma, development of atypical aging characteristics and undesirable color changes [28]. In the must, glutathione traps ortho-quinones, which are formed during oxidation, to control formation of browning pigments, as shown in Figure 1.6 and discussed in greater detail in 1.4.1. Glutathione has been shown to protect various aroma compounds that are present in wine [28]. As shown by these studies, it is clear that the GSH concentration is able to change dramatically between must and wine, and its concentration is able to be manipulated by the winemaker through limiting oxidation throughout vinification and aging.

1.4.1 Role in Wine Oxidation

The role of glutathione and its associated antioxidant capacity in must and wine are key in the inhibition of browning. Browning is an oxidative process that occurs during vinification or aging of wine and is considered to be a substantial quality defect in white wines. Browning results from enzymatic oxidation and chemical oxidation. Phenols, specifically o-diphenols, are implicated in the oxidative browning in wine and further discussion can be found in 1.5.2.

Chemical oxidation, or non-enzymatic oxidation, is due to the oxidation of phenolic compounds and subsequent polymerization of the oxidation products, as well as polymerization of phenolic compounds with other wine constituents, such as acetaldehyde and glyoxylic acid which give rise to browning pigments [39]. The phenolic compounds present in wine that are most susceptible to chemical oxidation include caffeic acid and its esters, catechin, epicatechin and gallic acid [40]. A number of studies have been performed in model wine to study the mechanism and role in which glutathione inhibits chemical oxidation in wine [41, 42]. One study in model wine demonstrated that the addition of GSH in sufficient concentrations inhibits oxidative coloration by delaying the formation of carboxymethine-bridged (+)-catechin dimers

[42]. Another study showed that the observed delay was a result of the ability of GSH to form addition products with carbonyl compounds such as glyoxylic acid, and the inhibiting effect of

GSH on the formation of glyoxylic acid-derived dimers was independent of temperature (20 vs

45°C) and the presence of copper and iron [42]. Inhibition of carbonyl-derived polymerization reactions hinders the formation of the yellow xanthylium cation, an undesirable pigment which may induce color changes that are associated with a decrease in wine quality [41].

Enzymatic aging mainly occurs in the must prior to fermentation, and chemical oxidation predominantly occurs in finished wine [39]. Enzymatic oxidation is correlated to the hydroxycinnamate content of grape juice, which is the main group of phenol compounds found

in white grape juice [40] [43]. When the berry is intact, hydroxycinnamates are contained in the vacuole of the grape berry and do not come into contact with the polyphenol oxidase (PPO) enzyme that is present in the cytoplasm due to compartmentalization. Once the berries are physically crushed and cell membranes are subsequently disrupted in the presence of oxygen, hydroxycinnamates are converted by PPO to o-quinones, which are reactive electrophiles. As shown in Figure 1.6, the grape PPO converts coutaric acid to caftaric acid, which is then further oxidized to caftaric acid quinone. Glutathione contains a mercapto group which acts as an electron-rich nucleophilic center, and substitutes into the electrophilic ring of the caftaric acid quinone [44]. In the caftaric acid moiety, the vicinial dihydroxy ring is regenerated by means of a proton transfer and equivalent of an enol shift [44]. The resulting reaction product, a thioester known as 2-S-glutathionyl caftaric acid or grape reaction product (GRP) is not a substrate for further oxidation by PPO. The role of the glutathione is significant, as it traps the o-quinones that are formed by PPO in their colorless form and prevents further formation of brown pigments.

Once glutathione is depleted, the o-quinones can oxidize other flavonols, and polymerize to form browning pigments.

O H

CO2H

H O OH

HO H H

CO2H Coutaric acid O H OH O H O CO2H CO2H

H O H O OH O

HO H H HO H H PPO, O2

CO2H CO2H Caftaric acid Caftaric acid quinone

H2N OH

O GSH Nucleophile

HO O

NH HN Yellow and colorless products O

O Nucleophile O H S OH Nucleophile CO2H

H O O OH Semiquinone or quinone HO H H Oxidation O

CO2H 2-S-Glutathionyl caftaric acid Quinone

Figure 1.6. Generalized schematic explaining the formation of colored compounds in wine, and the role of GSH in the prevention of oxidation.

Upon GSH depletion, caftaric acid quinone, which is an oxidant, is able to oxidize GRP and other flavonols and be reduced back to caftaric acid. Additionally, caftaric acid quinone can react with caftaric acid and polymerize to form a reoxidizable phenol [45]. It is due to these polymerization reactions with o-quinones that leads to browning in grape juice [46]. Overall, the role of glutathione in inhibition or delay of these polymerization reactions in must and wine prevents the formation of browning pigments which are associated with decreased wine quality.

1.4.2 Impact on Aroma Compounds

Beyond the role of glutathione in preventing the oxidation of phenolic compounds in wine, it has been shown previously that the presence of glutathione prevented or slowed the loss of esters and terpenes that impart fruity, floral and positive varietal aromas in many grape varieties and their corresponding wines [28]. The loss of positive aroma compounds is thought to be due to oxidation reactions and the protective effect of glutathione was attributed to its sulfhydryl moiety which has important redox and nucleophilic potential in wine [28]. Varietal thiol compounds 4-mercapto-4-methylpenta-2-one (4MMP), 3-mercaptohexan-1-ol (3MH) and 3- mercaptohexylacetate (3MHA) are important aroma compounds that contribute to the varietal aroma of Sauvignon blanc, and are particularly susceptible to oxidation during storage. Previous studies found that the addition of glutathione prior to bottling generally resulted in wines with higher 3MHA levels after six months of bottle aging [37]. These results suggest that glutathione plays an important role in the protection of these compounds. The phenolic oxidation product o- quinone is able to react with thiols via a Michael addition reaction, and can also form peroxides through coupled reactions, which may then oxidize thiol compounds. It has been suggested that glutathione may compete with aromatic thiols to bind o-quinone, which in turn limits the loss of varietal aroma compounds in wine [28]. 1.5 Phenolics

Polyphenol and phenolic compounds are a large class of plant secondary metabolites with a diversity of structures. Phenolic compounds are classified as simple phenols (with one phenolic group) or polyphenols based on the number of phenol units in the molecule. Phenolic compounds play an important role in the quality of plant-based foods and have garnered significant interest based on their antioxidant properties. Foods such as tea, red wine and beer have very complex phenolic profiles [47]. One of the most common phenolic components in plant foods are the hydroxycinnamic acids, such as p-coumaric, caffeic and ferulic acids. These

compounds are highly reactive due to the hydroxyl group (-OH) bonded directly to the nucleophilic benzene ring. Phenols are effective radical-scavengers, which is governed by their ability to act as hydrogen or electron donating agents. Depending on their structure, phenols are classified as non-flavonoid compounds (hydroxycinnamic acids) and flavonoid compounds

(flavonols, flavones, flavanols and isoflavones), examples of which can be found in Figure 1.6

[48].

Flavonoids

Flavonols R1 Kaempferol (R1=R2=H) OH Quercetin (R1=OH, R2=H) Myricetin (R1=R2=OH)

OH O R2

OH O

1 1 Flavan-3-ols R R

OH OH

OH O OH O OH OH

OH OH

(+)-Catechin (R1=H) (+)-Epicatechin (R1=H) (+)-Gallocatechin (R1=OH) R1 (+)-Epigallocatechin (R1=OH)

OH O OH

OH OH O

OH (+)-Epicatechin gallate (R1=H) 1 (+)-Epigallocatechin gallate (R =OH) OH

Anthocyanins R1

OH Cyanidin 3-glucoside (R1=OH, R2=H) 1 2 Peonidin 3-glucoside (R =OCH3, R =H) OH O 1 2 2 Delphinidin 3-glucoside (R =R =OH) R 1 2 Petunidin 3-glucoside (R =OH, R =OCH3) 1 2 Malvidin 3-glucoside (R =R =OH3) O-Glc

Figure 1.7. Most common flavonoid compounds found in wine [39].

As shown in Figure 1.7, flavonoids have a common core structure, the flavane nucleus consisting of two benzene rings (A and B) linked by an oxygen containing pyran ring (C)

(C6C3C6). Flavonoids are differentiated by the degree of oxidation of the heterocyclic ring (C) and the hydroxylation and methylation of the –R groups, which allows for a large family of structures with differences in stability and physicochemical properties, and thus impact on organoleptic properties of wine [39].

Non-flavonoids

Derivatives of benzoic and cinnamic acid

R3 R1

CO2H

2 2 R CO2H R

R1 R3 R1 R2 R3 Benzoic acid H H H Cinnamic acid p-Hydroxybenzoic acid H OH H p-Comaric acid Protocatechuic acid OH OH H Caffeic acid Vanillic acid OCH3 OH CH Ferulic acid Gallic acid OH OH OH Syringic acid OCH3 OH OCH3 Sinapic acid

Stilbenes OH

trans-Resveratrol

Volatile Phenols

OH OH OH

H3CO H3CO OCH3

R R R

Ethylphenol (R=CH2CH3) Guaiacol (R=H) Syringol (R=H) Vinylphenol (R=CHCH2) Methylguaiacol (R=CH3) Methylsyringol (R=CH3)

Figure 1.8. Most common non-flavonoids found in wine [39].

Non-flavonoid compounds, as shown in Figure 1.8, are mainly derivatives of benzoic acid and cinnamic acid; but also contain stilbenes and stilbene glycosides, the best-known example

of which is trans-resveratrol. Non-flavonoids also contain hydrolysable tannins, which are esters of gallic acid and ellagic acid with glucose or other related sugars [39].

In grapes, the non-flavonoid compounds are found primarily in the pulp, and the flavonoid compounds are found in the skin, seed and stem. The phenolic composition of grapes and their resulting wines varies based on the varietal, growing conditions, stage in berry development as well as the reactions that occur from the moment the grapes are crushed until the beginning of alcoholic fermentation. Winemaking techniques have a significant impact on the extraction of phenolic compounds from grapes and their stability in wine [47]. Maceration, skin contact time and bottle aging are factors that determine the phenolic composition of finished wine.

1.5.1 Phenolic Compounds in Wine

Phenolic compounds are one of the most important constituents of wine, as they contribute to the organoleptic characteristics of color, astringency and flavor properties. The type and concentration of phenolics have a profound effect on the sensory attributes of wine. The most common wine flavonoids in wine are flavonols (kaempferol, quercetin and myricetin), flavan-3- ols (catechin, epicatechin and tannins) and anthocyanins (cyaniding-3-glucosides, peonidin-3- glucoside, delphinidin-3-glucoside, petunidin-3-glucoside, and malvidin-3-glucoside). Wine flavonoid concentration is strongly affected by winemaking practices such as pressing and maceration, which affect the extent of extraction from skins and especially from seeds that are rich in flavan-3-ol units. Flavan-3-ols are primarily found in the seed, skin and stem of the grape berry in monomeric, oligomeric and polymeric forms; the latter two are known as proanthocyanidins or condensed tannins. Seed tannins are typically oligomers and polymers composed of the monomeric flavan-3-ols(+)-catechin, (−)-epicatechin, and (−)-epicatechin gallate [39]. Skin tannins also contain (−)-epigallocatechin and trace amounts of (+)- gallocatechin and (−)-epigallocatechin gallate [39]. Typically, the concentrations of

proanthocyanidins or condensed tannins are in the range of 1 – 4 g/L in red wines [49]. In white wines, typical concentrations of these compounds are approximately 100 mg/L and highly dependent on pressing techniques [49]. With respect to their sensorial properties, monomeric catechins are bitter, while polymers are generally astringent [50].

The concentration of polyphenols in red wines is significantly higher than white wines, with ranges between 1 to 5 g/L for red wines and 0.2 to 0.5 g/L for white wines. The polyphenols found in white wines are mainly hydroxycinnamic acids, which are important in wine browning reactions and loss of varietal thiol aroma. The low concentration of flavonoids, such as catechin and quercetin glycosides, in white wine is also important in regards to browning reactions, with increased concentrations of flavonoids found in white wines musts that are exposed to longer skin contact times and harder pressing conditions [51].

In previous studies, it has been shown that an increase in catechin and quercetin derivatives may impact the detection threshold of varietal compounds in Sauvignon blanc, and that the presence of caffeic acid decreased the threshold of some aroma compounds [52]. The molecular interactions between phenolic compounds and volatile aroma compounds, and the resulting influence on the perceived detection thresholds, highlights the importance of total phenolic content in wine as it affects the resulting sensory attributes of wine. High levels of hydroxycinnimates were observed in the phenolic profile of wines made from free run juice, whereas high levels of flavonols were found in heavily pressed and skin contact wines [5].

Increased levels of hydroxycinnimates are correlated with the preservation of floral and fruity notes in wine [4].

1.5.2 Oxidation of phenolic compounds in wine

Phenolic compounds are primary substrates for oxidation. From a sensory perspective, controlled oxidation of red wines may be beneficial by its role in enhancing and stabilizing color

and reducing astringency; however, oxidation of white wines generally results in decreased quality [51]. As previously discussed in section 1.4.1 in regards to GSH, enzymatic browning occurs almost entirely in grape must. The likely mechanism for oxidation of phenolic compounds involves hydroxylation to the ortho-position adjacent to a hydroxyl group of phenolic substrates

(via monophenol oxidase activity) and oxidation of ortho-dihydroxybenzenes to ortho- benzoquinones (via diphenol oxidase activity), as shown in Figure 1.9.

Monophenol OH

PPO + O2

OH O Phenolic PPO + O2 species Condensation Brown Catechin, SO products polymers 2 Amino acids, R OH GSH R O proteins Monocatecol ortho-Quinone

Figure 1.9. Enzymatic browning processes observed in grape must [40].

There are several classes of enzymes that are able to catalyze these reactions, and these enzymes are classified as oxidoreductases. The most important of which are polyphenoloxidases (PPO), specifically tyrosinase and laccase. Tyrosinase is present in the grape berry and converts monophenols into catecols via oxygen incorporation, and catechol oxidation to the brown pigment melanin. Laccase is produced by molds, and catalyzes the oxidation of para-hydroquinones to para-benzoquinones. Comprehensive reviews of enzymatic oxidation reaction mechanisms occurring in grape juice and must are covered elsewhere [51].

Enzymatic reactions are the focus of a considerable amount of research with the ultimate goal to improve wine quality and stability. Upon bottling, enzymatic action ceases, yet the non- enzymatic, chemical reactions that occur during aging are able to continue to cause significant

changes in the chemical composition of wine. The reaction products of enzymatic oxidation reactions are important in the scope of non-enzymatic oxidation reactions in that both reactions produce similar by-products, quinones. The mechanism for non-enzymatic reactions occurring post-fermentation is presented in detail in section 1.3. 1.6 Volatile Sulfidic Compounds in Wine

Volatile sulfidic compounds (VSCs) are a group of sulfur-containing compounds that have a significant impact on the aroma and sensory attributes of wine. The chemical structures of the

VSC dictate the beneficial or detrimental contribution to overall wine aroma. Volatile sulfidic compounds in wine have been noted to be a “double edged sword” [53], as they contribute to both pleasant and unpleasant aromas. VSCs containing the sulfhydryl moiety (-SH) are of significant interest, as they have relatively low odor detection thresholds and the sulfurous aroma in wine is generally attributed to the sulfhydryl-containing compounds.

Many of the sulfur-containing aroma compounds that are present in wine due to viticultural practices, such as maceration, remain redox-active during wine aging. These sulfur-containing compounds can participate in one and two electron transfer, radical processes and exchange reactions, which are observed during non-enzymatic oxidation reactions [15. Because of the sulfhydryl moiety, VSCs are also able to participate in redox reactions with other wine constituents, specifically transition metals, as well as form metal complexes. In addition, sulhydryls are nucelophiles, and their presence can impact the reaction rate of oxidation reactions in wine [54].

Beyond maceration, another important processing step in winemaking that can dramatically affect the oxidative stability of desirable aroma compounds is copper fining. Copper fining is the standard method of removing undesirable thiols (such as H2S, MeSH, EtSH) from wine, but recent studies have shown that the residual copper is redox active and can oxidize beneficial

wine components. The redox mediated non-enzymatic oxidation reactions that occur in wine are associated with the loss and/or formation of VSCs post-bottling. Copper fining and subsequent reactions between VSCs and metals are discussed in greater detail in sections 1.7.3 and 1.7.4.

The important differences between beneficial and undesirable thiols is discussed in detail the following sections.

1.6.1 Fermentive Thiols

The volatile sulfidic compounds H2S, methanthiol (MeSH) and ethanthiol (EtSH) contribute to unpleasant aromas in wine, and are known as fermentive thiols, examples of which can be found in Table 1.1.

Table 1.1: Structure and associated sensory descriptor of various fermentation-derived thiol compounds.

Compound Structure Sensory Descriptor

Hydrogen sulfide H-S-H Rotten egg

Methanethiol H3C-SH Cooked cabbage

Dimethyl sulfide H3C-S-CH3 Cabbage

Dimethyl disulfide H3C-S-S-CH3 Cauliflower

Methyl thioesters O Cooked cauliflower Cheesy Chives R SCH3

These thiol compounds are responsible for “reductive” sulfidic off-odors such as rotten egg, sewage, and burnt rubber, and are considered defects. The fermentive thiols arise during alcoholic fermentation by the yeast Saccharomyces cerevisiae, with the resulting concentration in finished wine being dependent on the nutrient status of the fermentation, yeast strain, and

fermentation conditions [55] [56] [57] [58] [59]. H2S is a natural by-product of the sulfate reduction pathway in yeast, acting as an intermediate for sulfur-containing amino acid synthesis

[60]. Excess production during fermentation can lead to the formation of methanethiol, ethanethiol, as well as other unpleasant sulfur-containing compounds dimethylsulfide (DMS) and dimethyl disulfide (DMDS), which aromas have been described as rotten cabbage or canned vegetables [60] [61] [62] [63] [64]. These volatile sulfidic compounds have odor detection thresholds at the microgram per liter level [65].

1.6.2 Varietal Thiols

The thiol compounds 4-mercapto-4-methylpenta-2-one (4MMP), 3-mercaptohexan-1-ol

(3MH, also known as 3-sulfanylhexan-1-ol, 3SH) and 3-mercaptohexylacetate (3MHA) have been identified as contributing the pleasant aromas such as grapefruit, passionfruit and blackcurrant in wine [66] [67] [68], which can be found in Table 1.2

Table 1.2: Structures and associated sensory descriptor of various of varietal thiols.

Compound Structure Sensory Descriptor

SH Passionfruit Grapefruit 3-mercaptohexan-1-ol (3MH) Guava Box hedge H3C OH

Passionfruit SH CH 3 Grapefruit 3-mercaptohexylacetate (3MHA) Gooseberry Guava H3C O O Box hedge

CH3 Passionfruit Grapefruit 4-mercapto-4-methyl-pentan-2-one (4MMP) H3C Gooseberry O Guava HS Box hedge CH 3

The compounds 4-mercapto-4-methylpenta-2-one (4MMP), 3-mercaptohexan-1-ol (3MH) and 3-mercaptohexylacetate (3MHA) are not present in grapes as free thiols but are released

during fermentation through the action of yeast from non-volatile, grape-derived precursors [28].

The precursors have been identified as cysteinylated and glutathionalyted molecules: S-2-

(hexan-1-ol)-L-cysteine (Cys-3MH), S-3-(hexan-1-ol)-glutathione (Glut-3MH), 4-(4- methylpentan-2-one)-L-cysteine (Cys-4MMP) and 4-S-glutathionyl-4-methylpentan-2-one (Glut-

4MMP) [28]. These sulfur-containing aroma compounds are known as varietal thiols, as they are responsible for the characteristic aroma of certain grape varieties, such as Sauvignon blanc.

The odor detection threshold for these varietal thiols is in the nanogram per liter concentration level. Many of the non-enzymatic oxidation reactions that occur in wine may be responsible for the loss of the pleasant varietal aromas 3-sulfanylhexan-1-ol (3SH) and 4-methyl-4- sulfaylpentan-2-one (4MSP) [69]. 1.7 Importance of Transition Metals to Non-Enzymatic Wine

Oxidation

Transition metals are known to catalyze redox reactions in wine [12]. Most importantly, under wine conditions, transition metals play a critical role in non-enzymatic oxidation reactions; the mechanism of which is described in section 1.3. The presence of transition metals is necessary to drive the oxidation of wine constituents, such as polyphenols, ethanol and sulfhydryl compounds forward [12] [54] [15] [70]. Previous studies have shown that wine oxidation can be slowed and eventually stopped in wine when iron and copper are removed using potassium ferrocyanide [71]. Beyond the redox cycling of transition metals, in particular Fe and Cu, transition metals and sulfhydryls are able to form ionic bonds. Bonding between sulfhydryls and transition metals results in metal sulfides and metal thiol complexes, which have serious implications on the ability to control and predict sulfhydryl loss and regeneration under

wine conditions, especially as it relates to copper fining. The relevance of two transition metals, iron and copper, to wine oxidation is discussed in the following sections.

1.7.1 Iron

Iron is typically present in wine in concentrations between 1 and 6 mg/L [71] [72], however concentrations as high as 9 mg/L observed [73]. The most important role of iron in wine is its ability to catalyze reactions of wine constituents. Iron has been a focus in the study of wine chemistry for its role as a mediator involving oxygen, polyphenols and sulfites. It has been shown that the addition of Fe to wine accelerates its oxidation, while its removal slows oxidation

[74]. Due to the electronic configuration of oxygen, its direct reaction with compounds having paired electrons such as phenolic compounds and sulfite is prevented [12]. Oxygen is reduced by Fe(II) to produce hydrogen peroxide, which can be further reduced by Fe(II) to hydroxyl radicals. These radicals will then begin to rapidly oxidize ethanol unless quenched by sulfite

[16]. The oxidation of Fe(II) results in the production of Fe(III), which is able to oxidize polyphenols with the presence of a nucleophile such as sulfite, thus regenerating Fe(II). Sulfite participates in this reaction by the removal of quinones through the formation of adducts or reduction back to the original polyphenol [75] [76]. Thus, wine oxidation reactions are mediated by redox cycling of Fe(III)/Fe(II), a mechanism first proposed in 1931 [77].

The overall rate of non-enzymatic wine oxidation depends significantly upon the reduction potential of the Fe(III)/Fe(II) couple, which is lowered by tartaric acid [12] [14] [16] [76]. Lowering the reduction potential results in greater reducing power; thus, a low reduction potential of the

Fe(III)/Fe(II) couple allows O2 to be more easily reduced to H2O2. Additionally, a low

Fe(III)/Fe(II) reduction potential facilitates H2O2 reduction to hydroxyl radicals through the

Fenton reaction. As Fe(II) is oxidized, the resulting Fe(III) that is formed is quickly reduced to

Fe(II) when sulfite and phenolics are present, both of which are abundant wine constituents [16].

It has been suggested that the majority of free Fe in wine is present as Fe(II), although much of the Fe is bound to the organic molecules in wine, such as tartrate [78] and tannins [79]. It has recently been confirmed that Fe(II) is the major species in wine due to the low pH and high concentration of phenolic compounds [80].

1.7.1.1 Fe(II) Concentration and Redox Status

Reduction potentials have often used to determine the redox status of wine. It has recently been observed that the typical methods for determination of reduction potential instead produced measurements that were generated by the oxidation of ethanol on platinum electrodes, and not by the redox processes involved in oxidation reactions in wine [81] [82]. A new method developed by Danilewicz leverages the correlation between redox status and

Fe(III):Fe(II) ratio present in wine to use as an alternative technique to estimate the overall redox status of wine. Fe redox cycles and the [Fe(III)]:[Fe(II)] ratio are dependent on the rates of

Fe(II) oxidation and Fe(III) reduction. Fe(II) dominates under reducing conditions, but upon increasing oxygen exposure, the conversion of Fe to the Fe(III) species also increases. Fe(II) depends primarily on oxygen, Fe and Cu concentrations. Fe(III) reduction depends on the concentration and reactivity of polyphenols, and sulfite concentration [80]. The [Fe(III)]:[Fe(II)] ratio, at equilibrium, will depend on the extent of oxygen exposure of the wine, and the relative rate of removal by phenolic compounds [80], as shown by Figure 1.10. Low Fe(III)]:[Fe(II)] ratios indicate the phenolic compounds present in wine have the ability to remove the O2 that enters the system, maintaining a reductive state. Higher ratios indicate that a wine is undergoing oxidation at faster rates.

H+ (III) 2+ (III) 2+ Fe(II) + O2 [Fe -O2] [Fe -O2] Fe(III) + HO2

Fe(III) Fe(II)

Fe(II) + Fe(III) + O2 Fe(III)O-OFe(III)

2H+ H2O2 + 2 Fe(III)

Figure 1.10. Relationship between the Fe(II):Fe(III) ratio and redox status. Proposed mechanism by

Danilewicz for the interaction of O2 with Fe in wine and the competition of Fe(III) and Fe(II) for the Fe(III)-

2+ superoxide complex ([Fe(III)-O2•] ) [83].

Previous studies have investigated the Fe(III)]:[Fe(II)] ratio using spectrophotometric methods with Fe(II)-selective ligands [71] [72]. However, the exposure to oxygen was not controlled in these studies and the composition changed, which in effect changes the

Fe(III)]:[Fe(II)] ratio. Additionally, the use of Fe(II)-selective ligands may cause a rapid increase in Fe(II) concentration, as they facilitate Fe(II) reduction. The newly proposed method by

Danilewicz uses 2-(5-Bromo-pyridylazo)-5-[N-propyl-N-(3-sulfopropyl)amino] phenol disodium salt hydrate (5-Bromo-PAPs, or Br-PAPs). Br-PAPs forms a Fe(II) complex with absorption at

740 nm, outside of the red wine absorption range, and is water soluble [83]. This method allows the determination of redox status of wine, and is particularly useful to determine the extent of oxidation during wine aging.

1.7.2 Copper

Copper is a minor component of all agricultural commodities – and therefore all foods – and grapes are no exception. Exogenous Cu may be also be introduced to grapes from Cu-based fungicide treatments (e.g., copper sulfate) in the vineyard [84] [85]. The Cu concentration present in grape juice decreases during fermentation, due to adsorption of Cu and yeast cell

removal [85] [86]. The major source of copper in white wine results from its deliberate addition to remove sulfidic off-odors. The legal limit for Cu concentration in finished wine is regulated internationally, and varies between 0.5 – 1.0 mg/L, but concentrations as high as 10 mg/L have been observed [87].

1.7.3 Copper Fining

The addition of copper to wine, in the form of its sulfate or citrate salt, is a process known as copper fining and is a common practice among winemakers. The copper fining process is intended to target the removal of H2S, MeSH and EtSH which are believed to be the primary cause behind the sulfidic off-odors. The reaction between H2S and Cu(II) is thought to result in a highly insoluble (6.3 x 10-36 (mol/L)2) colloidal CuS precipitate, which could then be removed from wine by filtration or racking [88]. The reaction is shown below in Figure 1.11.

H S + Cu(II) + CuS (s) 2 [Cu-SH] (aq)

Figure 1.11. Removal of H2S by the addition of Cu (II), resulting in the formation of insoluble CuS.

In actual practice, the straightforward reaction between H2S and Cu(II) and formation of a CuS(s) precipitate is much more complex, and there are many components in wine that prevent simple

CuS(s) formation.

