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Investigations of wine and grape skin tannins from the Okanagan valley Visintainer, Dawn Michaela 2013

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INVESTIGATIONS OF WINE AND GRAPE SKIN TANNINS FROM THE OKANAGAN VALLEY by Dawn Michaela Visintainer  B.Sc., The University of British Columbia, 2010  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE  in  THE COLLEGE OF GRADUATE STUDIES  BIOCHEMISTRY AND MOLECULAR BIOLOGY  THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan)  December 2013 ? Dawn Michaela Visintainer, 2013 ii  Abstract  A grape skin tannin profile was established throughout berry development in Oliver, Naramata, and Osoyoos, three