The mechanism of copper fining remains poorly understood, and there appear to be numerous disadvantages of this method according to a growing body of recent reports. The use of Cu(II) to remove H2S is nondiscriminatory and can react with both reductive fermentive thiols and the varietal thiols that provide both the desirable and undesirable aromas [88]. As previously discussed, the potential impact of residual (i.e. effectively soluble) Cu in wine and its role in oxidation reactions is significant. Removal of beneficial thiols would result in a loss of the

varietal character of the wine [37]. Copper fining is ineffective at removing other sulfur- containing aroma compounds such as disulfides, thioacetates and cyclic sulfur compounds which also contribute unpleasant off-odors, due to the absence of a free thiol group [15].

Nonvolatile thiols, which are present in large molar excess to the Cu(II) added during the fining process, and also greatly exceed the concentration of H2S present in the wine, could compete for reaction with Cu(II) [15]. Additionally, the practical difficulty of removing the CuS precipitate in wine has been demonstrated, showing filtration to be ineffective and that the precipitate may not be observed [87] [89]. The residual copper that remains in the wine post-bottling is then able to participate in redox-mediated reactions.

1.7.4 Reactions of Copper in Wine

Residual copper in wine has been linked to oxidative and reductive spoilage of wine [37] [90]

[91]. Evidence has been shown in white wines treated with Cu(II) that the H2S aroma appears to return during storage [92]. The recent shift to the widespread use of screwcap closures is thought to be a contributing factor, as the closure mediates the ingress of oxygen into the bottle

[87]. Screwcaps allow very little oxygen ingress (<0.5mg/L per year), which creates a very reductive environment [91]. The reductive environment favors the release of H2S and other low molecular weight volatile sulfur compounds (VSCs). This has been shown in a study in

Sauvignon blanc in which wines with low oxygen conditions and high concentration of Cu(II) (0.3 mg/L vs. 0.1 mg/L) generated the highest concentration of H2S after a 6-month storage period

[37]. Some studies have shown that wine may contain precursors that are able to produce H2S and methanethiol post-bottling, yet the causative mechanism is unclear [9] [93]. The Strecker degradation of cysteine has been reported to result in the formation of H2S, and it has been suggested that direct reduction of sulfate or sulfite may form H2S post-bottling [91] [94].

Additionally, it has been reported that thiols are able form complexes with Cu(II), and the bound

forms are reversible [95] [96]. These findings are significant, and together indicate that Cu(II) is a participant in troublesome reactions to liberate or generate H2S and thiols post-bottling.

1.7.5 Release of Metal Sulfide and Metal Thiol Complexes

Upon bottling, many sulfur compounds present in wine remain redox active during the aging process, and can participate in reactions such as one and two electron transfer, radical processes and exchange [15, 70]. Compounds containing sulfhydryl moieties are also able to bind to transition metals, in many cases forming stable complexes that are frequently observed in living and geochemical systems and perform a critical redox role. Many of the thiols which are key in predicting and improving finished wine quality are the result of enzymatic action occurring during grape maturation and grape juice/must fermentation. In the post-bottling environment, enzymatic action is does not occur; however, non-enzymatic reactions catalyzed by transition metals liberated from metal complexes may lead to significant changes in the finished wine over time. The proposed mechanism for Cu-thiol complex formation by Kreitman et al is shown below in Figure 1.12.

RS Cu(I)-SR 4RSH + 2Cu(II) 2[RS-Cu(II)-SR] RS-(I)Cu SR

Cu(I) R

Aggregation SR SH SR RS Cu(I)-SR 2 RS-Cu(II) Cu(I) Cu(I) Cu(I) RS-(I)Cu SR RS SR RSSR

Figure 1.12. Proposed mechanism for the initial reaction of thiols with Cu(II) and Cu(I)-thiol complex formation [15].

It has been shown that a major factor in the release or seemingly “reappearance” of H2S and methanethiol is due to the dissociation of bound metal species [96]. Because metal sulfides are non-volatile and odorless, the wine may appear to be free of faults until dissociation of the complex occurs. Results from these studies indicate that approximately 94% of H2S and 47% of

MeSH are effectively bound to metal under wine conditions [95] [96]. Although many metals can form these complexes with H2S, only Cu(II) is able to fully bind and release H2S [95]. A major driving force for the manifestation of these reactions is the reductive and anaerobic conditions that occur post-bottling. Under aerobic conditions, H2S loss may occur due to reactions with quinones formed through oxidation reactions of wine. One study found that over a period of 18 months, free H2S concentration increased over time while total H2S concentration did not change [96].

Recent studies have attempted to elucidate the mechanisms involved in the reappearance of H2S/thiols under reductive conditions. One study has proposed three classes of precursors that are implicated in the reappearance sulfhydryls in wine [15]. The first class is metal- sulfhydryl complexes that are formed upon the addition of Cu(II) to wine, which are released under anaerobic conditions. The second is asymmetrical disulfides, polysulfanes, and

(di)organopolysulfanes formed from the oxidation of sulfhydryls upon Cu(II) addition or pesticide exchange; these may be released through mechanisms such as thiol-disulfide exchange, sulfitolysis or other related reactions. The third is S-alkyl thioacetates that are formed primarily during fermentation. Clearly, Cu(II) plays a significant role in the cause of this common wine fault, and its direct addition to wine must be avoided or minimized for prevention of the reappearance of reductive off-aromas such as H2S. This situation argues for the development of new winemaking techniques that allow for H2S removal without the inadvertent introduction of

Cu(II) that can remain in wine.

1.7.6 Current Methods for Copper Removal in Wine

Few novel approaches have been suggested or published in the current literature for the removal of copper from wine. A recent study investigated non-polar adsorbent PVI-PVP

(polyvinylimidazole-polyvinylpyrrolidone) co-polymers for the removal of heavy metals in wine, specifically Cu, Fe, Pb, Cd and Al [97]. These methods proved to be effective when applied to the wine, with minor effects on phenolic composition, but resulted in a decrease in total acidity and increase in pH, which may have negative impacts on the sensory attributes of wine.

Another current recent study investigated the use of cation-exchange resins. This study found the cation-exchange resins resulted in successful removal of Fe and Cu, yet significant losses were observed in the organoleptic characteristics of the treated wines, and the authors concluded neither treatment investigated was of practical value [98]. Another treatment for the removal of copper in wine involves the use of potassium ferrocyanide, also called “blue fining,” which requires the direct addition of the compound to wine. Although potassium ferrocyanide is not poisonous itself, the addition to grape juice or wine may cause it to hydrolyze and form hydrocyanic acid, which is poisonous [99]. In the countries in which it is legal, this treatment is regulated and monitored under very strict control because of the associated hazards [99]. The results of these studies demonstrate that no practical or effective method currently exists that is able to effectively remove copper from wine, without causing undesirable changes in the concentration of other wine components. This further underlines the need to devise innovative winemaking techniques which effectively remove H2S and thiols, without the negative consequences of residual copper remaining in the wine.

1.7.7 Bound Cu(II) Fining Techniques

Cu(II) salts are extremely effective in the removal of sulfhydryls, but the resulting accumulation of residual copper and oxidation products released post-bottling is detrimental to

wine quality and stability. The method of immobilized or bound Cu (II) fining for the removal of

VSCs in wine shows promise as a likely contender for the replacement of traditional copper fining methods. Immobilized Cu(II) fining exploits the reaction potential and affinity between

Cu(II) and VSCs under wine conditions and subsequent formation of stable Cu(II)-sulfide complexes. Because the Cu(II) species is immobilized and bound to an inert substrate, it may be easily removed from wine post-fining with the Cu(II)-sulfide interactions intact, resulting in both the removal of VSCs and without leaving residual Cu behind after fining. This method has the potential to significantly improve the oxidative stability of wine post-bottling.

1.7.8 Potential for Proteins to Remove Copper in Wine

Proteins may provide an additional novel pathway for the removal of Cu in wine. The use of proteins to reduce copper concentration in wines, especially after a Cu fining operation, may improve the oxidative stability of the finished wine. Fining proteins are thought to successfully remove molecules from wine through interactions between their charged amino acid residues and electrostatic attraction to these molecules. These interactions could be exploited for removal of Cu and Cu-sulfide complexes. The wide variety and complexity of amino acid residues in fining proteins may similarly participate in a multitude of metal-binding mechanisms, such as ion exchange, complexation, coordination and microprecipitation in order to remove residual copper and associated complexes [100].

Traditionally, proteins may be added to certain wine varieties as a fining agent to soften or reduce the wine’s astringency, or reduce color by the precipitation of polymeric phenols and tannins. Most of the available fining proteins are by-products from other industries and are relatively inexpensive. The four major proteins used in wine applications are isinglass, gelatin, casein and albumin [89]. In recent years, other proteins such as pea protein, wheat gluten and patatin, as well as synthetic polymers such as polyvinylpolypyrrolidone (PVPP), have been

evaluated as fining agents [101] [102] [103]. Newer fining techniques, such as the use of plant proteins and synthetic materials have been studied for the removal of tannins and polyphenol compounds [101]. The benefit of using fining proteins to remove the excess copper is centered around their prevalent and widespread use in the winemaking industry; fining proteins are relatively inexpensive and have established protocols for use in the food industry [88]. The ability to utilize fining proteins for selective copper removal in wine would result in a low-cost, innovative and easy to implement solution for the reduction in oxidative reactions resulting from residual copper catalysis in wine. 1.8 Purpose and Significance

Pennsylvania is the United States of America’s fifth largest producer of grapes, and contains over 14,000 acres of vineyards. In 2016, the total retail value of wine sales in the US was valued at $60 billion dollars [104]. In the fiscal year 2014 – 2015, the wine sales in Pennsylvania reached $1.09 billion [105]. Between the years of 2007 and 2012, the wine export industry in the

Pennsylvania grew from $1 million to $9 million, and Pennsylvania was the fastest growing wine exporting state in the country. Wine is an important agricultural commodity in the

Commonwealth, and any winemaking technique which enhances quality is of great benefit to the winemaker and consumer.

Across the US and globally, winemakers employ many practices to contribute to wine quality and ensure a desirable product for consumers. An essential aspect of winemaking includes the prevention of oxidation during vinification, post-fermentation and aging. Addressing the oxidation of wine using novel methods, such as maceration techniques, fining with bound Cu(II) and protein fining for the removal of Cu are of significant interest to the winemaker and wine researcher. The purpose of these novel methods is to prevent oxidation through greater extraction and preservation of grape and wine constituents with antioxidant and redox activity,

such as phenols and glutathione, and to remove excess levels of residual copper that lead to undesirable wine qualities. Because wine quality and salability are correlated with freshness and maintenance of a wine’s aroma profile, the success of these techniques is essential to the continued growth of the wine industry. 1.9 Hypothesis and Objectives

The overall aim of this thesis is to evaluate novel vinification techniques that can improve wine quality with respect to overall oxidative stability. I hypothesize that novel vinification techniques, specifically maceration treatments and alternative methods of copper fining, will improve wine quality with respect to overall oxidative stability in Pennsylvania wines.

The test this hypothesis, the following objectives were established:

1. Determine if and how the maceration techniques of cryogenic maceration and

extended skin contact affect the oxidative stability of white wines made from hybrid

grapes;

2. Evaluate the use of bound Cu(II) materials in place of traditional copper fining to

remove H2S and thiols without contributing to the final Cu concentration in the

finished wine, thus increasing the oxidative stability of the wine;

3. Investigate the use of protein fining after traditional copper fining, as a means to

remove the Cu(II) which is introducing during the copper fining process.

Chapter 2

Effect of Maceration Techniques on White

Wine Quality Made from Interspecific Hybrid

Grapes (Vitis ssp.)

2.1 Abstract

Cayuga and Traminette are versatile interspecific white fleshed hybrid grape varieties that yield white wines which, as with all wines, vary in quality attributes depending on vinification techniques. Phenolic compounds, glutathione and other redox active compounds extracted from the grape have a significant impact on the wine’s ability to mitigate deleterious oxidation reactions that may occur. These hybrid grape varieties were chosen to evaluate two novel maceration techniques for white winemaking, cryogenic maceration and extended skin contact.

The treatment effect on the resulting phenolic content, antioxidant capacity, glutathione concentration and redox status of wine was determined in order to evaluate quantitative measures of overall quality and stability. In Cayuga and Traminette wines, extended skin contact and cryogenic maceration resulted in significantly increased Folin-Ciocalteu phenolic content over control wines. Antioxidant capacity, as measured by DPPH radical scavenging capacity, was significantly increased in extended skin contact over control wines. Extended skin contact treatment resulted in significantly decreased glutathione concentration in both Cayuga

and Traminette wines. CIE-LAB color values indicated that Cayuga extended skin contact wine was significantly darker and more orange in color than cryogenic maceration and control treatments. Overall, the quality parameters of the extended skin contact wines were decreased compared to the control. The quality parameters of the cryogenically treated wines were maintained or increased compared to the control, indicating these maceration techniques may be a viable method for the production of antioxidant enhanced, high quality white hybrid wines. 2.2 Introduction

Among the hybrid grape varieties used to produce high quality white wines, several are grown in Pennsylvania and are of tremendous economic value to the Commonwealth’s wine industry [106]. The hybrid grape variety Cayuga White was developed by Cornell in 1972, and has been shown to be an extremely productive and disease resistant variety that is suitable to be grown in the Northeastern climates [107].The grape skin has been described as resistant to cracking and its flesh as meaty and somewhat astringent [107]. It is a result of a cross between

Seyve-Villard (also known as Seyval, a high-quality white French hybrid) and Schuyler. Schuyler is a cross between Zinfandel (V. vinifera) and Ontario (white American-type cross breed). The complex characteristic attributes of Cayuga wine appear to be the result of a combination of the more desirable characteristics of its progenitors. Flavors associated with Cayuga wines are dependent on vinification techniques and ripeness at harvest. Typically, this variety has been known to produce highly quality wines with fruity aromas. The fruity aromas of Cayuga range from bright and crisp to more assertive, forward fruit flavors with hints of Vitis labrusca and

Muscat, as the ripeness progresses. As these wines age, the V. labrusca and Muscat flavors have been shown to manifest more prominently.

The Gewürztraminer hybrid grape variety Traminette was released by Cornell in 1996, and

produces high quality wines with varietal characteristics similar to its parents. Its grapes have been shown to have good balance between sugar, acid and pH ideal for winemaking. Because 40

the vine has greater cold tolerance and disease resistance than its Gewürztraminer parent, it is

a suitable wine grape to be grown in the cooler Northeastern climate of Pennsylvania. Previous

work at Cornell has recommended the must be given a 24 to 48 hour duration of skin contact

time at 5°C with 50 mg/L SO2 in order to optimize flavor expression [108]. Traminette wines

made with extended skin contact techniques have strong spice and floral aromas, full structure

and long aftertaste. Traminette wine has been described as different from its vinifera parent in

structure and mouthfeel, due to the absence of strong fresh ground spice flavors and phenolic

bitterness typical of a ripe Gewürztraminer [108]. With some skin contact during vinification,

Traminette results in aromas more similar to Gewürztraminer [108]. If appropriately monitored,

Traminette grapes vinified using skin contact techniques do not typically result in wines with

objectionable bitterness or high pH as seen with other varieties. It has been observed that

longer skin contact times may result in a shift of the typical floral and spicy Gewürztraminer

flavors toward Muscat-like flavors [108]. Typical dry Traminette wines have been described as

having nice texture and spice feel [108]. The conventional grape juice parameters of TSS, TA

and pH for both Cayuga and Traminette varieties can be found in Table 2.1 below.

Table 2.1: Juice soluble solids, wine pH and acidity for Traminette and Cayuga White grape varieties

grown at two New York Locations from Cornell University.

Soluble Solids (°Brix) Total Acidity (g/L tartaric acid) pH

Cultivar Location Avg Min Max Avg Min Max Avg Min Max

Traminette* Geneva 20.10 17.10 23.00 10.10 6.30 12.80 2.96 2.90 3.20

Cayuga** Geneva 18.90 14.30 22.40 7.90 5.50 11.00 3.26 3.00 3.33

Traminette*** Fredonia 19.70 17.90 23.40 10.00 5.00 15.00 3.10 2.90 3.20

*Wine data for Traminette: Soluble solids based on 23 years (1972-75, 1977-95); pH data based on 11 years (1982-86, 1988- 89, 1991, 1993-95); total acidity based on 19 years (1972-75, 1977-82, 1984, 1986-89, 1991, 1993-95). **Wine data for Cayuga White: Soluble solids based on 1- years (1975-1983 and 1986); pH data based on 2 years (1982, 1983); total acidity based on 7 years (1976 -77, 1979-82, 1986). ***Wine data for Traminette (Fredonia) based on 1990-93 data.

French hybrid grapes are economically important to Pennsylvania and the grape industry in the Northeastern United States, and because these hybrids are not as widely studied as vinifera varieties, is important to understand the impacts of various vinification techniques on resulting wine quality and stability that can be used by the winemaker. Additionally, previous studies have shown significant differences between hybrid grapes and European grapes, and it is important to investigate these differences and how they affect wine quality [2].

White wines are typically low in phenolic content, due to both white grape composition and standard white winemaking techniques that limit juice and pomace contact, resulting in less antioxidant capacity, and consequently, less protection from reactive oxygen species in finished wines. However, white wine quality typically benefits from limiting oxidation, and the prevention of oxidation during vinification is extremely important to the winemaker. The mitigation of deleterious oxidation reactions aids in the aging process, quality preservation and overall stability of white wines. Previous research shows that an increase in phenolic compounds and antioxidant capacity contribute to beneficial sensory attributes of wines, such as mouthfeel and flavor [5].

Other than increasing the endogenous antioxidant capacity of a wine through processing, the only tools that winemakers currently have for limiting white wine oxidation is through the use of exogenous sulfur dioxide (SO2) and/or selecting bottle closures with extremely low oxygen transmission rates (OTR). Both of these approaches are potentially problematic: high levels of added sulfur dioxide can mask various beneficial aroma active compounds in varietal white wines, can elicit asthmatic responses in sensitized individuals, and cannot exceed 350 mg/L

(total SO2) according to U.S. law (27 CFR 4.22(b)(1)). With respect to low OTR bottle closures and packing systems, wines stored under extreme anoxic conditions can develop “reduced” character, most likely due to the dissociation of bound primary thiols and H2S [15].

Maceration is a technique that allows the phenolic components of the grape to be extracted from the pomace fraction (i.e., skins and seeds) into the juice fraction, which results in increased antioxidant capacity of the resulting pressed juice and, ultimately, the finished wine. In standard white vinifera winemaking, this process is avoided or minimized because, in many cases, it results in wines with atypical quality attributes. If maceration were to be performed on these varieties, the resulting finished wine may be bitter and astringent, with off colors and flavors not typical of their varietal characteristics. Due to the delicate balance of quality parameters in white wine making, it is important to control the maceration process as to maximize antioxidant capacity while minimizing undesirable sensory attributes. Thus far, with respect to current literature and recent studies, the effect of maceration techniques on the enhancement of quality parameters of white wines has only been conducted in vinifera varieties. As shown in previous work, hybrid grapes have significant and important differences in composition compared to vinifera; especially due to phenolic chemistry, and it is unknown how hybrid grapes will respond to these treatments [2, 109].

Extended skin contact is a commonly employed maceration technique used in red wine

[110]. Red wines typically undergo alcoholic fermentation with long skin contact times. This process results in quality attributes characteristic of red wine: deeper in color, higher antioxidant capacity and more astringent. Another maceration technique that has recently been performed in white wines is cryogenic maceration. In recent studies, cryogenic maceration was shown to significantly increase phenolic compounds and antioxidant capacity while preserving sensory attributes closely related to the control [4, 5]. These two methods were applied to the Cayuga and Traminette grapes and the resulting quality and stability parameters were investigated. 2.3 Materials and Methods

2.3.1 Chemicals

Folin-Ciocalteu reagent (2N), Gallic Acid, Trolox, 2,2-diphenyl-1-picrylhydrazyl (DPPH•),

Sodium carbonate 2-(5-Bromo-pyridylazo)-5-[N-propyl-N-(3-sulfopropyl)amino] phenol disodium salt hydrate were purchased from Sigma-Aldrich (St. Louis, MO). Water was purified to 18.2W using a Millipore Q-Plus system (Millipore Corp, Bedford, MA). The chemicals and solvents used were of analytical or HPLC grade. All solutions were prepared volumetrically using Milli-Q water unless otherwise noted.

2.3.2 Maceration Treatments

Must and juice of hand harvested Traminette (30 September 2017) and Cayuga (4 October

2017) were obtained from Happy Valley Vineyard and Winery (State College, PA) during the crushing/destemming and immediately following pressing operations.

2.3.2.1 Cryogenic Maceration

Cryogenic maceration (CM) treatment occurred immediately upon collection of must, directly from the crusher/destemmer hose, on site at Happy Valley Vineyard and Winery. Prior to collection, 50 mg/L SO2 in the form of potassium metabisulfite (KMBS) was added to each empty Nalgene container. Grape must was transferred by pump into six sanitized 10-gallon open-top, low density polyethylene fermentation bins (Nalgene Nunc International, Waltham,

MA) to yield approximately 5 – 7 gallons of must per bin. Approximately 10 lbs of dry ice was added within seconds upon transfer of must to each bin, where it was quickly stirred and immersed into the must, and each bin was covered with a polyethylene lid. As CO2 evolved from the must, dry ice was periodically added to ensure the must temperature continued to drop during the treatment period. The periodic additions of dry ice over fifteen minutes resulted in a total amount of 30 lbs of dry ice added to each bin for the cryogenic treatment. Must temperature was monitored using an electronic K-type thermocouple (Fluke Corporation,

Everett, WA) for the duration of the dry ice addition until which time the must temperature reached -4°C and the must was observed to be in a semi-solid state. 44

2.3.2.2 Control

Juice for control (C) replicates was collected directly from stainless steel fermentation tanks into four sanitized 5-gallon glass carboys. The collection of juice occurred concurrently with the pressing operation.

2.3.2.3 Extended Skin Contact

Must for extended skin contact ESC replicates was collected into four sanitized 5-gallon open-top, low density polyethylene fermentation bins (Nalgene Nunc International, Waltham,

MA) following the same procedure as noted above for the cryogenic maceration replicates, with the exception of the dry ice addition. Similarly, 50 mg/L SO2 in the form of potassium metabisulfite (KMBS) was added to each empty Nalgene container prior to must collection.

2.3.3 Vinification

A process flow diagram of the treatment and vinification procedure can be found below in

Figure 2.1.

Grapes

Crush/Destem CM ESC Add dry ice to must Collect must C Freeze must at -20°C overnight Alcoholic Press Fermentation Allow must to thaw Press Transfer juice to until -1 - 4°C bin/carboys

Cold Settling, 24h at 4°C

Rack

Alcoholic Fermentation

Cold Stabilization

Bottling

Figure 2.1 Process Flow Diagram of Maceration Treatments.

Must, juice and semi-frozen must were transported to the Department of Food Science’s Wet

Pilot Plant at the Pennsylvania State University (University Park, PA) within 1 hour of processing at Happy Valley Vineyard and Winery. For all treatments, juice samples (50 mL) were removed from each replicate for TSS (°Brix), pH, and titratable acidity. An additional sample aliquot (50 mL) was collected and frozen at -80°C until additional analysis could be performed. For control replicates, juice was treated with pectic enzyme (2 g/hL Lallzyme C) and 50 mg/L SO2, and stored at 3°C for 24 hours for settling. The control replicates were racked into clean carboys prior to inoculation. Extended skin contact replicates were inoculated on the same day as must 46

collection following juice sample collection. Extended skin contact took place over four days prior to press. No acid adjustment or chaptalization was performed on either varietal.

Cryogenic maceration replicates were placed into a walk-in freezer at -20°C overnight (16 hours). The following morning, the cryogenic maceration replicates were removed and allowed to thaw at ambient temperature prior to pressing. It was observed that the cryogenic maceration replicates thawed to a semi-frozen state and pressing operation occurred while the must temperature was approximately -1 – 4°C. The six replicates were combined for a total of two separate pressing operations using a hydraulic, stainless-steel basket press. For the Traminette variety, the juice was collected into a sanitized 15-gallon open-top, low density polyethylene fermentation bins with a lid (Nalgene Nunc International, Waltham, MA), treated with pectic enzyme (2g/hL Lallzyme C) and stored at 3°C for 24 hours for settling. This method of storage during cold settling for the Traminette was observed to result in significant oxidation of the juice, as it was extremely brown in appearance after 24 hours. Because of this, a different approach was pursued for the Cayuga. For Cayuga, the juice was collected and transferred to four sanitized 5-gallon glass carboys, treated with pectic enzyme (2g/hL Lallzyme C) and stored at

3°C for 24 hours for settling. The cryogenic maceration replicates were racked into clean carboys prior to inoculation.

Each replicate was inoculated with Saccharomyces cerevisiae EC-R2 yeast (Lalvin,

Petaluma, CA), at a rate of 0.30 g/L yeast with additions of 0.30 g/L of Go-Ferm nutrient

(Lallemand, Petaluma, CA) and 0.30 g/L Opti-White (Lallemand, Petaluma, CA). Primary fermentation was carried out without external temperature control. Alcoholic fermentation was monitored daily by temperature readings using a thermocouple and TSS readings via hydrometer. For extended skin contact replicates, pomace caps were punched down three times daily in addition to fermentation monitoring. At one-third sugar depletion, Fermaid K was added at the rate of 0.25 g/L.

Once Brix measured below zero by hydrometry, an enzymatic reducing sugar assay

(Clinitest, Bayer AG, Leverkusen, Germany) was employed to confirm dryness, defined as < 1% residual sugar. Wine replicates samples were collected (250 mL) for pH, titratable acidity (TA), alcohol, volatile acidity (VA), free SO2 and total SO2 measurements. An aliquot of wine (100 mL) was frozen at -80°C until further analysis could be performed. Extended skin contact replicates were combined, pressed using a hydraulic stainless-steel basket press and transferred into two

5-gallon carboys. Each wine replicate was dosed to achieve 50 mg/L SO2 and held at 3°C for 48 hours for settling. The replicates were then racked and allowed to cold stabilize until bottling.

Existing free SO2 concentrations were determined one day prior to bottling by the aeration oxidation method. Wine was manually bottled (Prospero TSM2005-IC-PEC, Pleasantville, NY) into sanitized 750 mL clear glass bottles and sealed with a screw-cap closure. Bottled wine was stored in cases in cold storage at 3°C until analysis.

2.3.4 Juice and Wine Chemical Analysis

The collected juice and wine samples were analyzed for TSS, pH and TA. Total soluble solids (°Brix) were measured using a handheld refractometer (Master, Atago, Nellevue, WA). pH was measured using an Orion Star A111 pH meter (Thermo Fisher Scientific, Waltham, MA).

Titratable acidity was measured using an autotitrator (G20, Mettler Toledo, Columbus, OH).

Prior to TA measurements, samples were heated in warm water (~30°C) for 10 minutes, then sparged with nitrogen gas for 30 seconds to remove dissolved CO2. A 10 mL sample of juice or wine was diluted to 40 mL with deionized water, titrated to a pH of 8.2 using 0.10 N sodium hydroxide, and resulting TA was recorded using tartaric acid equivalents (g/L).

Alcohol content (%v/v) in wines was determined using an ebulliometer (Laboratories

Dujardin-Salleron, Noizay, France). Volatile acidity (VA) was measured using a Cash still distillation apparatus and reported as acetic acid equivalents. Total SO2 in the wine samples was determined using the Ripper method. Free SO2 was determined using the aeration

oxidation method. All wine chemical analysis methods followed procedures established by OIV

[111].

2.3.5 CIE-LAB Color Measurements

Tristimulus color for juice and wine samples was obtained following the method described in the Compendium of International Methods of Wine and Must Analysis [111]. Samples were filtered through a 0.45 μm PTFE syringe filter (0.45 μm, 13 mm filter diameter; AcrodiscTM, Ann

Arbor, MI) and transferred to a 10mm glass cuvette. The full spectrum of the sample was scanned in transmittance mode from 280 nm to 780 nm in 5 nm increments, and the CIE-LAB parameters (L*, a*, b*, C*ab, hab) were obtained through integration and using the tables provided within the reference literature. Illuminant D65 and 10° Observer were used in the calculations as the standard conditions. Within the uniform color space CIELAB, the color coordinates a* and b*, and lightness L* are defined. The coordinate a* takes positive values for red and negative values for green, and the coordinate b* takes positive values for yellow and negative values for blue. The value L* is an approximate measure for luminosity and is defined as the property in which each color can be considered equivalent to a member of the gray scale between black and white, taking values between 0 – 100. Other parameters such as chroma

(C*ab) and hue (hab) can be defined using CIELAB space values:

∗ ∗ ∗ / � = [(� ) + (� ) ]

∗ ∗ ℎ = arctan (� /� )

Chroma (C*ab) allows the determination for each hue the degree of difference in comparison to a gray color with the same lightness, and is a quantitative measure of colorfulness. Hue (hab) is the parameter by which colors have traditionally been defined as red, green, etc, and allows to distinguish a color with reference to a gray color of the same lightness.

Hue is considered the qualitative attribute of color, as it is related to difference in absorbance at different wavelengths.

Color differences may be quantified by the Euclidean distance between two points in three- dimensional space defined by L*, a* and b*:

∗ ∗ ∗ ∗ ∆� = (∆� ) + (∆� ) + (∆� )

For each of the parameters L*, a*, b* and C*ab, one-dimensional changes in color may be calculated by the final value of the variable minus the initial one, which yields values for DL*,

Da*, Db* and DC*ab. Changes in hue, DHab, are calculated according to the following:

∗ ∗ ∗ ∆� = (∆� ) − (∆� ) − (∆� )

2.3.6 Determination of antioxidant capacity

Antioxidant capacity of wine samples was determined using the DPPH radical scavenging assay method previously reported [4]. Trolox stock solutions in the range of 1 to 750 μM made in methanol were used to create a calibration curve. For the assay, a 63.4 μM DPPH stock solution was made in methanol, to which 0.1 mL of wine of Trolox calibration standard was added. Solutions were mixed and stored at ambient temperature in the dark for 60 minutes.

Absorbance measurements of the solutions were obtained at 515 nm on the Thermo Scientific

Genesys 10S UV-Vis spectrophotometer (Waltham, MA) using 80% (v/v) as a blank. Antioxidant capacity was reported as mg/L equivalents of Trolox.

2.3.7 Determination of total phenolic content

Total phenolic content was determined using the Folin-Ciocalteu assay on wine samples, following the method adapted by Waterhouse [112, 113]. Gallic acid stock solution was prepared in a 100 mL volumetric flask by dissolving 0.5 grams of gallic acid in 10 mL of ethanol, with the remaining volume filled to the line with MilliQ water. A calibration curve of gallic acid 50

was prepared in the range of 0 to 500 μM. For each sample, 20 μL of wine or calibration solution was pipetted into separate cuvettes, along with 1.58 mL of water and 100 μL of Folin-

Ciocalteu reagent and well mixed. After waiting one minute, 300 μL of sodium carbonate solution was added. The solutions were mixed and stored at ambient temperature for 120 minutes. The absorbance of each solution at 765 nm was obtained on the Thermo Scientific

Genesys 10S UV-Vis spectrophotometer (Waltham, MA) using water in place of wine or calibration solution as a blank. Total phenolic content was reported as mg/L equivalents of gallic acid.

2.3.8 Glutathione determination

Prior to glutathione analysis, samples were filtered through a 0.45 µm filter and then shipped overnight to Penn State Hershey on dry ice where they were then stored at -80°C until time of analysis. On the day of analysis, samples were thawed, mixed 1:1 with HPLC grade methanol

(750 uL each; Fisher Scientific, Hampton, NH, USA), and then filtered with a 0.25 µm syringe filter (Whatman plc, Maidstone, UK) into HPLC vials (Agilent Technologies, Santa Clara, CA,

USA). Sample vials were then placed in a refrigerated auto-injector (ESA Model 542) at 4°C to prevent any potential degradation.

Samples were analyzed by high-performance liquid chromatography (HPLC; ESA Model

582 Solvent System) with a Prodigy 5 µm ODS-3 100 Å column (250 x 4.6 mm; Phenomenex,

Torrance, CA, USA) and an electro-chemical detector (ECD, ESA CoulAssay Detector). The

HPLC was used with one mobile phase, which was 50 mM sodium phosphate buffer and 1 mM octane-sulfonic acid brought to pH 2.7 with phosphoric acid and mixed with acetonitrile (ACN,

HPLC grade, Fisher Scientific) to a final concentration of 5% ACN, at 1.5 mL/min with 15 minutes for each sample with GSH eluting around 6.6 min. Sample injection volumes were 20

µL. The ECD cells analyzed were 300 mV (to remove easily oxidize interferences) and 920 mV

(to analyze glutathione). Fresh glutathione (l-glutathione, Kyowa Hakko Kogyo Co., Chiyoda-ku,

Tokyo, Japan) standards were prepared daily in 3 mM EDTA, ranging from 3 to 150 µM.

Spectra were recorded and analyzed with CoulArrayWin software. Method recovery (110%) was determined by processing the 150 µM GSH standard with the methodological procedure used for the samples and determination of final concentration. Instrumentation accuracy (95%) found by spiking samples with known amounts of standard to 1 mL of sample after filtration.

Precision (97%) was tested by replicating samples from both juice (n=5, 99%) and wine (n=3,

96%) and from a standard (n=3, 96%).

2.3.9 Accelerated aging study

An accelerated aging study of the Cayuga and Traminette wines was performed. Equal volumes of the replicates of each treatment were combined together under a nitrogen stream to create one 750 mL aliquot representing each treatment (C, CM and ESC). The replicates were pooled to ensure the aliquot was representative of bottled replicated, as well as to ensure homogeneity of the aliquot. To create the pooled aliquot specific to each treatment, wine bottle closures were removed, immediately followed by a gentle nitrogen stream introduced into the headspace. Once the headspace was flushed for several minutes, a glass, 5mL bottle-top dispenser (LabIndustries L/I Repipet ® Dispenser, Barnstead Thermolyne, Dubuque, IA) connected to a nitrogen stream was fitted over the top of the wine bottle and was used to take wine samples. The initial 50 mL of wine collected from each bottle was discarded. Aliquots of each treatment (20mL) were transferred to nitrogen-flushed 20 mL screw-top vials (Restek,

Bellefont, PA). The vials were sealed with a screw-cap containing rubber septa, which was subsequently punctured with a 21 gauge needle to allow oxygen ingress. Wine samples were made in triplicate. The vials were aged at room temperature (25°C) for 96 hours.

2.3.9.1 Measurement of Fe(II):Fe(III) ratios in wine

A calibration curve was obtained by the addition of FeSO4•7H2O to model wine (12% ethanol, 8.0 g/L tartaric acid, pH 3.3 with NaOH) containing Br-PAPs (2.6 x 10-4 mol/L) and 2 mole equivalents of ascorbic acid to ensure no Fe(III) was present. The Br-PAPs ligand was added first to ensure the Fe(II) did not oxidize; addition of the Fe(II) prior to the ligand would result in rapid oxidation of the tartrate complex. The Fe(II)-Br-PAPs complex is not able to react with oxygen. The calibration curve was constructed using Fe(II) concentrations ranging from 1.0 to 4.0 mg/L (1.79 to 7.16 x 10-5 mol/L).

Samples of 2.5 mL were removed from the vials vial syringe and transferred to nitrogen- flushed reaction tubes. Br-PAPs was rapidly added (2.6 x 10-4 mol/L; 25µL of a solution containing 14 mg/1000µL H2O), and absorbance at 740 nm was measured after 30 seconds and then at 1 min intervals for 6 min. The results were plotted to obtain trend lines, which were then extrapolated to time zero to determine the absorbance at the moment of mixing (t0). Mean t0 (±SD) values were calculated from triplicate samples. To calculate total Fe concentration, excess ascorbic acid (9.4 mg in 100 µL 0.01 N H2SO4) was added to 50 mL of wine under nitrogen and Br-PAPs (25 µL) was added to 2.5 mL of wine under nitrogen. After 4 hours, absorbance at 740 nm was measured in triplicate, which corresponded to total Fe concentration.

2.3.10 Statistical analysis

Statistical analysis was performed by SPSS Statistics statistical software (IBM, version 25,

Armonk, NY). One-way ANOVA was used to evaluate group differences, with post-hoc planned comparison testing completed using Tukey HSD. The results presented represent mean, overall model significance, and between-group differences for the control, cryogenic maceration and extended skin contact treatments. Data is represented as mean values (± standard deviation) of all replicates of each treatment. Detailed discussion of results obtained from one-way ANOVA and post-hoc tests can be found in Appendix B. 53

2.4 Results and Discussion

2.4.1 Juice and Wine Conventional Analysis

The results from the conventional juice and wine analysis obtained from Cayuga (

Table 2.2) and Traminette (Table 2.3) wines are juices are found below. Although statistically significant differences were observed between treatments for the pH of Cayuga juice and wine, when considered in the context of the typical values found in Table 2.1, these differences are not meaningful. These values were well within the range of those reported in

Table 2.1.

Table 2.2: Juice and wine conventional analysis of Cayuga (mean values and standard deviation) for control (C), cryogenic maceration (CM), and extended skin contact (ESC). One- way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice Brix pH Titratable Acidity

C 19.7 ± 0.10a,b 3.10 ± 0.01a,b 7.26 ± 0.06a

CM 20.2 ± 0.06a 3.14 ± 0.01a 6.71 ± 0.00a

ESC 19.5 ± 0.38b 3.08 ± 0.05b 7.85 ± 0.62b

Wine Free SO2 pH Titratable Acidity

C 11.7 ± 5.3a 3.49 ± 0.03a 7.91 ± 0.23a

CM 1.8 ± 0.8b 3.54 ± 0.01b 7.39 ± 0.06b

ESC 2.8 ± 1.4b 3.37 ± 0.01c 8.42 ± 0.22c

Table 2.3: Juice and Wine Conventional Analysis of Traminette (mean values and standard deviation) for control (C), cryogenic maceration (CM), and extended skin contact

(ESC). One-way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice Brix pH Titratable Acidity

C 21.1 ± 0.19a 2.97 ± 0.01a 8.50 ± 0.09a

CM 20.1 ± 0.12b 3.31 ± 0.01b 6.90 ± 0.10b

ESC 20.9 ± 0.30a 3.12 ± 0.12c 7.82 ± 0.34c

Wine Free SO2 pH Titratable Acidity

C 8.3 ± 1.12a 3.49 ± 0.03a 8.92 ± 0.15a

CM 1.37± 0.00b 3.54 ± 0.01b 7.52 ± 0.08b

ESC 1.37 ± 0.00b 3.67 ± 0.01c 7.44 ± 0.15b

2.4.2 CIE-LAB Color Values

The results for the CIE-LAB color values observed in Cayuga juice and wine can be found in

Table 2.4. The most significant findings can be observed in the CIE-LAB values for wine, as statistically significant differences were observed between the treatments. The ESC wine was observed to be darker and more orange in color than C and CM wines. An increase in lightness

L* was observed between the Cayuga wine values for C and C in comparison to ESC, which indicates that C and CM wines were lighter and less brown. The value of a* increased in ESC compared to C and CM which indicates browning, which may be due to polymerization and subsequent precipitation of the pigments which give color [110]. Positive b* values indicate more browning observed in the ESC wines versus the C and CM wines. C*ab values are indicative of a more vivid color, with the largest values observed in the ESC juice, indicating greater color saturation, i.e. darker in color.

Table 2.4: CIE-LAB color values observed from Cayuga juice and wine for control (C), cryogenic maceration (CM), and extended skin contact (ESC) treatments. One-way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice Values C CM ESC

L* 99.6 ± 0.1a 97 ± 0.3b 99.8 ± 0.1a

a* 0.23 ± 0.06a 3.59 ± 0.12b .11 ± 0.07a

b* 3.89 ± 0.37a 11.34 ± 0.25b 2.70 ± 0.37c

a b c C*ab 3.89 ± 0.37 11.76± 0.46 2.71± 0.37

a b a Hab 86.7 ± 0.6 72.7 ± 0.3 87.7 ± 1.1

Color hue 7.5 ± 0.9a 2.5 ± 0.2b 11.1 ± 2.4c

Color Intensity 0.069 ± 0.008a 0.21 ± 0.013b 0.050 ± .007c

Wine Values C CM ESC

L* 99.4 ± 0.0a 99.4 ± 0.1a 98.8 ± 0.1b

a* 0.54 ± 0.7a 0.66 ± 0.16a 1.23 ± 0.12b

b* 4.22 ± 0.08a 3.95 ± 0.11a 6.09 ± 0.33b

a a b C*ab 4.25 ± 0.09 4.01 ± 0.14 6.21 ± 0.35

a a b Hab 82.7 ± 0.9 80.5 ± 2.0 78.5 ± 0.5

Color hue 5.07 ± 0.37a 4.41 ± 0.58a 3.90 ± 0.09b

Color intensity 0.069 ± 0.002a 0.065 ± 0.005a 0.120 ± 0.005b

Table 2.5 shows the changes in LAB color parameters observed between the Cayuga juice and wine due to the maceration process. Each treatment was compared to the control juice and wine, and the differences were quantified. For wine, it is expected that the CM values would deviate less from the C in comparison to ESC; i.e. greater differences would be observed in the

ESC wine in comparison to CM. This trend was observed. The ∆L* values indicate the difference in lightness and darkness, with positive values indicating wines were lighter in comparison to control and negative values indicating treatment wines were darker. Although both wines were darker than the control wine, the ESC had a greater magnitude. The ∆a* values indicate the difference between red and green, with positive numbers correlating to redder in color, and negative values being greener. Both CM and ESC wines showed more positive ∆a* colors in comparison to control, with the magnitude of the ∆a* value in ESC wine being greater.

The ∆b* values indicate differences in yellow and blue, with positive numbers being more yellow, and negative values representing bluer colors. The ∆b* value of ESC was greater than the control, and taken into context with the ∆a* value, this finding indicates that ESC wines were overall more orange than the C. The ∆b* value for CM was negative, indicating it was bluer than the control. This may also be indicative of greater inhibition of the formation of the yellow xanthylium cation, an undesirable pigment and by product of wine oxidation which may induce color changes that are associated with a decrease in wine quality [41, 42] observed in the CM compared to C. Greater ∆E*ab values indicate a higher variability of color between samples, illustrating that ESC was more variable in color than the CM wines in comparison to control.

Table 2.5: Changes in CIE-LAB color parameters observed between Cayuga juice and wine, in comparison to the control, due to maceration processes.

CIE-LAB Cayuga Juice Cayuga Wine

Parameter CM ESC CM ESC

∆L* -2.40 -0.52 -0.03 -0.63

∆a* 3.21 0.67 0.12 0.69

∆b* 7.25 1.45 -0.27 1.87

∆C*ab 7.76 1.54 -0.24 1.96

∆Hab 1.63 0.41 0.16 0.37

∆E*ab 8.29 1.68 0.29 2.09

Overall, the CIE-LAB color values support the hypothesis that CM was expected to be equivalent or better performing than C in regards to wine quality parameters. These findings are supported by the appearance of the Cayuga wine replicates that can be found in Figure 2.2.

Figure 2.2. Image of Cayuga wine replicates; from left: control (C), cryogenic maceration (CM) and extended skin contact ESC.

2.4.2.1 CIE-LAB Color Values for Traminette

The results for the CIE-LAB color values observed in Traminette juice and wine can be found in Table 2.6. Unlike the results observed in the Cayuga replicates, the CIE-LAB color results indicate that the Traminette CM wine was more closely correlated to the ESC wine than the control, as evidenced by the L*, a*, b* values. The CM and ESC wines were darker and browner than the C, indicating that browning reactions and oxidation has occurred in these wines. These results are unsurprising, due to the observation that the CM juice underwent significant oxidation during the cold-settling period prior to the start of fermentation. This can be observed in the CIE-LAB values colors of the CM juice, in which the decrease in L* and large comparative increases in a* and b* support this theory, especially when compared to the results observed in the Cayuga juice, where there not nearly as significant differences observed between treatments. Interestingly, although there did appear to be significant oxidation that occurred in the CM juice, the CIE-LAB values of the CM wine suggest that some recovery may

have occurred, due to the increase in lightness L* which indicates that wines were lighter and less brown post-fermentation.

Table 2.6: CIE-LAB color values observed from Traminette juice and wine for control (C), cryogenic maceration (CM), and extended skin contact (ESC) treatments. One-way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice Values C CM ESC

L* 99.5 ± 0.1a 89.4 ± 0.2b 96.4 ± 2.2c

a* 0.35 ± 0.04a 10.72 ± 0.47b 2.91 ± 1.87c

b* 3.69 ± 0.42a 43.42 ± 0.37b 12.22 ± 6.18c

a b c C*ab 3.71 ± 0.42 45.47 ± 0.32 12.58 ± 6.42

a b a Hab 84.3 ± 0.4 76.7± 0.6 78.7± 5.5

Color hue 6.35 ± 0.25a 3.55± 0.20a 4.26 ± 2.40a

Color Intensity 0.073 ± 0.010a 1.0970 ± 0.000b 0.285 ± 0.153c

Wine Values C CM ESC

L* 99.1 ± 0.0a 95.7 ± 0.6b 96.1 ± 1.3c

a* 0.86 ± 0.03a 5.29± 0.61b 5.00± 1.21c

b* 5.20 ± 0.13a 15.31 ± 1.74b 13.32 ± 4.57b

a b b C*ab 5.27± 0.13 16.20 ± 1.84 14.24± 4.70

a b b Hab 80.6 ± 0.4 71.0 ± 0.4 69.0± 1.8

Color hue 4.29 ± 0.13a 2.31 ± 0.04b 2.18 ± 0.17b

Color Intensity 0.100 ± 0.002a 0.320± 0.043b 0.286± 0.100b

Table 2.7 shows the changes in LAB color parameters observed between Traminette juice and wine due to the maceration process. Each treatment was compared to the control juice and wine, and the differences were quantified. As expected, the CM and ESC wines were fairly

similar in the extent of changes observed in comparison to control. As seen with the results in

Table 2.6, the CM and ESC values were observed to be fairly similar.

Table 2.7: Changes in CIE-LAB color parameters observed between Traminette juice and wine, in comparison to the control, due to maceration processes.

CIE-LAB Traminette Juice Traminette Wine

Parameter CM ESC CM ESC

∆L* -10.23 -3.10 -3.67 -2.28

∆a* 10.46 2.54 4.70 3.46

∆b* 40.14 8.53 10.93 5.49

∆C*ab 41.43 8.86 11.79 6.26

∆Hab 1.86 0.78 1.59 1.72

∆E*ab 42.72 9.42 12.45 6.88

An image of the Traminette wines can be found in Figure 2.3 and illustrates that differences reflected in the CIE-LAB color values. Greater ∆E*ab values indicate a higher variability of color between samples, illustrating that CM was more variable in color than the ESC wines in comparison to control, likely due to the oxidation that occurred.

Figure 2.3. Image of bottled Traminette replicates; from left: control (C), cryogenic maceration (CM) and extended skin contact ESC.

2.4.3 Determination of Antioxidant Capacity

The results of the DPPH antioxidant capactiy assay for Cayuga can be found in Figure 2.4.

Antioxidant capacity by the DPPH assay is a way to quantify the wine’s ability to mitigate deleterious oxidation that may occur. For both the Cayuga juice and wine, little variation in antioxidant capacity was seemingly observed between treatments. Tabulated values can be found in .

Table 2.8: Antioxidant capacity of DPPH radical scavenging, expressed in mg/L Trolox, and

Folin-Ciocalteau (F-C) total phenolic content, expressed as mg/L gallic acid equivalents for control (C), cryogenic maceration (CM), and extended skin contact (ESC) for Cayuga juice and wine. One-way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice C CM ESC

DPPH 1067 ± 22a 836 ± 20a,b 838± 286b

F-C 498± 50a 351± 103b 377± 109b

Wine C CM ESC

DPPH 1049 ± 11a 1035± 8a 1069 ± 1b

F-C 317± 12a 351± 12b 673± 26c

However, when analyzing the changes in the DPPH activity observed between the juice and wine, interesting trends are revealed. For the C, the antioxidant capacity was 1067 ± 21 mg/L

Trolox equivalents in the juice vs 1049 ± 11 mg/L Trolox equivalents in the wine. This suggests that no outside of a slight decrease in antioxidant capacity, no dramatic changes occurred in the average antioxidant capacity over the course of fermentation. In the CM juice, the antioxidant capacity was 836 ± 20 mg/L Trolox equivalents versus 1035 ± 8 mg/L Trolox equivalents in the wine. This reveals that a 19% increase in average antioxidant capacity occurred in the CM treatment. It is unknown why the antioxidant capacity of the CM treatment was significantly lower than the C. It may be due to the exposure of the Cayuga CM must to air during the thawing period after the CM treatment and prior to pressing. For the ESC, a similar increase of

22% in average antioxidant capacity was observed; with 838 ± 268 mg/L Trolox equivalents in the juice versus 1069 ± 1 mg/L Trolox wine. It is important to note that the standard deviation associated with the antioxidant capacity in the ESC juice is quite large, and thus results in less confidence in the apparent increase in average antioxidant capacity.

Cayuga Juice Cayuga Wine 1500 1500 C C

a b CM a a b CM 1000 a,b ESC 1000 ESC

500 500 mg/L Trolox equivalents mg/L Trolox equivalents 0 0 C C CM CM ESC ESC Treatment Treatment

Traminette Juice Traminette Wine 1500 1500 C C CM CM c 1000 ESC 1000 ESC a a 500 500 b b c mg/L Trolox equivalents mg/L Trolox equivalents 0 0 C C CM CM ESC ESC Treatment Treatment

Figure 2.4. Antioxidant capacity as measured by DPPH, expressed as mg/L Trolox equivalents, for control (C), cryogenic maceration (CM), and extended skin contact (ESC) for a) Cayuga juice; b) for

Cayuga wine; c) for Traminette juice; and d for Traminette wine. Different letters indicate statistical significance by one-way ANOVA.

The results from the DPPH radical scavenging assay for Traminette can be found in Figure

2.4. The Traminette juice and wine results illustrate some interesting trends in the antioxidant capacity, and tabulated values of antioxidant capacity for Traminette can be found in .

Table 2.9: Antioxidant capacity of DPPH radical scavenging, expressed in mg/L Trolox, and

Folin-Ciocalteau (F-C) total phenolic content, expressed as mg/L gallic acid equivalents for control (C), cryogenic maceration (CM), and extended skin contact (ESC) for Traminette juice and wine. One-way ANOVA indicated significant between-group difference. Different letters indicate statistical difference.

Juice C CM ESC

DPPH 583 ± 56a 256 ± 16b 184 ± 19c

F-C 236 ± 33a 237 ± 21a 175 ± 24b

Wine C CM ESC

DPPH 541 ± 24a 416 ± 38b 966 ± 16c

F-C 236 ± 8a 265 ± 11b 415 ± 47c

Similar to results observed in Cayuga, the antioxidant capacity remained essentially unchanged between the juice and the wine, with 583 ± 50 mg/L Trolox equivalents in the juice vs 541 ± 24 mg/L Trolox equivalents in the wine. In the CM, we see a similar trend to those revealed in the Cayuga. The antioxidant capacity increased by 38% between the juice and wine samples, with 256 ± 19 mg/L Trolox equivalents in the juice vs 416 ± 38 mg/L Trolox equivalents in the wine. Although the average antioxidant capacity is the lowest in the CM wine compared to both C and ESC, the apparent increase in activity is reassuring that the CM treatment had an impact on activity of the CM wines. This indicates that the CM treatment was beneficial in regards to antioxidant capacity, illustrating that not only was the antioxidant capacity preserved throughout winemaking, but an increase in average antioxidant capacity was observed. The antioxidant capacity of the ESC treatment increased substantially between the juice and the wine samples. An 81% increase in average antioxidant capacity was observed, with 184 ± 19 mg/L Trolox equivalents in the juice vs 966 ± 16 mg/L Trolox equivalents in the wine. This result supports that the greatest extraction of antioxidant compounds occurred from the ESC wine.

Additionally, in comparison to the results in Cayuga, the average antioxidant capacity increased substantially between juice and wine samples, indicating that the maceration treatments had a profound effect on the antioxidant capacity in the Traminette. Antioxidant capacity in the C juice was significantly greater for both Cayuga and Traminette. This may be due to processing techniques; the control most likely had the lowest exposure to oxygen. Due to the ease of

handling of juice versus the must during the initial processing steps and maceration treatment, some oxidation may have occurred in CM and ESC.

The antioxidant capacity is governed by the reaction rates of the phenolic and the radical substrate, driven by molecular stoichiometry and available reaction sites on the phenolic [4].

Overall, less differences between treatments in antioxidant capacity than expected; possibly due to the presence of meta, para or mono substituted phenolics, which respond to Folin-Ciocalteu assay but not the DPPH radical scavenging assay. Additionally, it should be noted that the differences observed in antioxidant capacity between the Cayuga and the Traminette are significant; the Cayuga juice and wine contain significantly greater total antioxidant capacity in comparison to the values observed in the Traminette. This result is another indicator how variable grape composition is between varieties, and how this may impact the resulting wine quality.

2.4.4 Determination of Total Phenolic Content

The results for total phenolic content in Cayuga juice and wine can be found in Figure 2.5. It was observed that total phenolic content increased with maceration treatments for both Cayuga and Traminette wines. This was expected, as these maceration techniques have previously been shown to result in a much greater extraction of phenolics in Chardonnay and Sauvignon blanc [4]. There were significant differences observed in the total phenol content of C compared the CM and ESC juice; with initial total phenolic content in the C juice being significantly greater.

Because the juice samples for all treatments was collected prior to fermentation, the effects of the treatment on the total phenolic content is not directly quantified. The measurement of the total phenolic content of the juice only indicates the starting level of phenolics for each treatment. The more significant observation as it relates to wine quality is the resulting total phenolic content of the wine post fermentation. No significant differences between the total

phenol content of the CM and ESC juice was observed, which indicates that the extent of initial extraction of phenolics in the macerated juices was essentially the same in Cayuga. The total phenolic content of CM and ESC had large standard deviations which indicates a high level of variability in the samples. The trends observed in the differences between the total phenolic content of the juice and the wine are striking. A decrease in the total phenolic content was observed between the C juice and wine, with 498 ± 50 mg/L gallic acid equivalents in juice versus 317 ± 12 mg/L gallic acid equivalents in wine. The total phenolic content did not change between the CM juice and wine, with 351 ± 103 mg/L gallic acid equivalents in the juice and 351

± 12 mg/L gallic acid equivalents in the wine. The total phenolic content in the ESC increased by

44% between the juice and wine treatments, with 377 ± 109 mg/L gallic acid equivalents in the juice and 673 ± 26 mg/L gallic acid equivalents in the wine. The overall trend observed in the

Cayuga wine between treatments is expected, with the total phenolic content of the control being statistically significantly less than the CM and ESC treatments, and the ESC wine containing the greatest phenolic content.

Cayuga Juice Cayuga Wine 800 800 C c C CM 600 a CM b 600 b ESC ESC 400 b 400 a

200 200

mg/L Gallic acid equivalents 0

mg/L Gallic acid equivalents 0 C C CM CM ESC ESC Treatment Treatment

Traminette Juice Traminette Wine

500 500 c C C 400 CM 400 CM ESC b ESC 300 a a 300 a b 200 200

100 100

mg/L Gallic acid equivalents 0 mg/L Gallic acid equivalents 0 C C CM CM ESC ESC Treatment Treatment

Figure 2.5. Total phenolic content as measured by Folin-Ciocaultau, expressed as mg/L Gallic acid equivalents, for control (C), cryogenic maceration (CM), and extended skin contact (ESC) for a) Cayuga juice; b) for Cayuga wine; c) for Traminette juice; and d) for Traminette wine. Different letters indicate statistical significance by one-way ANOVA.

The results for the total phenolic content Folin-Ciocalteau assay for Traminette can be found in Figure 2.5. As with the results from antioxidant capacity, the fairly similar trends were observed in the total phenolic content of the Traminette juice and wine compared to Cayuga. No statistical significant differences between the total phenolic content of the control and CM juice were observed. The total phenolic content of the ESC juice was statistically significantly lower than C and CM, but were within the same range. This indicates that initial extraction of phenolics in the Traminette juice maceration is not significant among the treatments and control.

No increase in total phenolic content of the C was observed between the juice and wine

samples; with 236 ± 33 mg/L gallic acid equivalents in the juice and 236 ± 8 mg/L gallic acid equivalents in the wine. The CM treatment showed slight increases (~10%) in total phenolic content, with 237 ± 21 mg/L gallic acid equivalents in the juice and 265 ± 11 mg/L gallic acid equivalents in the wine. The ESC resulted in the greatest increase in total phenolic content, 175

± 24 mg/L gallic acid equivalents in the juice and 415± 47 mg/L gallic acid equivalents in the wine, which signifies at 58% increase.

For both Cayuga and Traminette, the total phenolic content of the wine showed statistically significant differences between treatments, with the total phenolic content increasing in the order of C < CM < ESC. The greatest total phenolic content was observed in the ESC wines, which was expected due to greater extraction typical of long skin contact times. The CM wines had significantly greater total phenolic content than the C wines, and this indicates it is effective at extracting more phenols than typical white winemaking. It has previously been shown in

Sauvignon blanc that cryogenic maceration increases the phenolic content due to not only increased extraction but also results from protection against oxidation (Baiano 2012) (Olejar

2015). A study performed in red grapes subject to freezing by dry ice resulted in increased proanthocyanidin extraction from the seeds, which indicates cryogenic maceration is an effective method of releasing phenolics from seeds and skins without ethanol (Busse-Valverde

2010). During the cryogenic maceration process, the resulting cellular membrane disruption allows for easier extraction of juice, with a reduction in press time and pressure that lowered chance of oxidation. The pressing of the must also affects the phenolic content, allowing juice to oxidize and thus lowers the phenolic content. Increased pressing has previously been shown to result in a decreased amount of phenolics in the final juice [8]. Because the CM must was pressed after the maceration treatment, the extraction of phenolics from the skin and seeds would have already occurred and may offer greater protection from oxidation compared to the control. Overall, the total phenolic content of the Cayuga and Traminette wines followed

expected trends, with the maceration treatments offering greater extraction of phenolics in comparison to traditional white winemaking. Additionally, it should be noted that there are differences observed in total phenolic content between the Cayuga and the Traminette; the

Cayuga juice and wine contain greater total phenolic content in comparison to the values observed in the Traminette. This result may be indicative of the variable grape composition observed between varieties, and may potentially have an impact on the resulting wine quality.

2.4.5 Glutathione Determination

The results for glutathione concentration in Cayuga juice and wine as determined by HPLC-

ECD can be found in Figure 2.6. No statistically significant differences in the GSH concentration of the Cayuga juice are observed between the C and ESC; this indicates that the initial concentration of GSH among treatments is essentially the same, with GSH concentrations of 49

± 3 mg/L in the C juice and 41 ± 11 mg/L in the ESC juice. The GSH concentration in the CM was 1.0 ± 0.1 mg/L, statistically significant and substantially lower than C or ESC, which strongly suggests that oxidation of the CM juice sample may have occurred prior to analysis.

Although it is possible for GSH to be produced by yeast during fermentation, it seems unlikely it was only produced in the CM wine, even though the C and ESC wines were inoculated with the identical yeast strain and nutrition parameters. Because the GSH concentration is virtually the same between the C and ESC juices, and also based on the similar trends obtained for antioxidant capacity and total phenolic content, it may be assumed that this trend would follow in the GSH concentration of the CM juice. In the Cayuga wine, no significant differences were observed in the concentration of GSH between C and CM wines. The GSH concentration of

ESC wine was statistically significantly lower than C and CM. This result indicates greater depletion of GSH in ESC occurred, and may be due to oxidation. A 29% decrease in the GSH concentration between the juice and wine of C was observed, compared to the 70% decrease in

ESC. Because the ESC wine had greater total phenolic content relative to C and CM wines, yet

did not follow the same trend for antioxidant capacity (i.e. antioxidant capacity among C, CM and ESC was essentially equivalent), it seems that the increased extraction of phenolics and redox active wine constituents in the ESC did not offer significant protection against oxidation.

When comparing the results of total phenolic content to antioxidant capacity, it would be assumed that greater total phenolic content in the ESC may result in greater overall antioxidant capacity, due to the increased extraction. However, because the method of skin contact requires fermentation to occur in bins instead of air-locked carboys, and also due to the punch downs of the pomace, the incorporation of oxygen in the ESC would be much greater than in the C or CM wines.

Cayuga Juice Cayuga Wine 60 a a 60 C C CM CM 40 a a ESC 40 ESC

20 20 b Glutathione (mg/L) b Glutathione mg/L 0 0 C CM ESC C CM Treatment ESC Treatment

Traminette Juice Traminette Wine 25 25 a C C 20 CM 20 CM ESC ESC 15 15 a

10 10

c Glutathione mg/L 5 5 Glutathione (mg/L) b b b 0 0 C C CM CM ESC ESC Treatment Treatment

Figure 2.6. Glutathione concentration, expressed as mg/L, for control (C), cryogenic maceration

(CM), and extended skin contact (ESC) for a) Cayuga juice; b) Cayuga wine; c) Traminette juice and

Traminette wine. Different letters indicate statistical significance by one-way ANOVA.

The results for glutathione concentration as determined by HPLC-ECD for Traminette juice and wine can be found in Figure 2.5. Significant differences in the concentration of Traminette juice between treatments was observed. The GSH concentration of the C juice was significantly greater than in the CM and ESC juice. As was observed in the GSH results for Cayuga, it is possible that the CM and ESC juice samples were oxidized prior to analysis. GSH in the CM juice was detected, but the concentration was below the limit of quantification, as the peak area was well outside of the calibration range, which is shown in a sample spectrum in Appendix A,

Figure 6.4. GSH was not detected in the ESC juice sample. The limit of detection for GSH was found to be below 0.6 mg/L (or 2 µM), as a glutathione side peak is observed when spiked in the Traminette ESC juice to the achieve a concentration of 2 µM, assuming that the ESC samples contained no GSH. In the Traminette wine, significant differences were observed between treatments, with the control containing the highest concentration of GSH at 12.4 ± 0.4 mg/L, followed by the ESC with 2.8 ± 0.4 mg/L GSH and the CM with 1.0 ± 0.1 mg/L GSH. The

GSH depletion of the control was 38% between juice and wine samples. Overall, the greater depletion of GSH in the ESC wines is indicative of oxidation. In Cayuga wine, the greater depletion of GSH in the ESC sample compared to C and CM was expected. In Traminette wine, the depletion of the GSH in the ESC sample compared to the control was expected, but the low

GSH concentration in CM may indicate oxidation has occurred.

2.4.6 Accelerated Aging Study

The results from the accelerated aging study to determine the redox status of the Cayuga wine is found in Figure 2.7. Because the ligand used in this experiment was selective for Fe(II), the results are presented as % Fe(II) / total Fe. Initially, 90 ± 1% of Fe was present in the wine 71

as Fe(II) was allowed to come into contact with air after the puncturing of the vial septa in the C wine. The Fe(II) concentration fell progressively to a final concentration of 61 ± 4% Fe(II). The

CM wine initially contained 91 ± 3% of the Fe in the form of Fe(II). The Fe(II) concentration of

CM wine fell progressively to a final concentration of 72 ± 5% Fe(II), significantly slower than the

C wine. In the case of the ESC, 74 ± 2 % of Fe was present as Fe(II), and the %Fe(II) dropped to 51% ± 2 after 4 days. It is important to note that as Fe(III) concentration increases over time, particularly beyond the 24 hour time point, the absorbance upon ligand addition increases rapidly, and the initial Fe(II) concentration calculated through extrapolation to t=0 is less certain

[83]. Due to the previous results of antioxidant capacity and glutathione concentration, it was expected that the rate of the decrease in %Fe(II) concentration would be similar in the C and

CM wines, and proceed at a faster rate in the ESC. Although the ESC wine had higher total phenolic content, the antioxidant capacity was similar to the other treatments. The depletion of

GSH compared to the control wine was an indication that the ESC wine has already undergone some oxidation. Because the rate of Fe(III) reduction depends on the concentration and reactivity of polyphenols as well as sulfite concentration, greater antioxidant capacity should result in slower decreases in %Fe(II) concentration. The lower [Fe(III)]:[Fe(II)] ratio in the CM versus the C indicates that polyphenols in wine are capable of removing the O2 that is entering the system, allowing it to maintain a reductive state. The CM wines had greater total phenolic content resulting from the maceration treatment, and therefore exhibited a slower rate of %Fe(II) decrease in comparison to C.

100 C CM 80 ESC

% Fe(II) 60

40 0 20 40 60 80 100 Time (hours)

Figure 2.7. Change in %Fe(II) concentration of Cayuga wine for control (C), cryogenic maceration

(CM) and extended skin contact (ESC) wines over 96 hours.

The results from the accelerated aging study to determine the redox status of the Traminette wines is found in Figure 2.8. Because the Traminette wines had lower total phenolic content and antioxidant capacity than Cayuga, it was expected that the %Fe(II) concentrations would be lower in this variety, and this was observed. The lower levels of polyphenols in the Traminette wines resulted in more rapid decreases in the %Fe(II) concentration compared to Cayuga.

Initially, 91 ± 5% of Fe was present in the as the Fe(II) was allowed to come into contact with air after the puncturing of the vial septa in the C wine. The Fe(II) concentration fell progressively to a final concentration of 65 ± 4% Fe(II). The initial concentration of %Fe(II) was similar between

Traminette and Cayuga, but the %Fe(II) dropped more rapidly due to less phenolic content present. The CM wine initially contained 78 ± 7% of the Fe in the form of Fe(II), which was significantly less than the concentration of the Cayuga CM wine, most likely due to the probably oxidation that occurred. The Fe(II) concentration of CM wine fell progressively to a final concentration of 47 ± 1% Fe(II), significantly slower than the C wine. In the case of the ESC, 75

± 6% of Fe was present as Fe(II), and the %Fe(II) dropped to 53% ± 3 after 4 days.

100 C CM 80 ESC

% Fe(II) 60

40 0 20 40 60 80 100 Time (hours)

Figure 2.8. Change in %Fe(II) concentration in Traminette wine for control (C), cryogenic maceration

(CM) and extended skin contact (ESC) over 96 hours.

Conclusions

The aging of wine is a complex process, and the most important aspect to winemakers is how the wine in total behaves in storage. This study evaluated the net effect of wine to resist oxidation using wine vinified by novel maceration treatments. Although the cryogenic maceration treatment was expected to have the greatest resistance to oxidation, this result was only observed in the Cayuga wines. As mentioned in the discussion, the Traminette juice may have been oxidized prior to fermentation, which may have impacted the resulting trends observed. Due to a greater process optimization in the vinification of Cayuga grapes, an enhancement of oxidative stability in the CM wine was observed. Overall, cryogenic maceration was shown to be a promising treatment for further study in white hybrid wines.

Chapter 3

Novel Methods for Copper Removal in Wine

3.1 Abstract

The removal of fermentation-derived sulfidic off-odors in wine, such as hydrogen sulfide and low molecular weight thiols, is typically performed by the method of copper fining, which is pervasive throughout the wine industry. The widely accepted mechanistic basis for copper fining is based upon the addition of copper(II) sulfate to wine, which is assumed to react preferentially with H2S and other malodorous thiols, yielding a copper sulfide (CuS) precipitate that is easily removed from wine. However, it has been observed that insoluble CuS is not the sole reaction product; this may lead to deleterious reactions in finished wine, as transition metals such as copper are known to catalyze wine oxidation reactions. In recent studies, an investigation into the underlying mechanism of copper and thiol reactions in wine, along with various other transition metals, indicated that these metals significantly affect the rate and course of copper-

H2S/thiol reactions. Furthermore, removal of H2S by precipitation as insoluble CuS was prevented in the presence of these transition metals and thiols, and H2S oxidation and polysulfane formation was promoted, thus effectively keeping both metals and sulfide species in solution after the addition of copper. These results strongly suggested that it was necessary to re-evaluate the general practice of copper fining in winemaking. The present study describes the use of various sources of immobilized copper in place of copper fining in wine and the effect on the copper (II) concentration, as well as thiol concentration over time. The immobilized

copper materials of CuO-Alumina and Cu(NO3)2-Celite were used in this study. Both immobilized copper materials were observed to result in a decrease in H2S, as well as the thiols

Cys and 3SH in model wine. In real wine systems of Riesling and Lemberger, the immobilized copper materials resulted in a lower Cu concentration than the traditional copper fining method.

In addition to the investigation of bound copper particles as a replacement for traditional copper fining techniques, alternative fining methods for the removal of residual copper were investigated. The ability of various fining proteins including isinglass, gelatin, albumin, casein and other plant-based proteins was assessed for the removal of residual copper in wine. The fining proteins Blancoll (egg albumin) and Plantis AF-P (potato protein) resulted in a 23 – 25% reduction in the Cu concentration of model wine after five days. The use of proteins for the reduction of copper concentration in wine, especially after a copper fining operation, could improve the oxidative stability of finished wine. 3.2 Introduction

Volatile sulfidic containing compounds (VSCs) have significant impacts on the sensory attributes of wine. Because the odor detection thresholds of these compounds are exceedingly low, VSCs are easily perceived by the consumer. Typical methods for the removal of VSCs involve splash racking or aerative pump overs. Both of these methods involve incorporating air into wine, which may lead to the oxidation of thiol compounds. The loss of aroma that results from the oxidation of these thiol compounds may mislead winemakers to believe the VSCs have truly been removed from the wine; however, VSCs can be reduced back to their aroma-active form under the typically reductive conditions seen with modern wine packaging systems. By simply oxidizing the VSCs, they are not truly eliminated from the wine. Another method for the removal of detrimental VSCs involves using inert gas to sparge wine. In this method, oxidation is not involved, yet sparging results in the volatilization of all of the thiol compounds, including

the beneficial/varietal thiols with positive aroma attributes. Furthermore, this process is prohibitive for most winemakers due to the high cost of purchasing large quantities of inert gases.

The standard practice in the winemaking industry for reducing off-odors, particularly H2S, is the process of copper fining. During copper fining, copper is added directly to the wine, almost always in the form of a sulfate or citrate salt [87, 88]. This process was previously thought to remove H2S by precipitation of insoluble CuS through racking or filtration, due to the extreme insolubility of CuS in aqueous solution (3 x 10-14 mg/L). However, based on recent studies, the complete removal of CuS from wine is virtually impossible under wine conditions, and those studies further demonstrated that a complex range of reaction products other than CuS are formed [15, 37, 70, 96 ].

In previous studies, it has been observed that the presence of Cu, along with other transition metals, is implicated in the reappearance of post-bottling reductive aromas [88, 92]. The redox recycling of thiols as catalyzed by various metals in wine is a complex process and the mechanism require further investigation by wine researchers. The observation of the reappearance of H2S and thiols is a relatively new phenomenon, due to modern winemaking practices and the ability to significantly limit O2 during wine production through the use of screwcaps and better closure technologies, resulting in a highly reductive environment.

In mechanistic studies performed by Kreitman et al, it was determined that anaerobic/reductive wine environments, in the presence of Cu and other transition metals post- bottling, favor the release of thiol-Cu complexes [15]. Under these conditions, VSCs are liberated from Cu-complexes and non-volatile disulfides can dissociate, resulting in the liberation of Cu, which can then react with other redox active sulfide compounds, and catalyze further disulfide scission in a redox cycling process. The ability of Cu(II) to react with VSCs in

wine is extremely effective in initially reducing the perceived reductive aromas; however, the direct addition of Cu to wine and resulting redox reactions that occur have numerous downsides, including the troubling reappearance/regeneration of VSCs. Based on these observations, alternative fining techniques which do not result in residual Cu(II) being present in wine would be of significant benefit to the winemaker. Alternative fining techniques, such as the use of animal and plant based proteins, have been investigated. Furthermore, the use of immobilized Cu(II), in which the Cu(II) is covalently bound to an inert substrate, has been investigated as an alternative copper fining technique. Immobilized or bound Cu(II) fining leverages the reaction potential and affinity of Cu(II) and VSCs toward the formation of Cu-thiol complexes, without leaving residual Cu behind post-fining to participate in deleterious reactions after bottling. The potential for the alternative fining process to be conducted without the risk of leaving behind residual copper, and subsequently causing the regeneration of sulfidic odor precursors, has the potential to dramatically decrease the likelihood of the reappearance of post-bottling reductive aromas in wine.

The success of fining proteins to remove small organic molecules such as proanthocyanidins provides a pathway to investigate proteins for the removal of excess copper, and resulting copper-thiol complexes that are formed during oxidation reactions [101] Animal proteins such as casein, gelatin, isinglass and albumin are commonly used to successfully remove polyphenols and astringent compounds such as tannins to improve the overall quality of wine [89]. These animal proteins have similar amino acid content, specifically, proline, glycine and hydroxyproline [114]. Fining proteins are thought to successfully remove molecules from wine through interactions between their charged amino acid residues and electrostatic attraction to these molecules. These interactions could be exploited for removal of metals and metal complexes. Other non-animal proteins such as patatin, wheat gluten and pea protein have been

shown to perform as fining proteins in wine and successfully remove unwanted wine constituents [115]. A newer, increasingly common fining agent is polyvinylpolypyrrolidone

(PVPP), which is a water-insoluble polymer that has previously been shown to effectively adsorb phenolic compounds from wine [101]. The wide variety and complexity of amino acid residues in fining proteins may similarly participate in a multitude of metal-binding mechanisms, such as ion exchange, complexation, coordination and microprecipitation in order to remove residual copper and associated complexes [100]. 3.3 Materials and Methods

3.3.1 Chemicals

L-cysteine (Cys), diethylenetriaminepentaacetic acid (DTPA), copper oxide on alumina

(CuO-Al) particles and copper nitrate on Celite (Cu(NO3)2-Cel) were purchased from Sigma-

Aldrich (St. Louis, MO). 2,4-Dinitrophenylhydrazine (DNPH) was purchased from MCB laboratory chemicals (Norwood, OH) and L-tartaric acid, 3-sulfanylhexan-1-ol (3SH) and 5,5’- dithiobis(2-nitrobenzoic acid) were obtained from Alfa Aesar (Ward Hill, MA). Cupric sulfate pentahydrate was purchased from EDM Chemicals (Gibbstown, NJ). TRIS hydrochloride was purchased from J.T. Baker (Center Valley, PA) and sodium hydrosulfide hydrate (as the source for H2S) was purchased from Acros Organics (Geel, Belgium). Fining proteins Finecoll, Blancoll,

Goldenclar Instant, Plantis AF and Plantis AF-P were obtained from Enartis (Windsor, CA).

Water was purified to 18.2W using a Millipore Q-Plus system (Millipore Corp, Bedford, MA). The chemicals and solvents used were of analytical or HPLC grade. All solutions were prepared volumetrically using Milli-Q water unless otherwise noted.

3.3.2 Vinification

Fruit harvested (7 October 2016) from Fero Vineyards (Lewisburg, PA) was transported to the Department of Food Science at the Pennsylvania State University where it was stored for less than 48 hours at 3°C until processing (9 October 2016). Fruit lug weights were recorded to estimate grape yields. Each varietal was crushed and destemmed. For Lemberger, must was evenly distributed between two 10 gallon open-top, low density polyethylene fermentation bins

(Nalgene Nunc International, Waltham, MA), yielding approximately 7.5 gallons of must per bin.

For Riesling, juice was transferred into 5-gallon carboys, treated with pectic enzyme (2g/hL

Lallzyme C) and 50 mg/L SO2, and stored at 3°C for 24 hours for settling. Juice samples (50 mL) were removed from each replicate for TSS (°Brix) and yeast assimilable nitrogen [79] measurements. The Riesling juice was chaptalized with sucrose to achieve a TSS of 21°Brix, but no acid adjustment was performed on either varietal.

Each replicate was inoculated with Saccharomyces cerevisiae ICV-GRE yeast (Lallemand,

Petaluma, CA) for Lemberger, and Saccharomyces cerevisiae EC-1118 yeast (Lallemand,

Petaluma, CA) for Riesling, at a rate of 0.25g/L yeast with an additional 0.30 g/L of Go-Ferm nutrient (Lallemand, Petaluma, CA). Primary fermentation was carried out without external temperature control. Alcoholic fermentation was monitored daily by temperature readings using a K-type thermocouple (Fluke Corporation, Everett, WA), and TSS readings via hydrometer. For

Lemberger, pomace caps were punched down three times daily in addition to fermentation monitoring. At one-third sugar depletion, YAN adjustments were made with the addition of

Fermaid K nutrient to achieve 0.25 g/L. Riesling replicates were also dosed with diammonium phosphate (DAP) to achieve 0.25 g/L.

Once Brix measured below zero by hydrometry, an enzymatic reducing sugar assay

(Clinitest, Bayer AG, Leverkusen, Germany) was employed to confirm dryness, defined as < 1% residual sugar. Riesling replicates samples were collected (250 mL) for pH, titratable acidity

(TA), alcohol, volatile acidity (VA), free SO2 and total SO2 measurements. An aliquot of wine

(100 mL) was frozen at -80°C until further analysis could be performed. The 5-gallon carboys containing the Riesling wine were dosed to achieve 50 mg/L SO2 and held at 3°C for 48 hours for settling. The Riesling replicates were then racked and allowed to cold stabilize until bottling.

Lemberger replicates were pressed using a hydraulic stainless-steel basket press and transferred into 5-gallon carboys. Primary fermentation samples of Lemberger wine (250 mL) were collected for pH, titratable acidity (TA), alcohol and volatile acidity (VA) measurements.

The Lemberger replicates were inoculated with Oenococcus oeni Alpha MBR malolactic bacteria (Lallemand, Petaluma, CA) at a concentration of 105 CFU/mL for secondary malolactic fermentation (MLF). The progress of MLF was monitored by paper chromatography weekly.

Once MLF was complete, Lemberger wine samples (250 mL) were collected for pH, titratable acidity (TA), alcohol, volatile acidity (VA), free SO2 and total SO2 measurements. The

Lemberger was dosed to achieve 50 mg/L SO2 and stored at 3°C until bottling. Existing free SO2 concentrations were determined one day prior to bottling by the aeration oxidation method.

Wine was manually bottled (Prospero TSM2005-IC-PEC, Pleasantville, NY) into sanitized 750 mL clear glass bottles and sealed with a screw-cap closure. Bottled wine was stored in cases in cold storage at 3°C until analysis.

3.3.3 Juice and wine analysis

Titratable acidity was measured using an autotitrator (G20, Mettler Toledo, Columbus, OH).

Prior to TA measurements, samples were heated in warm water for 10 minutes, then sparged with nitrogen gas for 30 seconds to remove dissolved CO2. The 10 mL sample of juice or wine

was diluted to 40 mL with deionized water, titrated to a pH of 8.2 using 0.10 N sodium hydroxide, and resulting TA was recorded using tartaric acid equivalents (g/L).

Alcohol content (%v/v) in wines was determined using an ebulliometer (Laboratories

Dujardin-Salleron, Noizay, France). Volatile acidity (VA) was measured using Cash still distillation and reported as acetic acid equivalents. Total SO2 in the wine samples was determined using the Ripper method. Free SO2 was determined using the aeration oxidation method.

3.3.4 Simulated Protein Fining Experiments

In a 250 mL volumetric flask containing model wine (12% ethanol, pH 3.6), an aqueous solution of sodium hydrosulfide hydrate was added to achieve a final concentration of 0.1 mg/L

H2S, and was agitated for 1 min. An aqueous solution of CuSO4 was added to each flask to bring the final copper concentration to 1 mg/L, and also agitated for one minute. To each flask, the highest recommended dose of fining protein was added. The added concentration and protein composition of each fining treatment can be found below in

Table 3.1. The flasks were agitated for one minute and allowed to sit for 30 minutes. The solutions were transferred into 50 mL centrifuge tubes and then centrifuged (3220 x g for 12 min) and decanted. For each fining protein, 5 mL samples were filtered through a 0.45 μm PTFE syringe filter. Samples were collected after 1, 2, 3, 4 and 5 days. The resulting samples were digested and prepared for copper determination by ICP-OES as described in section Error!

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Table 3.1: Protein composition of various fining protein treatments and respective dose in mg/L added to model wine, as recommended by the manufacturer.

Fining Protein Protein Concentration (mg/L)

Goldenclar Gelatin 100

Finecoll Isinglass 40

Blancoll Egg Albumin 80

Plantis AF Plant (unspecified) 300

Plantis AF-P Potato 300

3.3.5 Simulated copper fining with bound Cu(II) in model wine

Model wine was prepared in volumetric flasks by dissolving tartaric acid (5 g/L) in water, followed by an addition of ethanol to result in a final concentration of 12% v/v. The solution was adjusted to pH 3.6 by the addition of sodium hydroxide and brought to volume with water. Thiol solutions of H2S were spiked into model wine as single additions to achieve final concentrations of 0.5 mg/L. CuO-Al particles, Cu(NO3)2-Cel and CuSO4 were subsequently added to achieve an effective dose of 1 mg/L Cu(II). Effective dose of Cu(II) was calculated by the molecular weight of the bound Cu(II) adsorbate (in this case, either CuO or Cu(NO3)2) plus the substrate

(Alumina, Al2O3 or Celite, SiO2) and corrected for CuO/Cu(NO3)2 content based on the extent of labeling, given as weight % loading by Sigma-Aldrich, which was 13% and 30%, respectively.

Model wine solutions containing the equivalent amounts of the respective inert substrates alumina and Celite were used as controls for the bound Cu(II) copper treatments, and model wine was used as a negative control.

3.3.6 Simulated copper fining with bound Cu(II) in real wine systems

Riesling and Lemberger vinified according to winemaking procedures described in section

Error! Reference source not found. were used for determination of the Cu concentration after t he addition of bound Cu(II) over 24 hours. Solutions of H2S were spiked into wine as a single addition to achieve final concentrations of 0.5 mg/L. CuSO4, CuO-Al particles and Cu(NO3)2-Cel were subsequently added to achieve a 1 mg/L concentration of Cu(II). Aliquots were collected at

1, 30, 60 min and 3, 6, 12, and 24 hours post-Cu addition. The collected samples were immediately centrifuged and filtered, and digestion of the filtrate was performed as described below in section Error! Reference source not found. prior to copper analysis. Digested s amples were analyzed for copper content by ICP-OES as described in section Error!

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3.3.7 Copper determination

Determination of the copper concentration in model wine, Riesling and Lemberger solutions was performed by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Prior to filtration, samples were centrifuged at 3220 x g for 10 minutes. For each treatment, 5 mL samples were filtered through a 0.45 μm PTFE syringe filter (0.45 μm, 13 mm filter diameter;

AcrodiscTM, Ann Arbor, MI). The resulting filtrate (5 mL) was digested by the addition of 30% hydrogen peroxide (3 mL) and sulfuric acid (100 μL) based on previously reported methodology.

The samples were heated in a convection oven at 110°C overnight before being reconstituted to

5 mL with 0.1 M nitric acid. Samples were analyzed using a Thermo Scientific iCap 6500 Duo

ICP-OES (Waltham, MA) with Cu monitoring at 324.754 nm axially and 371.030 nm radially, with an internal Yttrium standard to evaluate drift.

3.3.8 H2S and thiol reduction by bound Cu(II)

H2S and Cysteine (Cys), an aqueous stock solution of each (0.5 M) was freshly prepared, while

3-sulfanylhexan-1-ol (3SH) was added directly by syringe during experimentation (Figure 3.1).

Solutions of H2S and Cysteine (Cys), and direct addition of (3SH) were spiked into air-saturated model wine as single addition to achieve final concentrations of 300 μM, followed by thorough mixing. CuO-Al particles, Cu(NO3)2-Cel and CuSO4 were subsequently added to achieve a molar equivalent or 50 μM Cu(II) and thoroughly mixed. Model wine solutions containing the equivalent amounts of the inert substrates alumina and Celite were used as controls for the bound Cu(II) treatments, and model wine was used as a negative control. O SH S H H HS OH OH NH2

Hydrogen sulfide Cysteine 3-Sulfanylhexan-1-ol

Figure 3.1. H2S and thiols used throughout this study.

Experiments were performed under oxygen-ingress controlled conditions. Model wine solutions spiked with H2S/thiols was transferred to 60 mL glass Biological Oxygen Demand

(B.O.D.) bottles (Wheaton, Millville, NJ). The solutions were allowed to overflow during transfer, and the bottles were immediately capped with ground glass stoppers to eliminate any headspace. The B.O.D. bottles containing the solutions were stored in the dark at ambient temperature. For each time point per replicate, one B.O.D. bottle was sacrificed and used for analyses.

3.3.9 Spectrophotometric measurements of thiols and H2S

Determination of H2S and thiols loss was obtained by UV-VIS measurement over 200 – 700 nm using an Aglient 8453 UV-Vis spectrophotometer (Aglient, Santa Clara, CA). The concentration of H2S and thiols was determined using Ellman’s reagent (DTNB). An aliquot of sample (100 μL) diluted in model wine (900 μL) was treated with a solution of DTNB (400 μL, 2 mM) in phosphate buffer (10 mM, pH 7.0) followed by addition of TRIS-phosphate buffer (100

μL, 1 M, pH 8.1). The mixture was left at ambient temperature for 30 minutes before the absorbance was measured at 412 nm against a blank consisting of the relative proportions of model wine, DTNB solution and TRIS-phosphate buffer as stated above.

H2S/thiols were spiked into model wine to achieve a final concentration of 300 μM. Copper, in the form of CuSO4, CuOAl and Cu-Celite with effective Cu concentrations of 50 μM were spiked into the model wine solution after 5 minutes and mixed thoroughly. Samples were immediately collected upon Cu treatment additions and to establish time zero levels of

H2S/thiols. The experiment was conducted at room temperature, and samples were collected at

30 minutes, 1 hour, 3 hours, 12 hours and 24 hours for the study over 24 hours. Samples removed at 30 minutes and 24 hours during the H2S and Cys experiment were retained, frozen at -80°C and underwent ICP-OES analysis for determination of Cu concentration described in section. For the 4-hour time study, samples were similarly removed at 10, 30, 90, 120 and 240 minutes.

3.3.10 Statistical Analysis

Statistical analysis was performed by SPSS Statistics statistical software (IBM, version 25,

examine the effects of treatment and time on H2S/thiol concentration. Data are mean ± standard deviation, unless otherwise stated. For results which found statistically significant differences between treatment and time for H2S/thiol concentration or Cu concentration, an analysis of simple main effects for treatment and time on mean H2S/thiol or Cu concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported

95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Detailed reporting of two-way ANOVA and post-hoc test results can be found in Appendix C. 3.4 Results and Discussion

3.4.1 Protein fining as a method of copper removal in model wine

An effective dose of 1 mg/L Cu, in the form of CuSO4 was added to model wine solutions, and various fining proteins were then added to affect the final concentration of copper. The Cu concentration of the model wine solutions treated with various proteins, as determined by ICP-

OES after 30 minutes, can be found below in Figure 3.2 . It is important to note that the Cu concentration of the model wine solution containing 0.1 mg/L H2S was the lowest at 0.72 ± 0.03 mg/L Cu. This result is interesting, as it has previously been shown that Cu is able to favorably bind and form stable complexes with H2S [15]. The various forms of the complexes have been shown to be soluble in model wine conditions however, and would not be expected to precipitate.

Tukey post-hoc test indicated the initial Cu concentration in the Blancoll (0.81 ± 0.02 mg/L

Cu), Plantis AF (0.79 ± 0.03 mg/L Cu) and Plantis AF-P (0.79 ± 0.03 mg/L Cu) protein fining treated samples was significantly higher than in the control (0.72 ± 0.03 mg/L Cu), p <.033.

Thus, higher Cu concentrations are present in the model wine solutions containing these proteins when compared to Cu and H2S alone. This result may indicate that less effective

interactions immediately occur between the protein residues of Blancoll, Plantis AF and Plantis

AF-P and Cu in comparison to the control. It is known that H2S and Cu quickly bind to form stable complexes in model wine; reaction or diffusion of Cu-S complexes to the residues may be slow or reversible, causing dissociation of the Cu or Cu-S back into the model wine solution. No statistically significant differences were observed in initial Cu concentration between the control,

Goldenclar (0.74 ± 0.02 mg/L Cu) or Finecoll (0.77 ± 0.02 mg/L Cu), p > .123, or between the

Goldenclar, Finecoll, Plantis AF and Plantis AF-P, p > .168. The initial Cu concentration of

Finecoll, Blancoll, Plantis AF and Plantis AF-P treated samples was not found to be statistically different, p > .352.

Figure 3.2 Initial Cu Concentration 30 minutes after protein fining. Different letters indicate statistical significance by one-way ANOVA. One-way ANOVA revealed statistically significant differences between treatments.

The results of the protein fining treatment after five days are shown in . After five days of protein fining, decreases in the Cu concentration of the treatments were observed. Statistically significant differences in the Cu concentration between treatments was observed. A Tukey post hoc test revealed that Cu concentration in the 1 mg/L Cu control (0.79 ± 0.03 mg/L Cu) and 1 mg/L + 0.1 mg/L H2S (0.74 ± 0.06 mg/L Cu) samples were significantly higher than in the

Goldenclar (0.68 ± 0.03 mg/L Cu), Finecoll (0.65 ± 0.00 mg/L Cu), Blancoll (0.61 ± 0.01 mg/L

Cu), Plantis AF (0.69 ± 0.02 mg/L Cu) and Plantis AF-P (0.61 ± 0.00 mg/L Cu), p <.011.

Approximately a ~20 – 25% decrease in Cu concentration was observed after five days.

Although the duration of time required to observe a statistically significant decrease is relatively long for a fining operation, a 23 – 25% decrease in concentration of the powerful catalyst Cu could have a significant impact on the sensory properties of wine. No significant statistical differences were found between the 1 mg/L Cu and 1 mg/L Cu + 0.1 mg/L H2S sample, p >

.264, indicating the presence of H2S did not significantly impact the overall Cu concentration in model wine after 5 days. No significant statistical differences were found in the Cu concentration after five days between Goldenclar, Finecoll, Blancoll and Plantis AF-P treated samples, p >

.111, indicating these proteins had similar affinity for Cu removal. Additionally, no significant statistical differences were found in the Cu concentration after five days between the 1 mg/L Cu

+ 0.1 mg/L H2S sample and Goldenclar, Finecoll and Plantis AF, p> .066. This result indicates that these treatments did not result in statistically significant decreases in Cu concentration when compared to the 1 mg/L Cu + 0.1 mg/L H2S sample, which had no fining protein added.

Figure 3.3. Concentration of Cu five days after a 1 mg/L Cu addition in the presence of various fining proteins, as determined by ICP-OES. Different letters indicate statistical significance by one-way ANOVA, which revealed statistically significant difference between protein fining treatments for Cu concentration in model wine after five days (F(7,23) = 223.759, p < .001).

The more successful of these treatments appear to be Blancoll, which as shown in

Table 3.1 is primarily composed of egg albumin and resulted in a decrease of 0.20 ± 0.01 mg/L Cu concentration and Plantis AF-P, primarily composed of potato protein, which resulted in a decrease of 0.18 ± 0.03 mg/L Cu concentration. It is important to note that the concentration of the 1 mg/L Cu control had decreased by ~20% over the five-day study. It is possible that a

fraction of the Cu(II) had precipitated and was removed by filtration prior to digestion of the samples and subsequent analysis by ICP-OES.

Factors that impact the ability of fining proteins to interact with wine constituents include its isoelectric point (pI), peptide chain length, composition of primary amino acid residues, conformational flexibility and solubility, and characteristics related to hydrophobicity such as bloom. If an isoelectric point of a protein is greater than the pH of juice or wine, the protein will occur as a positively charged entity, capable of interacting with negatively charged species via hydrogen-bond formation. Bloom refers to the ability of a protein to absorb water; higher bloom ratings indicate greater absorption capability. Because the number of bonding sites determines effectiveness, larger molecular weight proteins may increase bonding. The selectivity of proteins for Cu and Cu-sulfide depends on the optimal type, placement, and geometry of bonding sites to give a stronger total bonding with a Cu-thiol species. Larger Cu-S complexes may have more groups and therefore more hydrogen bonding potential. Solubility and flexibility of the protein in order to align itself with Cu and Cu-S complexes is a key aspect in order to provide a good fit.

Soluble proteins have greater capacity for removal over insoluble agents, due to greater surface area available for interactions.

Goldenclar is a mostly comprised of gelatin (60 kDa, pI = 4.8, 4.85) and has a bloom number on the order of 6 -10 times its weight [89]. The higher proportion of proline and hydroxyproline in gelatin is related to water exclusion and clumping behavior, and confer rigidly on the collagen molecule of gelatin by permitting the sharp twisting of the collagen helix [116].

Blancoll is comprised of egg albumin, which is comprised of 50% ovalbumin (46 kDa, pI = 4.55,

4.90) and 15% conalbumin (87 kDa, pI = 6.8, 7.1) [89]. Finecoll is comprised of isinglass, (pI of

4.50, 4.80) [89] . Plantis AF is comprised of unspecified, non-gluten plant protein. Plantis AF-P is pure potato protein. Patatin, the primary protein in potatoes consists of 39 - 45 kDA

glycoproteins with a pI value of 4.6 [103]. A previous study found that albumin and patatin exhibited similar efficacy in the removal of polyphenols from wine, and indicated the similar size and pI of the two proteins may be responsible for this observation [103]. This result was similar obtained in this study, with similar efficacy between Blancoll (albumin) and Plantis AF-P

(patatin).

Competition between positively charged H+ ions with the copper ions and copper-thiol complexes for binding sites on the proteins may have occurred and prevented binding of Cu to amino acid residues, as all of the proteins will have a net positive charge at wine pH (~3.3 –

3.6). Increased pH (i.e. fewer H+ ions) would result in more binding sites being open for the copper ions and copper-ion complexes, resulting in an enhanced absorption of these species. It is hypothesized that the solution pH and isoelectric point are important variables in copper removal by proteins, as the H+ ions will act as competitors for sorption by the protein, and the metal speciation in solution is highly dependent on pH. In a study using marine algal biomass to adsorb heavy metals including copper in aqueous solution, it was confirmed that carboxyl, ether, alcoholic and amino groups were responsible for binding the metal ions [117]. The wide variety and complexity of amino acid residues in fining proteins may similarly participate in a variety of metal-binding mechanisms, such as ion exchange, complexation, coordination, and microprecipitation [117]. It was initially hypothesized that interactions between Cu and Cys residues in the protein could be responsible for the removal of Cu, however egg albumin is comprised of relatively small amounts of Cys, with 6% Cys residues present in the amino acid sequence of albumin, and approximately 1% Cys in patatin [118] [119]. Thus, this theory was not supported by the amino acid composition of these proteins. As mentioned, previous studies suggest that other factors such as protein size and pI are more predictive of the ability for Cu

removal, and were responsible for the increased interactions between Cu and the fining proteins

Blancoll and Plantis AF-P that were observed in this study.

3.4.2 Copper Determination of Bound Cu(II) in Model Wine

A simulated copper fining using bound Cu(II) in model wine was performed. The Cu concentration of the bound Cu(II) particles and their analogous inert substrates was determined by ICP-OES in model wine and the results are shown in Figure 3.4. An effective Cu concentration of 1 mg/L Cu of CuSO4, CuOAl and CuCelite was added to model wine to simulate conditions that may occur in real wine systems and allowed to react for 30 minutes after the addition of the treatment. Global limits legal limits for Cu are in the range of 0.5 – 1 mg/L, but may be as high as 10 mg/L [87]. The inert substrates were evaluated to determine their impact on the Cu concentration in model wine. The results revealed statistically significant differences between treatments. The addition of CuSO4, which intends to simulate a typical copper fining operation, resulted in a Cu concentration of 0.90 ± 0.01 mg/L, a respectively large concentration compared to the Cu concentrations of 0.040 ± 0.001 mg/L observed in CuCelite and .009 ± .004 mg/L Cu mg/L observed in the CuOAl in the model wine solution. The large concentration of CuSO4 was expected, as it is highly soluble in model wine under the experimental conditions (no precipitate was observed during the timeframe of the experiment).

Although the Cu concentration of the CuCelite treatment did result in a statistically significant higher Cu concentration than the control (.006 ± .003 mg/L Cu), or CuOAl (.009 ± .004 mg/L

Cu), relative to the concentration of the CuSO4 it was much less. However, this result could indicate that CuCelite results in more dissociation of the Cu and was investigated further.

Because the CuCelite had a statistically significantly lower Cu concentration than the CuSO4 treated sample, it was still considered to be an appropriate bound Cu(II) candidate for further fining experiments.

Overall, the results from this study indicated that Cu was not dissociating from the bound

Cu(II) particles and leaching into the model wine solution after 30 minutes. This indicates that the bound Cu(II) particles may be an appropriate replacement for traditional Cu fining, where large concentrations of residual Cu remain in the wine post-fining. Additionally, it was observed that the inert substrate alone (to which the Cu(II) is bound) did not have an effect on the copper concentration in the model wine solution (i.e. no statistically significant differences in Cu concentration were revealed between the model wine and the inert substrates).

Figure 3.4. Cu concentration determined by ICP-OES 30 minutes after the addition of CuSO4, Bound

Cu(II) particles and analogous inert substrates to model wine. An effective Cu concentration of 1 mg/L

Cu(II) of CuSO4, CuOAl and CuCelite was added to simulate conditions in real wine systems. Different letters indicate statistical significance by one-way ANOVA. There was a statistically significant difference between groups for initial Cu concentration in model wine as determined by one-way ANOVA, F(5,17) =

13836.316, p < .001. A Tukey post hoc test revealed that initial Cu concentration in the CuSO4 treated sample (.89 ± .01 mg/L Cu) was found to be significantly higher than the control CuOAl, alumina (.006 ±

.003 mg/L Cu), CuCelite (.040 ± .001 mg/L Cu) p < .001. Error bars indicate standard deviation of triplicate measurements.

3.4.3 Simulated Copper Fining with Bound Cu(II) Particles in Real Wine Systems

A simulated copper fining process using bound Cu treatments was performed in real wine systems, with Riesling representative of white wine and Lemberger representative of red wine.

An effective Cu concentration of 1 mg/L of CuSO4, CuOAl and CuCelite was added to the real wine system at concentrations that are consistent with values reported in real wine [87]. The resulting Cu concentration in the wine treated with CuSO4, CuOAl and CuCelite was monitored over 24 hours, with samples removed 1 minute, 30 minutes, 1 hour, 3 hours, 6 hours, 12 hours and 24 hours. Samples were then digested and analyzed for Cu concentration using ICP-OES, as described in section 3.3.7.

3.4.3.1 Bound Cu(II) in Riesling over 24h

The Cu concentration in Riesling wine treated with bound Cu(II) particles or CuSO4 was measured over 24 hours, with time points at 1 minute, 30 minutes, 1 hour, 3 hours, 6 hours, 12 hours and 24 hours, the results of which are found in

Figure 3.5. An effective Cu concentration of 1 mg/L Cu of CuSO4, CuOAl and CuCelite was added to Riesling at concentrations that are consistent with values reported in real wine. There was a statistically significant difference in Cu concentration between treatments at all time points. As expected, the CuSO4 treatment resulted in the greatest final Cu concentration at all time points, ranging from the largest Cu concentration of 0.72 ± 0.05 mg/L at 1 minute to the lowest concentration of 0.59 ± 0.11 mg/L Cu at 1 hour. It should be noted that the cause of the apparent decrease in Cu concentration observed in the CuSO4 treatment between 1 minute and

1 hour is unknown, but due to the large standard deviation associated with the Cu concentration measurements at 1 hour, little weight can be attributed to this phenomenon without further

investigation. The main effect of treatment differences observed in the mean Cu concentration between treatments in

Figure 3.5 are statistically significant, p < .001. On average over all time points, the Cu concentration of the CuSO4 was associated with a Cu concentration 0.27 mg/L greater than the

CuOAl and 0.51 ± 0.04 mg/L greater than CuCelite. This correlates to a 41% greater average

Cu concentration in the CuSO4 compared to the CuOAl, and a 77% greater average Cu concentration in the CuSO4 compared to the CuCelite.

For both the control and the CuCelite, there was not a statistically significant difference in mean Cu concentration between time points, illustrating the concentration of Cu for the control and CuCelite treatment did not change significantly between time points. The CuCelite had an average Cu concentration of 0.148 ± 0.006 mg/L over the 24-hour period, and the control had an average Cu concentration of 0.085 ± 0.005 mg/L over the 24-hour period. This indicates that the Cu concentration in the CuCelite treatment did not increase significantly, and thus the Cu did not dissociating from its Celite substrate under real white wine conditions. However, statistically significant differences in mean Cu concentration between time points were observed for CuSO4 and CuOAl, p < .001. Thus, the Cu concentration changes significantly between time points for these treatments. As observed in

Figure 3.5, there is a clear increase in the Cu concentration over time observed in the

CuOAl. This indicates that the Cu must be dissociating from the alumina substrate under real wine conditions. The largest increase in Cu concentration was observed between 1 hour and 2 hours, where the Cu concentration increased from 0.32 ± 0.02 mg/L to 0.53 ± 0.01 mg/L, which is a 1.6-fold increase. The increase in Cu concentration observed between these two time points for CuOAl is almost as great as the overall difference between the average Cu concentration of CuOAl compared to CuSO4, where a 1.7-fold increase in average Cu

concentration was observed between the two treatments. It is unknown what mechanisms are responsible for the large increase in Cu concentration at these time points, but it may be due to unbound CuO powder present on the surface of the alumina bead, which may dissolve and achieve equilibrium in wine conditions. Although CuO is virtually insoluble in water and alcohol, it is readily soluble in strong acid solutions [120], and the low pH (~3.3 – 3.6) of the Riesling may be responsible for the observed increase in concentration.

Although a traditional Cu fining process may occur over 24 hours before filtration or racking, typically the reaction between Cu and H2S has been observed to occur rapidly and a reduction in H2S can be perceived after a few hours. Because the bound Cu(II) treatments are not aqueous solutions (such as CuSO4), but rather are solid powders and beads, these treatments are able to be physically removed from wine after a certain duration of time, thus having the potential to limit the residual Cu concentration to the maximum observed at that time point.

1.0 Control 0.8 CuSO4

0.6 CuOAl CuCelite 0.4

0.2 Cu Concentration (ppm) 0.0 0 2 4 6 8 10 12 24 Time (hours)

Figure 3.5. Cu concentration as determined by ICP-OES after the addition of 1 mg/L CuSO4 or bound Cu(II) treatment in Riesling over 24 hours. A two-way ANOVA was conducted to examine the effects of treatment and time on Cu concentration. There was a statistically significant differences

between treatment and time for Cu concentration, F(18, 140) = 13.337, p < .001, partial η2 = .632. For some points, the error bars are shorter than the height of the symbol and they have not been drawn.

3.4.3.2 Bound Cu(II) in Lemberger over 24h

Bound Cu treatments and the resulting Cu concentration was evaluated in Lemberger, a red wine, in addition to the white wine Riesling. Red wines have substantial differences in comparison to white wines, specifically in regards to total phenolics and tannins, with approximately ten times greater amounts observed in red versus white wines. The greater concentration of phenolics in red wine have the potential to interact with the bound copper treatments, through binding or reaction, which may prevent the interaction between bound Cu and H2S/thiols, the primary targets of copper fining which the bound Cu treatments aim to remove. The presence of substantially greater phenolic content and subsequent complexation with Cu may result in lower effective bound Cu concentrations. The solution phase concentrations of Cu in Lemberger were monitored over time with CuOAl, CuCelite and CuSO4 treatments. The results are found in Figure 3.6. An effective Cu concentration of 1 mg/L Cu(II) of

CuSO4, CuOAl and CuCelite was added to Lemberger in concentrations that may occur in real wine systems. At all of the time points, there was a statistically significant difference between the treatments. Overall, CuSO4 resulted in the greatest increase in Cu concentration that was

0.693 mg/L higher than the control, 0.662 mg/L greater than the CuCelite and 0.443 mg/L higher than the CuOAl. This result is expected, and the majority of the CuSO4 exist in soluble forms in wine, and both bound Cu(II) treatments resulted in lower Cu concentrations in comparison.

Following similar trends observed in the Riesling, the CuOAl treatment resulted in a greater Cu concentration than the CuCelite, and was found to be 0.218 mg/L greater than Celite. The Cu concentration of CuCelite and CuOAl were statistically significantly higher than the control.

Figure 3.6. Cu concentration as determined by ICP-OES after the addition of 1 mg/L CuSO4 or bound Cu(II) treatment in in Lemberger over 24 hours. A two-way ANOVA was conducted to examine the effects of treatment and time on Cu concentration. There was a statistically significant difference between treatment and time for Cu concentration, F(18, 140) = 44.121, p < .001, partial η2 = .850. For some points, the error bars are shorter than the height of the symbol and they have not been drawn.

3.4.4 Reduction of thiols and H2S by bound Cu(II)

The reactivity of Cu(II) with H2S in the form of CuSO4 in comparison to the bound Cu(II) treatments, CuOAl and CuCelite, as well as other thiols was assessed under model wine conditions. The model wine was first air-saturated, and then oxygen-ingress was controlled after transfer of model wine to B.O.D. bottles, as detailed in section 3.3.8. H2S was investigated as it is the primary target for copper fining operations. The other thiols under investigation include

Cys, representative of homo-Cys and Cys derivatives and 3SH to represent secondary thiols.

H2S/thiol concentrations were measured over 4 hour and 24 hour periods to determine extent of

H2S/thiol removal by CuSO4 and bound Cu. It was expected that a difference in reactivity of

H2S, Cys and 3SH would be observed, with reaction rates related to the availability of -SH

moiety. H2S, as a reducing agent, was expected to react quickly, followed by Cys, with the accessibility of its primary thiol, followed by 3SH, a secondary thiol.

3.4.4.1 H2S Reduction by Bound Cu(II) over 4h

The results for H2S removal by bound Cu(II) can be found in Figure 3.7. The addition of

CuSO4 to model wine containing H2S resulted in a loss of ~1.3 (64 µM) mole equivalents of H2S, and the remaining free H2S was decreased to a concentration of 50 µM at 4 hours. This is similar to the observation in previous studies, Cu(II) addition to H2S resulted in an immediate

~1.4 (74 µM) mole equivalent loses [15]. The bound Cu(II) treatments CuCelite and CuOAl resulted in initial loss of 56 and 57 µM H2S, respectively. However, CuOAl proved to be more effective at H2S removal than CuCelite, with only 46 µM H2S remaining after 4 hours compared to 140 µM remaining in the CuCelite treated model wine.

500 H2S 400 CuSO4 300 CuOAl CuCelite 200

100 S Concentration (uM) 2 H 0 0 60 120 180 240 Time (min)

Figure 3.7. Loss of H2S in oxygen-ingress controlled model wine experiments upon addition of Cu(II)

(50 µM) in the form CuSO4 and bound Cu(II) treatments to H2S (300 µM) over 4 hours.

3.4.4.2 Cys Reduction by Bound Cu(II) over 4h

100

The reduction of Cys by bound Cu is investigated, with the compound Cys functioning as a representative of the homocys and Cys derivatives that are present in large concentrations in wine. The combined concentration of Cys, N-acetylcysteine and homocysteine is reported to be

20 µM in white wine, and glutathione (GSH) is present in concentrations of approximately 40 µM in Sauvignon blanc. These non-volatile thiol compounds are typically present in large molar excess of the Cu concentration (3-6 µM) added during copper fining operations [94]. The concentration of H2S would be significantly less, being present at approximately 300 nM in wine

[15]. These non-volatile thiols could interfere with removal of detrimental VSCs and their interaction with bound Cu was evaluated. The results for Cys removal by bound Cu(II) can be found in Figure 3.8. The addition of CuSO4 resulted in a loss of ~1.4 (65 µM) mole equivalents of

Cys after 10 minutes, the remaining free Cys was decreased to a concentration of 38 µM after 4 hours. These results are similar to those observed in previous studies, with the addition of Cu(II) resulting in a slightly greater 2 (101 µM) mole equivalents of Cys [15]. CuOAl resulted in a loss of 65 µM Cys at 10 minutes, and a loss of 95 µM at 30 minutes. CuCelite resulted in minimal initial losses of Cys at 10 minutes, but at 30 minutes resulted in a loss of 104 µM of Cys. Both

CuOAl and CuCelite were effective at Cys removal after 4 hours, with only 67 µM and 64 µM remaining, respectively after 4 hours.

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500 Cys 400 CuSO4 300 CuOAl CuCelite 200

100 Cys Concentration (uM) 0 0 60 120 180 240 TIme (min)

Figure 3.8. Loss of Cys in oxygen-ingress controlled mode wine experiments upon addition of bound

Cu(II) treatments over 4 hours.

3.4.4.3 3SH Reduction by Bound Cu(II) over 4h

The compound 3-sulfanylhexan-1-ol (3SH) is a grape-derived varietal thiol in wine and was chosen as a representative for the evaluation of varietal thiol removal by bound Cu. Copper fining operations can result in significant losses of beneficial thiols such as 3SH that provide positive sensory attributes and contribute to the character of wine. The results for 3SH removal by bound Cu(II) can be found in Figure 3.9. The addition of CuSO4 resulted in a loss of ~0.8 (40

µM) molar equivalents of 3SH at 10 minutes, the remaining SH was decreased to a concentration of 38 µM after 4 hours. These results are similar to those previously reported, with slower reaction times between Cu and 3SH in comparison to Cys or H2S. After 2 hours, CuSO4 resulted in removal of 140 µM, or ~2.8 mole equivalents of 3SH. Previously reported results had observed the removal of ~2 mole equivalents after 2 hours [15]. The bound Cu(II) treatments

CuCelite and CuOAl resulted in initial losses of 56 µM and 57 µM SH, respectively. Both CuOAl and CuCelite were effective at Cys removal, with only 67 µM and 64 µM remaining after 4

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hours. CuCelite was observed to be more effective at 3SH removal overall, and exhibited greater interactions with 3SH over CuOAl for all time points.

400 3SH

300 CuSO4 CuOAl 200 CuCelite

100 3SH Concentration (uM) 0 0 60 120 180 240 Time (min)

Figure 3.9. Loss of 3SH in oxygen-ingress controlled mode wine experiments upon addition of bound

Cu(II) treatments over 4 hours.

3.4.4.4 H2S Reduction by Bound Cu(II) over 24h

The results for H2S removal by bound Cu(II) cover 24 hours can be found in Figure 3.10.

The addition of CuSO4 to model wine containing H2S resulted in a loss of ~1.3 (66 µM) mole equivalents of H2S at 10 minutes, indicating faster reaction than the bound Cu(II) treatments.

The bound Cu(II) treatments CuCelite and CuOAl resulted in minimal initial loss of H2S at 10 minutes, but increased uptake to ~2 (103 µM) mole equivalents and 0.8 (36 µM) mole equivalents at 30 minutes, respectively. After 10 hours, the consumption of H2S was the greatest by CuSO4, with 261 µM of H2S uptake, a ~5 molar equivalent. In comparison, the consumption of H2S by CuOAl was ~2.5 (188 µM) mole equivalents, and ~3.5 (141 µM) mole equivalents for CuCelite. At 24 hours, the amount of H2S present in the CuSO4 treatment was

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reduced to 38 µM. CuCelite and CuOAl proved to be similarly effective at H2S removal, with 64

µM and 67 µM H2S remaining after 24 hours.

400 H2S CuSO 300 4 CuOAl 200 CuCelite

100 S Concentration (uM) 2 H 0 0 1 2 3 4 10 24 Time (hours)

Figure 3.10. Loss of H2S in oxygen-ingress controlled mode wine experiments upon addition of bound Cu(II) treatments over 24 hours.

3.4.4.5 Cys Reduction by Bound Cu(II) over 24h

The results for Cys removal by bound Cu(II) cover 24 hours can be found in Figure 3.11.

The addition of CuSO4 to model wine containing Cys resulted in a loss of ~3.2 (161 µM) mole equivalents at 30 minutes, indicating faster reaction than the bound Cu(II) treatments. The bound Cu(II) treatments CuCelite resulted in Cys uptake of ~1.2 (62 µM) mole equivalents at 30 minutes. Significant decreases in Cys were not observed in CuOAl treatments until 2 hours, where the loss of Cys was ~2.9 (144 µM) mole equivalents. After 10 hours, the consumption of

Cys was the greatest by CuSO4, with a loss of 255 µM, a ~5 molar equivalent, similar to observations in Cys. In comparison, the consumption of Cys by CuOAl was ~3.5 (178 µM) mole equivalents, and ~4 (98 µM) mole equivalents for CuCelite. At 24 hours, the amount of Cys

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present in the CuSO4 treatment was reduced to 45 µM. CuCelite and CuOAl proved to be similarly effective at Cys removal, with 65 µM and 64 µM H2S remaining after 24 hours.

500 Cys 400 CuSO4

300 CuOAl CuCelite 200

100 Cys Concentration (uM) 0 0 1 2 3 4 10 24 Time (hours)

Figure 3.11. Loss of Cys in oxygen-ingress controlled mode wine experiments upon addition of bound Cu(II) treatments over 24 hours.

3.4.4.6 3SH Reduction by Bound Cu(II) over 24h

The results for 3SH removal by bound Cu(II) cover 24 hours can be found in Figure 3.12.

The addition of CuSO4 to model wine containing 3SH resulted in a loss of ~1.2 (60 µM) mole equivalents at 30 minutes, indicating similar reaction rates to the bound Cu(II) treatments. The bound Cu(II) treatment CuCelite resulted in Cys uptake of ~1.3 (65 µM) mole equivalents at 30 minutes, whereas CuOAl resulted in Cys uptake of ~ 0.8 (40 µM) mole equivalents. After 10 hours, the consumption of Cys was the greatest by CuSO4, with a loss of 224 µM, a ~4.5 molar equivalent, similar to observations in H2S and Cys. In comparison, the consumption of 3SH by

CuOAl was ~3.1 (155 µM) mole equivalents, and ~3.5 (175 µM) mole equivalents for CuCelite.

At 24 hours, the amount of 3SH present in the CuSO4 treatment was reduced to 64 µM.

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CuCelite and CuOAl proved to be less effective at Cys removal, with 89 µM and 112 µM H2S remaining after 24 hours.

400 3SH CuSO 300 4 CuOAl 200 CuCelite

100 3SH Concentration (uM) 0 0 1 2 3 4 10 24 Time (hours)

Figure 3.12. Loss of 3SH in oxygen-ingress controlled mode wine experiments upon addition of bound Cu(II) treatments over 24 hours.

3.4.4.7 Comparison of Each Treatment on Efficacy of H2S/Thiol Removal

A comparison of each treatment and its resulting efficacy of H2S, Cys and 3SH removal are shown below in Figure 3.13 for CuSO4, Figure 3.14 for CuOAl and Figure 3.15 for CuCelite. As expected, the reaction rate is relatively rapid for H2S and Cys, and relatively slower for 3SH.

This has been seen in previous studies in air saturated model wine [15]. Uptake of the H2S after

10 minutes by Cu(II) was shown to be ~1.4 mole equivalents. The Cys and 3SH uptake was determined to be ~1.3 and ~0.8 mole equivalents respectively. The uptake of Cys and 3SH by

Cu(II) is slower than what was seen previously, but faster reaction rates were seen for H2S .

However, after 30 minutes, the concentration of Cys decreased significantly. After 4 hours, H2S and Cys were almost entirely (87 – 90%) consumed, with SH not fully (73%) reacted. This

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treatment resulted in the most complete removal of all thiol compounds in comparison to bound

Cu(II).

CuSO4 400 H2S

300 Cys 3SH 200

100 S/Thiol Concentration (uM) 2 0 H 0 60 120 180 240 Time (min)

Figure 3.13. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for oxygen-ingress controlled model wine experiments for samples treated with CuSO4.

The efficacy of the CuOAl treatment is shown below in Figure 3.14. As shown, the CuOAl showed virtually complete removal of H2S and Cys after 4 hours, with less reactivity with 3SH. It is possible that the 3SH interaction with Cu(II) was limited to less available reaction sites on the surface of the bead. Uptake of H2S, Cys and 6SH after 10 minutes by Cu(II) was shown to be

~1.1 (65 µM) mole equivalents. After 30 minutes, the uptake of H2S, Cys and 6SH increased to

~1.9 (95 µM) mole equivalents. This treatment effectively removed H2S and Cys, with 87% and

79% consumption after 4 hours, respectively. The trends observed in the CuOAl removal of H2S and Cys after 4 hours was similar in reactivity of CuSO4. Unlike CuSO4, 3SH was not as effectively removed after 4 hours. The CuOAl resulted is only a 37% (115 µM) consumption of

3SH after 4 hours.

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CuO-Alumina

400 H2S

300 Cys 3SH 200

100 S/Thiol Concentration (uM) 2 0 H 0 60 120 180 240 Time (min)

Figure 3.14. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for oxygen-ingress controlled model wine experiments for samples treated with CuOAl.

The efficacy of the CuCelite treatment determined for H2S, Cys and 3SH is found in Figure

3.15. CuCelite was extremely effective in the removal of Cys, with less reactivity observed with

H2S and 3SH over 4 hours. This is unexpected, based on previous studies in real wine systems.

The initial removal by CuCelite at 10 minutes is minimal for H2S, Cys and 3SH. However, after

30 minutes, the uptake of H2S and Cys by Cu(II) was shown to be ~2 mole equivalents. At 30 minutes, the uptake of 6SH was shown to be 1.3 (66 µM) mole equivalents. After 4 hours, the

CuCelite resulted in the removal of 80% Cys, similar to observations in the extent of removal by

CuOAl. Less H2S and 6SH were removed in comparison, with 62% and 50% consumed, respectively.

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Cu(NO3)2-Celite 400 H2S

300 Cys 3SH 200

100 S/Thiol Concentration (uM) 2 0 H 0 60 120 180 240 Time (min)

Figure 3.15. Comparison of the concentration of Thiols/H2S determined by Ellman’s reagent for oxygen-ingress controlled model wine experiments for samples treated with Cu-Celite.

The results from the determination of Cu concentration of the bound Cu(II) treatments investigated in the H2S reduction experiment, which is discussed in section Error! Reference s ource not found., can be found below in Figure 3.16. Surprisingly, the Cu concentration among the bound Cu(II) treatments is significant. The CuSO4 treatment resulted in increased Cu(II) concentrations in the model wine solutions containing H2S, with 50% of the total Cu(II) added detected at 30 minutes and 81% detected at 24 hours. The CuOAl resulted in lower final Cu concentrations among the bound Cu(II) treatments, with ~2% of the Cu concentration detected at 30 minutes, which increased to 36% at 24 hours. The CuCelite had 60% total Cu(II) at 30 minutes and 75% at 24 hours. The efficacy of H2S removal observed at those time points must be attributed in part to an increased free Cu(II) concentrations present in the bound Cu(II) treatments that is able to participate in reactions with H2S. It can be concluded that the Cu(II) partially dissociated from its inert substrate and was able to react with H2S. Because the

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concentration of the CuOAl bead was relatively low and successful at uptake of H2S, it requires further investigation to better understand the dissociation of CuO-Alumina.

50 Control 40 CuSO4 30 CuOAl CuCelite 20

10 Cu Concentration (uM) 0

Control CuSO CuOAl CuCelite

Figure 3.16. Cu Concentration determined by ICP-OES, from samples collected during the oxygen- ingress controlled H2S experiment at 30 minutes and 24 hours.

The determination of Cu concentration of the bound Cu(II) treatments investigated in the 24- hour Cys reduction experiment, which is discussed in section Error! Reference source not f ound. can be found below in Figure 3.17. Similar to results obtained from the H2S experiment, the Cu concentration among the bound Cu(II) treatments is greater than expected in comparison to results obtained from experiments performed in real wine. The CuSO4 treatment resulted in increased Cu(II) concentrations in the model wine solutions containing H2S, with 63% of the total Cu(II) added detected at 30 minutes and 51% detected at 24 hours. The CuOAl had the lowest free Cu concentration among the bound Cu(II) treatments, with >1% of the Cu concentration detected at 30 minutes, which increased to 38% at 24 hours. The CuCelite had

50% total Cu(II) at 30 minutes and 47% at 24 hours. It can be concluded that the increased Cu concentrations indicates Cu(II) partially dissociated from its inert substrate and was able to react

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with Cys. The efficacy of Cys removal observed at those time points must be attributed in part to an increased free Cu(II) concentrations present in the bound Cu(II) treatments that is able to participate in reactions with Cys. As seen with H2S, the concentration of the CuOAl bead was relatively low and successful at Cys uptake, it requires further investigation to better understand the dissociation of CuO-Alumina.

50 Control 40 CuSO4

30 CuOAl CuCelite 20

10 Cu Concentration (uM) 0

Control CuSO CuOAl CuCelite

Figure 3.17 Cu Concentration determined by ICP-OES, from samples collected out of BOD bottles from Cys experiment at 30 minutes and 24 hours.

3.4.5 Concluding Remarks

The differences of H2S, Cys and 6SH removal between CuSO4 and bound Cu(II) treatments may be due to form of the substrate in which Cu(II) is bound impacting diffusion of the thiols to

Cu(II) reaction sites. The CuOAl used in this study is in the form of 14-20 mesh alumina beads, with 9 - 11 wt % labelling of CuO. The CuCelite comes in the form of powder, with 28 - 34 wt%

Cu(NO3)2 on Celite. The extent of labeling for the bound Cu(II) in CuOAl is less than CuCelite,

13% versus 30%, respectively. Although the amount of added “effective Cu(II)” for CuSO4,

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CuOAl and CuCelite was equivalent (50 µM), the form of the Cu(II) added to model wine solutions will have a large impact on reactivity. CuCelite is a powder, and has a significantly larger surface area than the alumina beads. Surface area is often correlated with rates of dissolution and other rate-related phenomena such as catalyst activity. Because of the detection of Cu(II) by ICP-OES observed in Figure 3.16 and Figure 3.17, further investigation into the immobilization mechanism of CuOAl and CuCelite must be performed, in order to obtain a greater understand of the exact bonding nature of the Cu(II) on the substrate. The nature of the bonding, where the attachment of Cu(II) to the substrate is by physisorption, through weak van der Waals forces, or chemisorption, through covalent bonding, will have an impact on the ability for the Cu(II) to dissociate from the inert substrate into the model wine.

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Chapter 4

Conclusions and Future Work

4.1 Summary

Several novel processing methods were investigated as means to improve wine quality with respect to oxidative stability. The use of novel maceration techniques (cryogenic maceration, extended skin contact) were shown to be promising for the production of high quality, shelf stable white hybrid wines. An assessment of the impact of the CM and ESC treatments on properties of juices, musts, and wines made from Cayuga and Traminette gave greater insight into how these techniques contribute to quality parameters that are unique to hybrid grape varieties. The improved understanding of these treatments in hybrid grapes, which are of significant economic and agricultural value to the Pennsylvania wine industry, will allow winemakers to incorporate novel methods for quality improvement.

Decreases in Cu concentration were observed in the protein fining treated model wine, with a 23-25% reduction in the Cu concentration observed in the Blancoll and Plantis AF-P protein treatments after five days. Although reduction in Cu concentration occurred only after a relatively long duration of contact time, these results indicate that the use of fining proteins may be a promising avenue to pursue for Cu removal in real winemaking applications and warrants further study. In addition, further investigation into other alternative methods is warranted due to the detrimental effects of residual Cu(II) in wine. Two bound Cu(II) forms, CuO-Alumina and

Cu(NO3)2-Celite, were shown to successfully decrease the concentration of H2S, Cys and 3SH

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under oxygen-ingress controlled model wine conditions over 4 and 24-hour time periods.

Although it appears the dissociation of Cu from the bound form into the model wine and wine may occur, these materials have shown to provide a simple and effective method for H2S and thiol removal for short durations of time. Overall, these novel techniques are of considerable importance to the winemaker and wine researcher, for both practical incorporation into

Pennsylvania wineries and for continued strides toward a deeper understanding of methods to enhance quality and shelf life of wine. 4.2 Future work

4.2.1 Further investigation of the effects of maceration treatments

The investigation of the cryogenic maceration and extended skin contact treatments in

Cayuga and Traminette wines yielded interesting and promising results which can be built upon and improved in the future studies. Further work should investigate other white hybrid wine grape varieties, and perhaps including the sampling of whole grapes to better understand the extent of extraction caused by the maceration treatments. The monitoring of GSH, total phenolic content, antioxidant capacity and redox status of the treatments throughout the duration of alcoholic fermentation may give greater insight to the changes that occur in the grape juice and must during alcoholic fermentation (i.e. depletion or increase of GSH, antioxidant capacity, etc).

The monitoring of GSH is of particular interest due to previous studies reporting that yeast may be able to alter the GSH concentration during alcoholic fermentation. Due to the complex metabolic processes of yeast and grape that may play a role in fluctuating concentrations of

GSH during fermentation, interpretation of the results may be challenging in order to fully unravel the significance of any changes that are observed during fermentation. To better understand and explain the observations obtained from the antioxidant capacity and total

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phenolic content assays, it would be revealing to perform phenolic profiling of the wines and juice of Cayuga and Traminette by HPLC.

4.2.2 Identification and quantification of volatile aroma compounds in Cayuga

and Traminette wines

Anecdotally, differences in aroma between the control, cryogenic maceration and extended skin contact treatments for both Cayuga and Traminette wines have been observed. In both

Cayuga and Traminette, the aroma of the control and cryomaceration treatment wine appeared to be fairly similar and overall pleasant. The extended skin contact treatment wine did not appear to contain detectable levels of the typical fruity/floral aromas of the C/CM wines and was overall unpleasant. Quantitative Solid Phase Extraction-Gas Chromatography-Mass

Spectrometry (SPE-GC-MS) analysis could be performed to determine the concentrations of free and bound volatile aromas, and free volatiles may be isolated using headspace solid-phase microextraction (HS-SPME) and analyzed by GC-MS, with semi-quantitative analysis of the compounds, reported as a ug/L equivalents of an internal standard.

Because the bulk of wine aroma compounds are located in grape skins, either in volatile form or bound to non-volatile precursors, it is expected that maceration would allow greater extraction of aromas prior to pressing. It is reasonable to assume that the presence of skins during maceration would add to the complexity of the processes and reactions that occur during fermentation. In general, little is known about the behavior of volatile compounds during maceration and the effect of maceration treatments on the dynamic development of aromas and phenols in white hybrids during wine production. Investigation of the evolution of free and bound volatile varietal and fermentation aroma compounds and phenols during fermentation of white hybrid grapes subjected to various maceration treatments may elucidate the evolution patterns of these compounds and allow for a better estimation of optimal skin contact time. Ultimately, it

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has the potential to result in a wide array of possibilities, with the ability to obtain wines with diverse compositions as a function of the moment of skin removal.

4.2.3 Copper Fining with Bound Cu(II) Treatments in Real Vinification Setting

The bound Cu treatments CuO-Alumina and Cu(NO3)2-Celite were evaluated in model wine systems as well as real wine systems, and results indicated differences between the resulting

Cu concentration in real wine and model wine systems. Real wine systems are a complex mixture, and in order to determine the bound Cu(II) efficacy in a setting that is applicable to winemakers, it would be of great benefit to study these treatments during an actual vinification process, in order to investigate the use of bound Cu(II) treatments in comparison to CuSO4 in the ability to remove H2S, as well as prevent increases in the final concentration of Cu in the finished wine.

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Appendix A: Supplementary Information for Chapter 2

Figure 6.1 Traminette Control Juice Full HPLC-ECD Spectrum

Figure 6.2 Traminette Control juice sample spectrum zoomed to GSH peak at rt = 6.6.

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Figure 6.3 Traminette CM juice full HPLC-ECD sample spectrum

Figure 6.4 Traminette CM juice sample spectrum zoomed to peak area, which was very small (17 nA), well beneath the calibration curve (700 nA at the lowest). In the cryogenic maceration juice samples, glutathione was detected but was below the limit of quantification.

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Figure 6.5. Traminette ESC juice full HPLC-ECD sample spectrum

Figure 6.6. Traminette ESC juice sample spectrum zoomed in to observe glutathione peak at rt = 6.6. Glutathione in the Traminette juice for the ESC samples was below the limit of detection, and possibly obscured by a peak at rt = 6.8.

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Appendix B: Supplementary Information for

Chapter 2

7.1 Reporting of One Way ANOVA Results

7.1.1 Juice and Wine pH

7.1.1.1 Cayuga

There was a statistically significant difference between groups for juice pH as determined by one-way ANOVA (F(2,8) = 4.087, p = .060). A Tukey post hoc test revealed that pH in extended skin contact juice was significantly lower than the pH in the cryogenic maceration juice (3.08 ±

.03 vs 3.14 ± .01, p = 0.05). There was no significant different between the control group and the cryogenic maceration p= 0.26, or extended skin contact p = .463. There was a statistically significant difference between groups for wine pH as determined by one-way ANOVA (F(2,7) =

47.582, p < .001). A Tukey post hoc test revealed that pH in wine was significantly different between control, cryogenic maceration and extended skin contact wines, with the pH of 3.49 ±

0.03, 3.54 ± 0.01 and 3.37 ± 0.01, respectively. There was a significant difference between the control group and the cryogenic maceration treatment p= 0.049, and the extended skin contact treatment p < .000.

There was a statistically significant difference between groups for titratable acidity in Cayuga juice as determined by one-way ANOVA (F(2,8) = 12.8, p = .003). A Tukey post hoc test revealed that titratable acidity in extended skin contact was significantly higher than the titratable acidity in cryogenic maceration (7.8 ± 0.5 g/L vs. 6.7 ± 0.001 g/L, p = 0.003) and the control (7.8 ± 0.5 g/Lvs 7.3 ± 0.06 g/L. p = 0.5). There was no significant difference between the control group and cryogenic maceration p = 0.09. There was a statistically significant difference

127

between groups for titratable acidity in Cayuga wine as determined by one-way ANOVA (F(2,7)

= 21.743, p = .001). A Tukey post hoc test revealed that TA in wine was significantly different between control, cryogenic maceration and extended skin contact wines, with the TA of 7.91 ±

0.23 g/L, 7.39 ± 0.06 g/L and 8.42 ± 0.22 g/L, respectively. There was a significant difference between the control group and the cryogenic maceration treatment p= 0.049, and the extended skin contact treatment p < .001.

There was a statistically significant difference between groups for Brix in juice as determined by one-way ANOVA (F(2,8) = 6.50, p = .021). A Tukey post hoc test revealed that Brix in extended skin contact was significantly lower than the Brix in cryogenic maceration (19.5 ± 0.38 vs. 20.2 ± 0.06, p= 0.017). There was no significant difference between the control group and cryogenic maceration p = 0.102 or extended skin contact p = .430.

There was a statistically significant difference between groups for Brix in juice as determined by one-way ANOVA (F(2,7) = 8.278, p = .014). A Tukey post hoc test revealed that free SO2 concentration in control was significantly higher than in cryogenic maceration (11.7 ± 5.3 vs.

1.83± 0.8, p= 0.021) and extended skin contact (11.7 ± 5.3 vs. 2.8 ± 1.4, p= 0.033). There was no significant difference found between the free SO2 concentration of the cryogenic maceration and extended skin contact treatment p = 0.948. There were no statistically significant differences found between treatments for volatile acidity in the Cayuga wine as determined by one-way ANOVA (F(2,7) = .569, p = .590) with a Tukey post hoc test.

7.1.1.2 Traminette

There was a statistically significant difference between groups for Traminette juice pH as determined by one-way ANOVA (F(2,9) = 1913.045, p < .001). A Tukey post hoc test revealed that pH was significantly different between control and cryogenic maceration juice (2.97 ± .01 vs

3.30 ± .01, p = 0.00). There was a significant different between the juice pH of the control group

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and the extended skin contact (2.97 ± .01 vs 3.06 ± .00, p = 0.000). The pH of the control was significantly lower than the extended skin contact, and the pH of the cryogenic maceration treatment was greater than the extended skin contact treatment. There was a statistically significant difference between groups for wine pH as determined by one-way ANOVA (F(2,7) =

216.081, p < .001). A Tukey post hoc test revealed that pH in Traminette wine was significantly different between control and cryogenic maceration wines (3.32 ± .03 vs 3.63 ± .03, p = 0.000) as well as between control and extended skin contact (3.32 ± .03vs 3.67 ± .01, p = 0.000).

There was no significant difference between the wine pH of the cryogenic maceration and the extended skin contact treatments p= 0.330.

The maceration treatments affected the juice pH by increasing it in both the CM and ESC treatments compared to the control. This pH change can be attributed to a release of buffering ions resulting from the extended skin contact and cryogenic maceration (Olejar 2015). The pH change observed in the CM and ESC wines, coupled with the decreased TA was reported in previous studies of Chardonnay (Olejar 2016) and Sauvignon blanc (Olejar 2015), which suggests that a release of basic materials or potassium due to potassium bitartrate precipitation occurs and may be responsible for these changes compared to control.

There was a statistically significant difference between groups for titratable acidity in

Traminette juice as determined by one-way ANOVA (F(2,9) = 55.758, p < .001). A Tukey post hoc test revealed that titratable acidity in cryogenic maceration juice was significantly lower than the titratable acidity in extended skin contact (6.89 ± 0.10 g/L vs. 7.83 ± 0.34 g/L, p = 0.000) and the control (6.89 ± 0.10 g/L vs 8.50 ± 0.09 g/L. p = 0.000). There was a significant difference between the control group and extended skin contact treatment p = 0.004. There was a statistically significant difference between groups for titratable acidity in Traminette wine as determined by one-way ANOVA (F(2,7) = 153.346, p < .001). A Tukey post hoc test revealed

129

that TA in wine was significantly different between control and cryogenic maceration (8.92 ±

0.15 g/L vs. 7.47 ± 0.11 g/L, p = 0.000) and extended skin contact wines (8.92 ± 0.15 g/L vs

7.51± 0.05 g/L. p = 0.000). There was no significant difference between the TA of the cryogenic maceration and the extended skin contact treatment p = .943.

There was a statistically significant difference between groups for Brix in juice as determined by one-way ANOVA (F(2,9) = 25.019, p < .001). A Tukey post hoc test revealed that Brix in control was significantly higher than the Brix in cryogenic maceration (21.05 ± 0.19 vs. 20.01 ±

0.10, p= 0.000). Tukey post hoc test also revealed that Brix in cryogenic maceration was significantly lower than the Brix in extended skin contact (20.01 ± 0.10vs. 20.93 ± 0.30, p=

0.001). There was no significant difference between the Brix in the juice of the control group and extended skin contact p = 0.693. An increase in Brix may be due to more exhaustive extraction from the grapes.

There was a statistically significant difference between groups for free SO2 concentration in wine as determined by one-way ANOVA (F(2,7) = 105.000, p < .001). A Tukey post hoc test revealed that free SO2 concentration in control was significantly higher than in cryogenic maceration (8.26 ± 1.12 vs. 1.38 ± 0.00, p= 0.000) and extended skin contact (8.26 ± 1.12 vs.

1.38 ± 0.00, p= 0.000). There was no significant difference found between the free SO2 concentration of the cryogenic maceration and extended skin contact treatment p = 1.000.

There were no statistically significant differences found between treatments for volatile acidity in the Traminette wine as determined by one-way ANOVA (F(2,7) = 1.282, p = .335) with a Tukey post hoc test.

7.1.2 Antioxidant capacity

7.1.2.1 Cayuga

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There was a statistically significant difference between groups for antioxidant capacity in

Cayuga juice as determined by one-way ANOVA (F(2,24) = 4.617, p = .020). A Tukey post hoc test revealed that DPPH scavenging activity in the control was significantly higher than in the extended skin contact (1066 ± 21 mg/L Trolox equivalents vs 838 ± 286 mg/L Trolox equivalents, p = 0.022). There was no significant difference in the antioxidant capacity between the control and the cryogenic maceration treatment p = .178. Additionally, there was no significant difference between the antioxidant capacity of the cryogenic maceration treatment and the extended skin contact p = 1.000.

There was a statistically significant difference between groups for antioxidant capacity in

Cayuga wine as determined by one-way ANOVA (F(2,27) = 267.593, p < .001). A Tukey post hoc test revealed that DPPH scavenging activity in the control was significantly lower than in the extended skin contact (287 ± 46 mg/L Trolox equivalents vs 665 ± 49 mg/L Trolox equivalents, p

= 0.000). There was no significant difference in the antioxidant capacity between the control and the cryogenic maceration treatment p = .264. There was a significant difference between the antioxidant capacity of the cryogenic maceration treatment and the extended skin contact (257 ±

25 mg/L Trolox equivalents vs 665 ± 49 mg/L Trolox equivalents, p = 0.000).

7.1.2.2 Traminette

There was a statistically significant difference between groups for antioxidant capacity in

Traminette juice as determined by one-way ANOVA (F(2,24) = 290.525, p < .001). A Tukey post hoc test revealed that DPPH scavenging activity in the control was significantly higher than in the extended skin contact (583 ± 56 mg/L Trolox equivalents vs 184 ± 19 mg/L Trolox equivalents, p = 0.000). There was a significant difference in the antioxidant capacity between the control and the cryogenic maceration treatment (583 ± 56 mg/L Trolox equivalents vs 256 ±

17 mg/L Trolox equivalents, p = 0.000). Additionally, there was a significant difference between

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the antioxidant capacity of the cryogenic maceration treatment and the extended skin contact p

= .007.

There was a statistically significant difference between groups for antioxidant capacity in

Traminette wine as determined by one-way ANOVA (F(2,27) = 851.587, p < .001). A Tukey post hoc test revealed that DPPH scavenging activity in the control was significantly lower than in the extended skin contact (541 ± 22 mg/L Trolox equivalents vs 965 ± 15 mg/L Trolox equivalents, p

= 0.000). There was a significant difference in the antioxidant capacity between the control and the cryogenic maceration treatment (541 ± 22 mg/L Trolox equivalents vs 416 ± 35 mg/L Trolox equivalents, p = 0.000), with the cryogenic maceration treatment containing significantly lower antioxidant capacity than the control. There was a significant difference between the antioxidant capacity of the cryogenic maceration treatment and the extended skin contact, with the cryogenic maceration treatment containing significantly less antioxidant capacity than the extended skin contact treatment (416 ± 35 mg/L Trolox equivalents vs 965 ± 15 mg/L Trolox equivalents, p = 0.000).

7.1.3 Total Phenolic Content

7.1.3.1 Cayuga

There was a statistically significant difference between groups for total phenolic content in Cayuga juice as determined by one-way ANOVA (F(2,24) = 7.225, p = .003). A Tukey post hoc test revealed that total phenolic content in Cayuga control juice was significantly higher than in the cryogenic maceration juice (498 ± 50 mg/L gallic acid equivalents vs 351 ± 103 mg/L gallic acid equivalents, p = 0.037) and the extended skin contact juice (498 ± 50 mg/L gallic acid equivalents vs 376 ± 109 mg/L gallic acid equivalents, p = 0.006). There was no significant difference in the total phenolic content between the cryogenic maceration and the extended skin contact p = 0.890.

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There was a statistically significant difference between groups for total phenolic content in

Cayuga wine as determined by one-way ANOVA (F(2,27) = 1234.395, p < .001). A Tukey post hoc test revealed that total phenolic content in control was significantly lower than in the cryogenic maceration (317 ± 12 mg/L gallic acid equivalents vs 350 ± 11 mg/L gallic acid equivalents, p = 0.000) and the extended skin contact (317 ± 12 mg/L gallic acid equivalents vs

672 ± 26 mg/L gallic acid equivalents, p = 0.000). There was a significant difference in the total phenolic content between the cryogenic maceration and the extended skin contact, with the extended skin contact phenolic content being significantly greater than the cryogenic treatment

(350 ± 11 mg/L gallic acid equivalents vs 672 ± 26 mg/L gallic acid equivalents, p = 0.000).

7.1.3.2 Traminette

There was no statistically significant difference between groups for total phenolic content in

Traminette juice as determined by one-way ANOVA (F(2,24) = 0.068, p = .934). A Tukey post hoc test revealed that total phenolic content was not significantly different among control and cryogenic maceration (235 ± 33 mg/L gallic acid equivalents vs 237 ± 20 mg/L gallic acid equivalents, p = 0.995). The total phenolic content (175 ± 24 mg/L gallic acid equivalents) in the

ESC treatment was found to be significantly lower than both the control (p < .001) and cryogenic maceration treatments (p = .001).

There was a statistically significant difference between groups for total phenolic content in

Traminette wine as determined by one-way ANOVA (F(2,27) = 27.508, p < .001). A Tukey post hoc test revealed that total phenolic content in control was significantly lower than in the cryogenic maceration (236 ± 10 mg/L gallic acid equivalents vs 264 ± 13 mg/L gallic acid equivalents, p = 0.000) and was significantly greater than the phenolic content in the extended skin contact (236 ± 10 mg/L gallic acid equivalents vs 207 ± 27 mg/L gallic acid equivalents, p =

0.004). There was a significant difference in the total phenolic content between the cryogenic

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maceration and the extended skin contact, with the extended skin contact phenolic content being significantly greater than the cryogenic treatment (264 ± 13 mg/L gallic acid equivalents vs 207 ± 27 mg/L gallic acid equivalents, p = 0.000).

7.1.4 Glutathione

7.1.4.1 Cayuga

There was a statistically significant difference between groups for glutathione concentration in Cayuga wine as determined by one-way ANOVA (F(2,7) = 152.823, p < .001). A Tukey post hoc test revealed that glutathione concentration in the control was significantly higher than in the extended skin contact (35 ± 3 mg/L vs 12 ± 2 mg/L, p = 0.000). It was also reveal that the glutathione concentration in the cryogenic maceration wine was significantly greater than in the extended skin contact (37 ± 1 mg/L vs 12 ± 2 mg/L, p = 0.000). There was no significant difference between the glutathione concentration of the control and the cryogenic maceration p

= 0.358. There was a statistically significant difference between groups for glutathione concentration in Cayuga juice as determined by one-way ANOVA (F(2,7) = 64.865, p < .001). A

Tukey post hoc test revealed that glutathione concentration in the control juice was significantly higher than in the cryogenic maceration (49 ± 3 mg/L vs 1 ± 0.1 mg/L, p = 0.000). It was also revealed that the glutathione concentration in the extended skin contact juice was significantly greater than in the cryogenic maceration (41 ± 11 mg/L vs 1 ± 0.1 mg/L, p = 0.000). There was no significant difference between the glutathione concentration of the control and the extended skin contact p = 0.216.

7.1.4.2 Traminette

There was a statistically significant difference between groups for glutathione concentration in Traminette wine as determined by one-way ANOVA (F(2,7) = 1328.336, p < .001). A Tukey post hoc test revealed that glutathione concentration in the control was significantly higher than

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in the extended skin contact (12.4 ± 0.4 mg/L vs 2.8 ± 0.1 mg/L, p = 0.000) as well as the cryogenic maceration (12.4 ± 0.4 mg/L vs 1.0 ± 0.4 mg/L, p = 0.000). The glutathione concentration of the extended skin contact wine was significantly higher than in the cryogenic maceration wine (2.8 ± 0.1 mg/L vs 1.0 ± 0.4 mg/L, p = 0.001). There was a statistically significant difference between groups for glutathione concentration in Traminette juice as determined by one-way ANOVA (F(2,8) = 753.035, p < .001). A Tukey post hoc test revealed that glutathione concentration in the control was significantly higher than in the extended skin contact (20.1 ± 1.3 mg/L vs 0.5 ± 0.0 mg/L, p = 0.000) as well as the cryogenic maceration (20.1

± 1.3 mg/L vs 0.5 ± 0.0 mg/L, p = 0.000). There was no significant difference between the cryogenic maceration and the extended skin contact, p=1.000.

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Appendix C: Supplementary Information for

Chapter 3

8.1 Reporting of Assumption Tests from Two-Way ANOVA

In addition to the reported main findings of two-way ANOVA statistical analysis found in section 3.4, detailed results from the assumption tests that were performed are reported in this section. When statistically significant interactions between treatment and time were found, an analysis of simple main effects for treatment at each level of time as well as time at each treatment, with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported with 95% confidence and p-values Bonferroni-adjusted within each simple main effect. Data are mean ± standard deviation, unless otherwise stated.

8.1.1 Bound Cu(II) in Riesling over 24h

A two-way ANOVA was conducted to examine the effects of treatment and time on Cu concentration. There was a statistically significant difference between treatment and time for Cu concentration, F(18, 140) = 13.337, p < .001, partial η2 = .632. Therefore, an analysis of simple main effects for treatment and time on mean Cu concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

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There was a statistically significant difference in Cu concentration between treatments at all time points. There was a statistically significant difference in Cu concentrations between treatments at 1 minute, F(3,140) = 199.031, p < .001, partial η2 = .810. There was a statistically significant difference in Cu concentrations between treatments at 30 minutes, F(3,140) =

138.838, p < .001, partial η2 = .748. There was a statistically significant difference in Cu concentrations between treatments at 1 hour, F(3,140) = 115.403, p < .001, partial η2 = .712.

There was a statistically significant difference in Cu concentrations between treatments at 3 hours, F(3,140) = 189.821, p < .001, partial η2 = .803. There was a statistically significant difference in Cu concentrations between treatments at 6 hours, F(3,140) = 167.505, p < .001, partial η2 = .782. There was a statistically significant difference in Cu concentrations between treatments at 12 hours, F(3,140) = 162.788, p < .001, partial η2 = .777. There was a statistically significant difference in Cu concentrations between treatments at 24 hours, F(3,140) = 153.373, p < .001, partial η2 = .767.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was not a statistically significant difference in mean Cu concentration between time points for control F(6,140) =.075, p = .998, partial η2 = .003. There was a statistically significant difference in mean Cu concentration between time points for CuSO4 F(6,140) =

3.967, p = .001, partial η2 = .145. There was not a statistically significant difference in mean Cu concentration between time points for CuCelite F(6,140) = .081, p = .998, partial η2 = .003.

There was a statistically significant difference in mean Cu concentration between time points for

CuOAl, F(6,140) = 45.411, p < .001, partial η2 = .661.

Main effect of treatment

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There was a statistically significant main effect of treatment F(3,140) = 1046.737, p < .001, partial η2 = .957. The control was associated with a mean Cu concentration .570 mg/L lower than the CuSO4 treatment, which was a statistically significant difference, p < .001. The control was associated a mean Cu concentration .063 mg/L lower than the CuCelite treatment, which was a statistically significant difference p < .001. The control treatment was associated with a mean Cu concentration .301 mg/L lower than the CuOAl treatment, which was a statistically significant difference, p =.000.

The CuCelite treatment was associated with a mean Cu concentration .507 mg/L lower than the CuSO4 treatment, which was statistically significant p < .001. The CuCelite treatment was associated with a mean Cu concentration that was .238 mg/L lower than CuOAl, which was statistically significant, p < .001. The CuOAl treatment was associated with a mean Cu concentration that was .269 mg/L lower than that of the CuSO4 treatment, which was found to be statistically significant p < .001.

Main effect of time

There was a statistically significant main effect of time F(6, 140) = 9.523, p < .001, partial

η2 = .290. The concentration of Cu at 1 minute was statistically significantly lower than 3, 6, 12 and 24 hours, p <.012. The mean difference between the concentration of Cu at 1 minute and

30 minutes, as well as and 1 minute and 1 hour was not statistically significant, p = 1.000. The mean difference between the concentration of Cu at 30 minutes and 3 hours was statistically significantly lower, p < .001. However, no other statistically significant differences were found between 30 minutes and any of the other time points. The mean difference between the concentration of Cu at 1 hour and 3 hours, as well as 1 hour and 6 hours was statistically significantly lower, p <.007. The mean difference between the concentration of Cu at 1 hour was not found to be statistically significant from than the concentration of Cu at any other time

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points, p > .034. The mean difference between the concentration of Cu at 3 hours when compared to 1 minute, 30 minutes and 1 hour was statistically significantly higher, p <.000. At 6 hours, the mean difference between the concentration of Cu at 1 minute and 1 hour was statistically significantly higher, p < .007. At 12 hours, the mean difference between the concentration of Cu at 1 minute was significantly lower, p <.012. However, no other statistically significant differences were found between any of the other time points when compared to the

Cu concentration at 12 hours. At 24 hours, the mean difference between the concentration of

Cu was statistically significantly higher at 1 minute, p =.002. No other significant difference were found between 24 hours and any of the other time points.

Pairwise comparisons

The CuSO4 treatment was observed to have a statistically significantly greater mean Cu concentration than the control at all of the time points, p < .001. The greatest mean difference was observed at 1 minute, with a mean difference of .627 mg/L. The smallest mean difference between the Cu concentration of the CuSO4 and the control was observed at 1 hour, with a mean difference of .504 mg/L. At 1 minute, the Cu concentration of CuSO4 was .72 ± 05 mg/L and control was 0.10 ± .01 mg/L, a mean difference of .627 mg/L, p < .001. At 24 hours, the, the

Cu concentration of CuSO4 was .62 ± .03 mg/L and control was .08 ± .01 mg/L, a mean difference of .504 mg/L, p < .001.

The CuSO4 treatment also resulted in a much higher mean Cu concentration than the

CuCelite and CuOAl treatments at all time points. The lowest mean difference between the Cu concentration of the CuSO4 and the CuCelite was observed at 1 hour, with a mean difference of

.452 mg/L, p < .001. The greatest mean difference between CuSO4 and CuCelite was observed at 1 minute. At 1 minute, the Cu concentration of CuCelite was .16 ± .00 mg/L and CuSO4 was

0.72 ± .05 mg/L, a mean difference of .569 mg/L greater, p < .001. At 24 hours, the, the Cu

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concentration of CuCelite was .15 ± .01 mg/L and CuSO4 was .62 ± .03 mg/L, a mean difference of .47 mg/L, p < .001. The lowest mean difference between the Cu concentration of the CuSO4 and the CuOAl was observed at 24 hours, with a mean difference of .131 mg/L, p < .001. The greatest mean difference between CuSO4 and CuOAl was observed at 1 minute. At 1 minute, the Cu concentration of CuOAl was .13 ± .02 mg/L and CuSO4 was 0.72 ± .05 mg/L, a mean difference of .596 mg/L greater, p < .001. At 24 hours, the, the Cu concentration of CuOAl was

.49 ± .02 mg/L and CuSO4 was .62 ± .03 mg/L, a mean difference of .131 mg/L, p < .001.

Additionally, it was observed that the mean difference between the CuCelite and CuOAl treatments was statistically significant at all time points, with the exception of 1 minute. The

CuOAl resulted in a mean difference in Cu concentration that was statistically significantly greater than the CuCelite. The lowest mean difference between the Cu concentration of the

CuCelite and the CuOAl was observed at 30 minutes. At 30 minutes, the Cu concentration of

CuOAl was .31 ± .01 mg/L and CuCelite was .15 ± .01 mg/L, a mean difference of .166 mg/L, p

< .001. The greatest mean difference between CuCelite and CuOAl was observed at 6 hours. At

6 hours, the Cu concentration of CuOAl was .49 ± .04 mg/L and CuCelite was .14 ± .01 mg/L, a mean difference of .350 mg/L, p < .001.

8.1.2 Bound Cu(II) in Lemberger over 24h

A two-way ANOVA was conducted to examine the effects of treatment and time on Cu concentration. There was a statistically significant difference between treatment and time for Cu concentration, F(18, 140) = 44.121, p < .001, partial η2 = .850. Therefore, an analysis of simple main effects for treatment and time on mean Cu concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

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Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in Cu concentration between treatments at all time points. There was a statistically significant difference in Cu concentrations between treatments at 1 minute, F(3,140) = 636.150, p < .001, partial η2 = .932. There was a statistically significant difference in Cu concentrations between treatments at 30 minutes, F(3,140) =

728.891, p < .001, partial η2 = .940. There was a statistically significant difference in Cu concentrations between treatments at 1 hour, F(3,140) = 554.586, p < .001, partial η2 = .922.

There was a statistically significant difference in Cu concentrations between treatments at 3 hours, F(3,140) = 509.786, p < .001, partial η2 = .916. There was a statistically significant difference in Cu concentrations between treatments at 6 hours, F(3,140) = 333.203, p < .001, partial η2 = .877. There was a statistically significant difference in Cu concentrations between treatments at 12 hours, F(3,140) = 932.334, p < .001, partial η2 = .952. There was a statistically significant difference in Cu concentrations between treatments at 24 hours, F(3,140) = 790.444, p < .001, partial η2 = .944.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was not a statistically significant difference in mean Cu concentration between time points for control F(6,140) =.198, p = .977, partial η2 = .008. There was a statistically significant difference in mean Cu concentration between time points for CuSO4 F(6,140) =

88.370, p < .001, partial η2 = .791. There was not a statistically significant difference in mean Cu concentration between time points for CuCelite F(6,140) = .247, p = .960, partial η2 = .010.

There was a statistically significant difference in mean Cu concentration between time points for

CuOAl, F(6,140) = 107.657, p < .001, partial η2 = .822.

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Main effect of treatment

There was a statistically significant main effect of treatment F(3,140) = 4220.670, p < .001, partial η2 = .989. The control was associated with a mean Cu concentration .693 mg/L lower than the CuSO4 treatment, which was a statistically significant difference, p < .001. The control was associated a mean Cu concentration .032 mg/L lower than the CuCelite treatment, which was a statistically significant difference p < .001. The control treatment was associated with a mean Cu concentration .250 mg/L lower than the CuOAl treatment, which was a statistically significant difference, p =.000.

The CuCelite treatment was associated with a mean Cu concentration .662 mg/L lower than the CuSO4 treatment, which was statistically significant, p < .001. The CuCelite treatment was associated with a mean Cu concentration that was .218 mg/L lower than CuOAl, which was statistically significant, p < .001. The CuOAl treatment was associated with a mean Cu concentration that was .443 mg/L lower than that of the CuSO4 treatment, which was found to be statistically significant p < .001.

Main effect of time

There was a statistically significant main effect of time F(6, 140) = 64.110, p < .001, partial η2 = .733. The concentration of Cu at 1 minute was statistically significantly lower than all other time points: 30 minutes, 3, 6, 12 and 24 hours, p <.017. The mean difference between the concentration of Cu at 30 minutes compared to 12 and 24 hours was statistically significantly lower, p < .001. However, no other statistically significant differences were found between 30 minutes and any of the other time points. The mean difference between the concentration of Cu at 1 hour compared to 12 hours and 24 hours was statistically significantly lower, p <.000. The mean difference between the concentration of Cu at 1 hour was not found to be statistically significant from than the concentration of Cu at any other time points, p > .051. The mean

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difference between the concentration of Cu at 3 hours compared to 12 hours and 24 hours was statistically significantly higher, p <.000. No other statistically significant differences were found between 3 hours and the other time points (i.e. 30 minutes, 1 hour, 6 hours), p > .188 The mean difference between the Cu concentration at 6 hours compared to 12 hours and 24 hours was statistically significantly lower, p < .001. The mean difference between the concentration of Cu at 12 hours compared to 1 minute, 30 minutes, 1 hour, 3 hours and 6 hours were significantly greater, p < .001. At 24 hours, the mean difference between the concentration of Cu was statistically significantly higher at 1 minute, 30 minutes, 1 hour, 3 hours, and 6 hours, p =.000.

No statistically significant differences were found between the mean difference in Cu concentration at 12 hours and 24, p = .892.

Pairwise comparisons

The CuSO4 treatment was observed to have a statistically significantly greater mean Cu concentration than the control at all of the time points, p < .001. The greatest mean difference was observed at 12 hours, with a mean difference of .855 mg/L. The smallest mean difference between the Cu concentration of the CuSO4 and the control was observed at 6 hours, with a mean difference of .490 mg/L. At 6 hours, the Cu concentration of CuSO4 was .55 ± 06 mg/L and control was 0.07 ± .01 mg/L, a mean difference of .490 mg/L, p < .001. At 12 hours, the, the

Cu concentration of CuSO4 was .93 ± .03 mg/L and control was .08 ± .01 mg/L, a mean difference of .855 mg/L, p < .001.

The CuSO4 treatment also resulted in a much higher mean Cu concentration than the

CuCelite and CuOAl treatments at all time points. The lowest mean difference between the Cu concentration of the CuSO4 and the CuCelite was observed at 6 hours, with a mean difference of .447 mg/L, p < .001. The greatest mean difference between CuSO4 and CuCelite was observed at 12 hours. At 6 hours, the Cu concentration of CuCelite was .11 ± .02 mg/L and

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CuSO4 was 0.56 ± .06 mg/L, a mean difference of .447 mg/L greater, p < .001. At 12 hours, the, the Cu concentration of CuCelite was .11 ± .01 mg/L and CuSO4 was .93 ± .03 mg/L, a mean difference of .447 mg/L, p < .001. The lowest mean difference between the Cu concentration of the CuSO4 and the CuOAl was observed at 6 hours, with a mean difference of .141 mg/L, p <

.001. The greatest mean difference between CuSO4 and CuOAl was observed at 1 minute. At 1 minute, the Cu concentration of CuOAl was .10 ± .01 mg/L and CuSO4 was 0.75 ± .07 mg/L, a mean difference of .646 mg/L greater, p < .001. At 6 hours, the, the Cu concentration of CuOAl was .42 ± .09 mg/L and CuSO4 was .56 ± .06 mg/L, a mean difference of .141 mg/L, p < .001.

Additionally, it was observed that the mean difference between the CuCelite and CuOAl treatments was statistically significant at all time points, with the exception of 1 minute. The

CuOAl resulted in a mean difference in Cu concentration that was statistically significantly higher than the CuCelite. The lowest mean difference between the Cu concentration of the

CuCelite and the CuOAl was observed at 30 minutes. At 30 minutes, the Cu concentration of

CuOAl was .26 ± .04 mg/L and CuCelite was .11 ± .00 mg/L, a mean difference of .151 mg/L, p

< .001. The greatest mean difference between CuCelite and CuOAl was observed at 24 hours.

At 24 hours, the Cu concentration of CuOAl was .48 ± .01 mg/L and CuCelite was .10 ± .02 mg/L, a mean difference of .372 mg/L, p < .001.

8.2 Reduction of thiols and H2S by bound Cu(II)

8.2.1 H2S Reduction by Bound Cu(II) over 4h

A two-way ANOVA was conducted to examine the effects of treatment and time on H2S concentration. There was a statistically significant difference between treatment and time for

2 H2S concentration, F(15, 48) = 4.317, p < .001, partial η = .574. Therefore, an analysis of simple main effects for treatment and time on mean H2S concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025

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level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in H2S concentration between treatments for all time points, except for 30 minutes. There was a statistically significant difference in H2S concentrations between treatments at 10 minutes, F(3,48) = 9.004, p < .001, partial η2 = .360.

There was not a statistically significant difference in H2S concentrations between treatments at

30 minutes, F(3,48) =2.637, p = .060, partial η2 = .142. There was a statistically significant difference in H2S concentrations between treatments at 60 minutes, F(3,48) = 3.857, p = .015,

2 partial η = .194. There was a statistically significant difference in H2S concentrations between treatments at 90 minutes, F(3,48) = 6.903, p = .001, partial η2 = .301. There was a statistically significant difference in H2S concentrations between treatments at 120 minutes, F(3,48) =

2 8.122, p < .001, partial η = .337. There was a statistically significant difference in H2S concentrations between treatments at 240 minutes, F(3,48) = 23.360, p < .001, partial η2 = .639.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was a statistically significant difference in mean H2S concentration between time points for control F(5,48) = 9.974, p < .001, partial η2 = .510. There was a statistically significant difference in mean H2S concentration between time points for CuSO4 F(5,48) = 22.140, p <

2 .001, partial η = .698.There was a statistically significant difference in mean H2S concentration between time points for CuOAl F(5,48) = 32.033, p < .001, partial η2 = .769. There was a statistically significant difference in mean H2S concentration between time points for CuCelite

F(5,48) = 13.479, p < .001, partial η2 = .584.

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Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 37.300, p < .001,

2 partial η = .700. The control treatment was associated with a mean H2S concentration 98.110 uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean H2S concentration 57.721 uM higher than the

CuOAl treatment, which was a statistically significant difference p < .001. The control treatment was associated with a mean H2S concentration 64.610 uM greater than the CuCelite treatment, which was a statistically significant difference, p =.000.

The CuSO4 treatment was associated with a mean H2S concentration 40.389 uM lower than the CuOAl treatment, which was statistically significant p = .001. The CuSO4 treatment was associated with a mean H2S concentration that was 33.500 uM lower than CuCelite, which was statistically significant, p = .005. The CuOAl treatment was associated with a mean H2S concentration that was 6.889 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = 1.000.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 64.675, p < .001, partial

2 η = .871. The concentration of H2S at 10 minutes was statistically significantly higher than 30,

60, 90, 120 and 240 minutes, p < .001. The mean difference between the concentration of H2S at 30 minutes and 60 minutes was not statistically significant, p = .344. The mean difference between the concentration of H2S at 60 and 90 minutes (p = .691), as well as 60 and 120 minutes (p =.071), was not statistically significant. However, the mean difference between the concentration of H2S at 60 minutes and 240 minutes was statistically significant, p < .001. This significant difference observed between the concentrations of H2S over time indicates that the effect of the treatment on the removal of H2S can be observed in a four-hour time window.

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Pairwise comparisons

The mean H2S concentration was observed to not deviate significantly among the CuCelite treatment and control until the 60-minute time point. Statistically significant mean differences between the CuCelite and the control were observed at 60 and 240 minutes. At 60 minutes, the mean H2S concentration of the CuCelite was 188 ± 20 uM and the control was 260 ± 15 uM, a statistically significant mean difference of 72 uM less, p = .019. At 240 minutes, the mean H2S concentration of the CuCelite was 140 ± 20 uM and the control was 230 ± 6 uM, a statistically significant mean difference of 90 uM less, p = .002. The mean difference in H2S concentration of the CuOAl and control was statistically significant only at 240 minutes, where the concentration of CuOAl was 46 ± 25 uM and the control was 230 ± 6 uM, with a mean difference of 183 uM, p

< .001. A statistically significant mean difference between CuCelite and CuOAl was found at

240 minutes, with a mean difference in H2S concentration 93 uM lower in the CuOAl treatment compared to the CuCelite treatment, p = .001.

The CuSO4 treatment was observed to have statistically significantly less mean H2S concentration than the control at 10, 90, 120 and 240 minutes. At 10 minutes, the H2S concentration of CuSO4 was 251 ± 6 uM and control was 371 ± 77 uM, a mean difference of 120 uM, p < .001. At 90 minutes, the, the H2S concentration of CuSO4 was 145 ± 27 uM and control was 249 ± 6 uM, a mean difference of 105 uM, p < .001. At 240 minutes, the concentration of the CuSO4 was 50 ± 19 uM and the control was 230 ± 6 uM, a mean difference of 180 uM, p <

.001. Although the CuSO4 treatment resulted in much lower mean H2S concentrations than in the CuOAl and CuCelite at all time points, no statistically significant mean differences were observed.

8.2.2 Cys Reduction by Bound Cu(II) over 4h

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A two-way ANOVA was conducted to examine the effects of treatment and time on Cys concentration. There was a statistically significant difference between treatment and time for

Cys concentration, F(15, 48) = 2.278, p = .016, partial η2 = .416. Therefore, an analysis of simple main effects for treatment and time on mean Cys concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in Cys concentration between treatments at

60, 90 and 120 minutes. There was not a statistically significant difference in Cys concentrations between treatments at 10 minutes, F(3,48) = 2.788, p = .051, partial η2 = .148, or at 30 minutes,

F(3,48) =1.855, p = .150, partial η2 = .104. There was a statistically significant difference in Cys concentrations between treatments at 60 minutes, F(3,48) = 7.340, p < .001, partial η2 = .314.

There was a statistically significant difference in Cys concentrations between treatments at 90 minutes, F(3,48) = 12.205, p < .001, partial η2 = .433. There was a statistically significant difference in Cys concentrations between treatments at 120 minutes, F(3,48) = 8.122, p < .001, partial η2 = .337. There was not a statistically significant difference in Cys concentrations between treatments at 240 minutes, F(3,48) = .701, p = .556, partial η2 = .042.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was a statistically significant difference in mean Cys concentration between time points for control F(5,48) = 17.176, p < .001, partial η2 = .641. There was a statistically significant difference in mean Cys concentration between time points for CuSO4 F(5,48) =

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24.005, p < .001, partial η2 = .714.There was a statistically significant difference in mean Cys concentration between time points for CuOAl F(5,48) = 23.419, p < .001, partial η2 = .709. There was a statistically significant difference in mean Cys concentration between time points for

CuCelite F(5,48) = 22.112, p < .001, partial η2 = .697.

Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 24.387, p < .001, partial η2 = .604. The control treatment was associated with a mean Cys concentration 90.167 uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean Cys concentration 22.944 uM higher than the

CuOAl treatment, which was not found to be a statistically significant difference p = .274. The control treatment was associated with a mean Cys concentration 53.278 uM greater than the

CuCelite treatment, which was a statistically significant difference, p =.000.

The CuSO4 treatment was associated with a mean Cys concentration 67.222 uM lower than the CuOAl treatment, which was statistically significant p < .001. The CuSO4 treatment was associated with a mean Cys concentration that was 36.889 uM lower than CuCelite, which was statistically significant, p = .011. The CuOAl treatment was associated with a mean Cys concentration that was 30.333 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = .055.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 79.878, p < .001, partial

η2 = .893. The concentration of Cys at 10 minutes was statistically significantly higher than 30,

60, 90, 120 and 240 minutes, p = <.006. The mean difference between the concentration of Cys at 30 minutes and 60 minutes was not statistically significant, p = .067. The mean difference between the concentration of Cys at 90 and 120 minutes was not statistically significant, p=.092.

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The mean difference between the concentration of Cys at 10, 30 60, 90 and 120 minutes versu

240 minutes was statistically significant, p < .001. This significant difference observed between the concentrations of Cys over time indicates that the effect of the treatment on the removal of

Cys can be observed in a four-hour time window.

Pairwise comparisons

The mean Cys concentration was observed to not decrease significantly among the treatments and control until the 60-minute time point. Statistically significant mean differences between the CuSO4 and the control were observed at 60, 90 and 120 minutes. At 60 minutes, the mean Cys concentration of the CuSO4 was 130 ± 34 uM and the control was 250 ± 25 uM, a statistically significant mean difference of 119 uM less, p < .001. At 90 minutes, the mean difference was 158 uM, p < .001. At 120 minutes, the mean Cys concentration of the CuSO4 was 54 ± 12 uM and the control was 206 ± 28 uM, a statistically significant mean difference of

152 uM less, p < .001. No statistically significant differences were observed in mean difference of Cys concentration between control, CuSO4, CuOAl or CuCelite treatments. Similar results were observed between the CuSO4 and CuOAl. Statistically significant mean differences between the CuSO4 and the CuOAl were observed at 60 and 90 minutes. At 60 minutes, the mean difference in Cys concentration between CuSO4 and CuOAl was 99 uM, p = .004. At 90 minutes, the mean difference in Cys concentration between CuSO4 and CuOAl was 113 uM, p =

.001. There were no statistically significant mean differences between the Cys concentration of

CuSO4 and CuOAl at 240 minutes. Additionally, no statistically significant mean differences were observed between the CuSO4 and the CuCelite for any of the time points.

The mean Cys concentration in the CuOAl did not significantly deviate from that of the control until the 120-minute time point. At 120 minutes, the mean Cys concentration of the

CuOAl was 122 ± 13 uM and the control was 206 ± 28 uM, a statistically significant mean

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difference of 85 uM less, p = .020. No statistically significant mean differences were observed between the CuOAl and the CuCelite for any of the time points.

Statistically significant mean differences between the CuCelite and the control were observed at 90 and 120 minutes. At 90 minutes, the mean Cys concentration of the CuCelite was 140 ± 20 uM and the control was 232 ± 35uM, a statistically significant mean difference of

93 uM less, p = .008. At 120 minutes, the Cys concentration of the CuCelite was 108 uM less than the control, p = .002. While the Cys concentration of the CuCelite was less than that of the

CuOAl for all time points after 10 minutes, no statistically significant mean differences in Cys concentration were observed.

8.2.3 3SH Reduction by Bound Cu(II) over 4h

A two-way ANOVA was conducted to examine the effects of treatment and time on 3SH concentration. There was a statistically significant difference between treatment and time for

3SH concentration, F(15, 48) = 4.954, p < .001, partial η2 = .608. Therefore, an analysis of simple main effects for treatment and time on mean 3SH concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Bonferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in 3SH concentration between treatments for all time points. There was a statistically significant difference in 3SH concentrations between treatments at 10 minutes, F(3,48) = 3.039, p = .038, partial η2 = .160. There was a statistically significant difference in 3SH concentrations between treatments at 30 minutes, F(3,48) = 4.673, p = .006, partial η2 = .226. There was a statistically significant difference in 3SH concentrations

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between treatments at 60 minutes, F(3,48) = 12.352, p < .001, partial η2 = .436. There was a statistically significant difference in 3SH concentrations between treatments at 90 minutes,

F(3,48) = 16.899, p < .001, partial η2 = .514. There was a statistically significant difference in

3SH concentrations between treatments at 120 minutes, F(3,48) = 19.392, p < .001, partial η2 =

.548. There was a statistically significant difference in 3SH concentrations between treatments at 240 minutes, F(3,48) = 41.727, p < .001, partial η2 = .723.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was a statistically significant difference in mean 3SH concentration between time

2 points for CuSO4 F(5,48) = 29.501, p < .001, partial η = .754. There was a statistically significant difference in mean 3SH concentration between time points for CuOAl F(5,48) =

16.067, p < .001, partial η2 = .626. There was a statistically significant difference in mean 3SH concentration between time points for CuCelite F(5,48) = 22.983, p < .001, partial η2 = .705. The simple main effect of time on 3SH concentration for the control was not statistically significant

F(5,48) = 1.249, p = .302, partial η2 = .115.

Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 73.312, p < .001, partial η2 = .821. The control treatment was associated with a mean 3SH concentration 92.611 uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean 3SH concentration 58.389 uM higher than the

CuOAl treatment, which was a statistically significant difference p < .001. The control treatment was associated with a mean 3SH concentration 76.722 uM greater than the CuCelite treatment, which was a statistically significant difference, p =.000.

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The CuSO4 treatment was associated with a mean 3SH concentration 34.222 uM lower than the CuOAl treatment, which was statistically significant p < .001. The CuSO4 treatment was associated with a mean 3SH concentration that was 15.889 uM lower than CuCelite, which was not found to be statistically significant, p = .129. The CuOAl treatment was associated with a mean 3SH concentration that was 18.333 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = .051.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 54.938, p < .001, partial η2

= .851. The concentration of 3SH at 10 minutes was statistically significantly higher than 30, 60,

90, 120 and 240 minutes, p = < .002. The mean difference between the concentration of 3SH at

30 minutes and 60 minutes was not statistically significant, p = .344. The mean difference between the concentration of 3SH at 60 and 90 minutes (p = 1.000), as well as 60 and 120 minutes (p =.077), was not found to be statistically significant. However, the mean difference between the concentration of 3SH at 60 minutes and 240 minutes was statistically significant.

This significant difference observed between the concentrations of 3SH over time indicates that the effect of the treatment on the removal of 3SH can be observed in a four-hour time window.

Pairwise comparisons

The mean 3SH concentration was observed to not decrease significantly among the treatments and control until the 30-minute time point. Statistically significant mean differences between the CuCelite and the control were observed at 30, 60, 90, 120 and 240 minutes. At 30 minutes, the mean 3SH concentration of the CuCelite was 250 ± 14 uM and the control was 305

± 15 uM, a statistically significant mean difference of 55 uM less, p = .009. At 60 minutes, the mean 3SH concentration of the CuCelite was 208 ± 19 uM and the control was 300 ± 25 uM, a statistically significant mean difference of 92 uM less, p < .001. At 90 minutes, the mean 3SH

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concentration of the CuCelite was 200 ± 18 uM and the control was 298 ± 30 uM, a statistically significant mean difference of 98 uM less, p < .001. At 120 minutes, the mean 3SH concentration of the CuCelite was 195 ± 23 uM and the control was 290 ± 24 uM, a statistically significant mean difference of 95 uM less, p < .001. At 240 minutes, the mean 3SH concentration of the CuCelite was 155 ± 16 uM and the control was 277 ± 21 uM, a statistically significant mean difference of 121 uM less, p < .001. Overall, after 30 minutes, the mean difference between the 3SH concentration of the CuCelite treatment and the control was at least

55 uM, p <.009.

Statistically significant mean differences between the CuOAl and the control were observed at 60, 90, 120 and 240 minutes. At 60 minutes, the mean 3SH concentration of the CuOAl was

230 ± 19 uM and the control was 300 ± 25 uM, a statistically significant mean difference of 71 uM less, p < .001. At 90 minutes, the mean 3SH concentration of the CuOAl was 210 ± 15 uM and the control was 298 ± 30 uM, a statistically significant mean difference of 88 uM less, p <

.001. At 120 minutes, the mean 3SH concentration of the CuOAl was 205 ± 13 uM and the control was 290 ± 24 uM, a statistically significant mean difference of 86 uM less, p < .001. At

240 minutes, the mean 3SH concentration of the CuOAl was 204 ± 13 uM and the control was

277 ± 21 uM, a statistically significant mean difference of 77 uM less, p < .001. Overall, after 60 minutes, the mean difference between the 3SH concentration of the CuOAl treatment and the control was at least 71 uM, p <.000.

The CuSO4 was observed to have statistically significantly less mean 3SH concentration than the control at 30, 60, 90, 120 and 240 minutes. At 30 minutes, the concentration of CuSO4 was 255 ± 21 uM and control was 305 ± 15, a mean difference of 55 uM, p = .022. At 60 minutes, the concentration of the CuSO4 was 225 ± 24 and the control was 300 ± 25, a mean difference of 75 uM, p < .001. At 90 minutes, the concentration of the CuSO4 was 200 ± 10 and

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the control was 298 ± 30, a mean difference of 98 uM, p < .001. At 120 minutes, the mean difference in 3SH concentration was 115 uM less than that of the control, p < .001. At 240 minutes, the 3SH concentration of the CuSO4 was 100 ± 25 uM and the concentration of the control was 277 ± 21 uM, a statistically significant mean difference of 177 uM less than that of the control, p < .001. The CuSO4 treatment also resulted in much lower mean 3SH concentrations than in the CuOAl and the CuCelite at 240 minutes. At 240 minutes, the mean difference of 3SH concentration was 100 uM and 56 uM less for the CuOAl and the CuCelite, respectively, p <.008.

8.2.4 H2S Reduction by Bound Cu(II) over 24h

A two-way ANOVA was conducted to examine the effects of treatment and time on H2S concentration. There was a statistically significant difference between treatment and time for

2 H2S concentration, F(15, 48) = 2.316, p = .014, partial η = .420. Therefore, an analysis of simple main effects for treatment and time on mean 3SH concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in H2S concentration between treatments for at 2, 4 and 10 hours. There was not a statistically significant difference in H2S concentrations between treatments at 10 minutes, F(3,48) = 2.742, p = .053, partial η2 = .146. There was not a statistically significant difference in H2S concentrations between treatments at 30 minutes,

2 F(3,48) =1.865, p = .148, partial η = .104. There was a statistically significant difference in H2S concentrations between treatments at 2 hours, F(3,48) = 7.022, p = .001, partial η2 = .305.

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There was a statistically significant difference in H2S concentrations between treatments at 4 hours, F(3,48) = 12.254, p < .001, partial η2 = .434. There was a statistically significant difference in H2S concentrations between treatments at 10 hours, F(3,48) = 10.947, p < .001,

2 partial η = .406. There was not a statistically significant difference in H2S concentrations between treatments at 24 hours, F(3,48) = .716, p = .547, partial η2 = .043.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was a statistically significant difference in mean H2S concentration between time points for control F(5,48) =17.076, p < .001, partial η2 = .640. There was a statistically significant difference in mean H2S concentration between time points for CuSO4 F(5,48) =

2 24.185, p < .001, partial η = .716.There was a statistically significant difference in mean H2S concentration between time points for CuOAl F(5,48) = 23.430, p < .001, partial η2 = .706. There was a statistically significant difference in mean H2S concentration between time points for

CuCelite F(5,48) = 21.777, p < .001, partial η2 = .694.

Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 23.967, p < .001,

2 partial η = .600. The control treatment was associated with a mean H2S concentration 89.111 uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean H2S concentration 21.944 uM higher than the

CuOAl treatment, which not a statistically significant difference p = .330. The control treatment was associated with a mean H2S concentration 51.889 uM greater than the CuCelite treatment, which was a statistically significant difference, p =.000.

The CuSO4 treatment was associated with a mean H2S concentration 67.167 uM lower than the CuOAl treatment, which was statistically significant p < .001. The CuSO4 treatment was

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associated with a mean H2S concentration that was 37.222 uM lower than CuCelite, which was statistically significant, p = .010. The CuOAl treatment was associated with a mean H2S concentration that was 29.944 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = .060.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 79.522, p < .001, partial

2 η = .892. The concentration of H2S at 10 minutes was statistically significantly higher than 30 minutes, 2 hours, 4 hours, 10 hours and 24 hours, p = <.005. The mean difference between the concentration of H2S at 2 hours and 4 hours was not statistically significant, p = .081. The mean difference between the concentration of H2S at 4 hours and 10 hours was not statistically significant, p = .092. However, the mean difference between the concentration of H2S at 24 hours was statistically significantly lower than the concentration of H2S at all other time points, p

= <.001. This difference observed between the concentrations of H2S over time indicates that the effect of the treatment on the removal of H2S can be observed over a 24 hour time window.

Pairwise comparisons

The mean H2S concentration was observed to not deviate significantly among the treatments and control until the 4-hour time point. At 4 hours, the mean H2S concentration of the

CuCelite was 140 ± 20 uM and the control was 232 ± 35 uM, a statistically significant mean difference of 93 uM less, p = .008. At 10 hours, the mean difference in the H2S concentration of the CuCelite was 108 uM less than that of the control, p = .001. However, the concentration in the CuCelite did not significantly deviate from that of the control at 24 hours, and no significant mean differences were observed among any of the treatments at that time point. The mean difference in H2S concentration of the CuOAl and control was statistically significant only at 10

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hours, where the concentration of CuOAl was 122 ± 13 uM and the control was 206 ± 28 uM, with a mean difference of 84 uM, p = .021.

The CuSO4 treatment was observed to have statistically significantly less mean H2S concentration than the control at 2, 4, and 10 hours. At 2 hours, the H2S concentration of CuSO4 was 95 ± 10 uM and control was 130 ± 34 uM, a mean difference of 115 uM, p = .001. At 4 hours, the, the H2S concentration of CuSO4 was 75 ± 20 uM and control was 232 ± 35 uM, a mean difference of 158 uM, p < .001. At 10 hours, the concentration of the CuSO4 was 54 ± 12 uM and the control was 206 ± 28 uM, a mean difference of 152 uM, p < .001. The CuSO4 treatment also resulted in much lower mean H2S concentrations than in the CuOAl at 2 and 4 hours. At 4 hours, the mean difference of H2S concentration was 99 uM greater for the CuOAl, p

<.004. At 4 hours, the mean difference of H2S concentration was 113 uM greater for the CuOAl, p <.001. However, at all other time points no significant differences were observed between the

CuSO4 and the CuOAl. No significant differences were observed in the mean differences in H2S concentration between the CuSO4 and the CuCelite treatment.

8.2.5 Cys Reduction by Bound Cu(II) over 24h

A two-way ANOVA was conducted to examine the effects of treatment and time on Cys concentration. There was a statistically significant difference between treatment and time for

Cys concentration, F(15, 48) = 2.969, p = .002, partial η2 = .481. Therefore, an analysis of simple main effects for treatment and time on mean Cys concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

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There was a statistically significant difference in Cys concentration between treatments at all time points: 10 minutes, 30 minutes, 2 hours, 4 hours, 10 hours and 24 hours. There was a statistically significant difference in Cys concentrations between treatments at 10 minutes,

F(3,48) = 22.564, p < .001, partial η2 = .585. There was a statistically significant difference in

Cys concentrations between treatments at 30 minutes, F(3,48) =13.433, p < .001, partial η2 =

.456. There was a statistically significant difference in Cys concentrations between treatments at

2 hours, F(3,48) = 15.456, p < .001, partial η2 = .491. There was a statistically significant difference in Cys concentrations between treatments at 4 hours, F(3,48) = 23.218, p < .001, partial η2 = .592. There was a statistically significant difference in Cys concentrations between treatments at 10 hours, F(3,48) = 15.513, p < .001, partial η2 = .492. There was a statistically significant difference in Cys concentrations between treatments at 24 hours, F(3,48) = 10.709, p

< .001, partial η2 = .401.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

There was a statistically significant difference in mean Cys concentration between time points for control F(5,48) = 12.272, p < .001, partial η2 = .561. There was a statistically significant difference in mean Cys concentration between time points for CuSO4 F(5,48) =

10.843, p < .001, partial η2 = .530.There was a statistically significant difference in mean Cys concentration between time points for CuOAl F(5,48) = 38.056, p < .001, partial η2 = .799. There was a statistically significant difference in mean Cys concentration between time points for

CuCelite F(5,48) = 29.125, p < .001, partial η2 = .752.

Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 86.047, p < .001, partial η2 = .843. The control treatment was associated with a mean Cys concentration 189.056

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uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean Cys concentration 78.611 uM higher than the

CuOAl treatment, which was a statistically significant difference p < .001. The control treatment was associated with a mean Cys concentration 108.167 uM greater than the CuCelite treatment, which was a statistically significant difference, p =.000.

The CuSO4 treatment was associated with a mean Cys concentration 110.444 uM lower than the CuOAl treatment, which was statistically significant p < .001. The CuSO4 treatment was associated with a mean Cys concentration that was 80.889 uM lower than CuCelite, which was statistically significant, p < .001. The CuOAl treatment was associated with a mean Cys concentration that was 29.556 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = .100.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 81.388, p < .001, partial

η2 = .894. The concentration of Cys at 10 minutes was statistically significantly higher than 2, 4,

10 and 24 hours, p < .001. The mean difference between the concentration of Cys at 10 minutes and 30 minutes was not statistically significant, p = 1.000. The mean difference between the concentration of Cys at 2 and 4 hours was not statistically significant, p=.142. The mean difference between the concentration of Cys at 4 hours and 10 hours was not statistically significant, p = .119. The mean difference between the concentration of Cys at all time points versus 24 hours was statistically significant, p = <.028. This significant difference observed between the concentrations of Cys over time indicates that the effect of the treatment on the removal of Cys can be observed in a 24-hour time window.

Pairwise comparisons

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The mean difference of the Cys concentration in the CuSO4 treatment was observed to decrease significantly from the control at all time points. After 10 minutes, the mean Cys concentration of the CuSO4 was 170 ± 27 uM and the control was 374 ± 78 uM, a statistically significant mean difference of 203 uM less, p < .001. At 30 minutes, the mean difference was

162 uM, p < .001. After 24 hours, the mean difference of Cys concentration 146 uM, p < .001.

Similar results were observed between the CuSO4 and CuOAl. At 10 minutes, there were no significant mean differences in Cys concentration between the treatments; however, after 30 minutes the mean difference in Cys concentration in the CuSO4 was lower by 157 uM than that of the CuOAl (p =.000), and 100 uM lower than the CuCelite (p = .008). At 2 hours, the mean difference in Cys concentration between CuSO4 and CuOAl was 98 uM, p = .009. At 4 hours, the mean difference in Cys concentration between CuSO4 and CuOAl was 116 uM, p = .001.

There were no significant mean differences between the Cys concentration of CuSO4 and

CuCelite at 2 or 4 hours. At 10 and 24 hours, there were no significant differences in the mean

Cys concentration between the CuSO4, CuOAl or CuCelite treatments.

The mean Cys concentration in the CuOAl did not significantly deviate from that of the control until after 2 hours. At 2 hours, the mean Cys concentration of the CuOAl was 230 ± 29 uM and the control was 324 ± 25 uM, a statistically significant mean difference of 94 uM less, p

= .014. At 4 hours, the Cys concentration of the CuOAl was 119 uM less than the control, p =

.001. After 10 hours, the mean difference was 128 uM, p < .001. At 24 hours, the mean difference was 130 uM, with the Cys concentration of CuOAl at 65 ± 18 and the control at 190 ±

28 uM.

The Cys concentration in the CuCelite did not significantly deviate from that of the control until after 2 hours. At 2 hours, the mean Cys concentration of the CuCelite was X and the control was X, a statistically significant mean difference of 136 uM less, p = .014. At 4 hours, the

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Cys concentration of the CuCelite was 170 uM less than the control, p < .001. After 10 hours, the mean difference was 122 uM, p = .001. At 24 hours, the mean difference was 130 uM, with the Cys concentration of CuCelite at 64 ±27 uM and the control at 190 ± 28 uM. While the Cys concentration of the CuCelite was less than that of the CuOAl for all time points, no statistically significant mean differences were observed.

8.2.6 3SH Reduction by Bound Cu(II) over 24h

A two-way ANOVA was conducted to examine the effects of treatment and time on 3SH concentration. There was a statistically significant difference between treatment and time for

3SH concentration, F(15, 48) = 2.960, p < .001, partial η2 = .481. Therefore, an analysis of simple main effects for treatment and time on mean 3SH concentration was performed with statistical significance receiving a Bonferroni adjustment and being accepted at the p < .025 level. All pairwise comparisons were run for each simple main effect with reported 95% confidence intervals and p-values Boneferroni-adjusted within each simple main effect.

Simple main effects for treatment at each level of time, which determines the main effect of treatment at each time point.

There was a statistically significant difference in 3SH concentration between treatments for all time points, except at 30 minutes. There was a statistically significant difference in 3SH concentrations between treatments at 10 minutes, F(3,48) = 3.252, p = .030, partial η2 = .169.

There was not a statistically significant difference in 3SH concentrations between treatments at

30 minutes, F(3,48) = 1.097, p = .360, partial η2 = .064. There was a statistically significant difference in 3SH concentrations between treatments at 2 hours, F(3,48) = 4.090, p = .012, partial η2 = .204. There was a statistically significant difference in 3SH concentrations between treatments at 4 hours, F(3,48) = 15.210, p < .001, partial η2 = .487. There was a statistically significant difference in 3SH concentrations between treatments at 10 hours, F(3,48) = 12.859,

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p < .001, partial η2 = .446. There was a statistically significant difference in 3SH concentrations between treatments at 24 hours, F(3,48) = 10.636, p < .001, partial η2 = .399.

Simple main effects for time at each treatment, which determines the main effect of time on each treatment.

The simple main effects of time on each treatment was statistically significant for all the treatments and the control. There was a statistically significant difference in mean 3SH concentration between time points for the control F(5,48) = 20.089, p < .001, partial η2 = .752.

There was a statistically significant difference in mean 3SH concentration between time points

2 for CuSO4 F(5,48) = 69.918, p < .001, partial η = .879. There was a statistically significant difference in mean 3SH concentration between time points for CuOAl F(5,48) = 48.802, p <

.001, partial η2 = .834. There was a statistically significant difference in mean 3SH concentration between time points for CuCelite F(5,48) = 56.308, p < .001, partial η2 = .854.

Main effect of treatment

There was a statistically significant main effect of treatment F(3,48) = 32.343, p < .001, partial η2 = .669. The control treatment was associated with a mean 3SH concentration 60.944 uM higher than the CuSO4 treatment, which was a statistically significant difference, p < .001.

The control treatment was associated a mean 3SH concentration 16.722 uM higher than the

CuOAl treatment, which was not found to be a statistically significant difference, p = .076. The control treatment was associated with a mean 3SH concentration 33.222 uM greater than the

CuCelite treatment, which was a statistically significant difference, p =.000.

The CuSO4 treatment was associated with a mean 3SH concentration 44.222 uM lower than the CuOAl treatment, which was statistically significant p < .001. The CuSO4 treatment was associated with a mean 3SH concentration that was 27.722 uM lower than CuCelite, which was statistically significant, p = .001. The CuOAl treatment was associated with a mean 3SH

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concentration that was 16.500 uM greater than that of the CuCelite treatment, which was not found to be statistically significant p = .083.

Main effect of time

There was a statistically significant main effect of time F(5, 48) = 194.836, p < .001, partial

η2 = .953. The concentration of 3SH at 10 minutes was statistically significantly higher than all other time points, p < .001. The mean difference between the concentration of 3SH between each time point was statistically significant, p < .041. This significant difference observed between the concentrations of 3SH over time indicates that the effect of the treatment on the removal of 3SH can be observed in a 24-hour time window.

Pairwise comparisons

The mean 3SH concentration was observed to not decrease significantly among the treatments and control until the 2-hour time point. After 2 hours, the mean 3SH concentration of the CuCelite was 204 ± 21 uM and the control was 242 ± 22 uM, a statistically significant mean difference of 48 uM less, p = .023. However, the concentration in the CuCelite did not significantly deviate from that of the control again until 24 hours. At 24 hours, the mean 3SH concentration of the CuCelite was X and the control was X, a statistically significant mean difference of 62 uM less, p = .002.

The CuSO4 was observed to have statistically significantly less mean 3SH concentration than the control at 4, 10 and 24 hours. At 4 hours, the concentration of CuSO4 was 95 ± 10 uM and control was 196 ± 28, a mean difference of 101 uM, p < .001. At 10 hours, the concentration of the CuSO4 was and the control was, a mean difference of 95 uM, p < .001. At

24 hours, the 3SH concentration of the CuSO4 was 65 ± 23 uM and the concentration of the control was151 ± 26 uM, a statistically significant mean difference of 86 uM less than that of the control, p < .001. The CuSO4 treatment also resulted in much lower mean 3SH concentrations

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than in the CuOAl and the CuCelite. At 4 hours, the mean difference of 3SH concentration was

80 uM and 59 uM less for the CuOAl and the CuCelite, respectively, p <.003. At 10 hours, the mean difference in 3SH concentration between the CuSO4 and the CuOAl and CuCelite was 68 uM (p < .001) and 49 uM (p = .021), respectively. However, at 24 hours no significant differences were observed between the CuSO4 and the CuOAl or CuCelite.

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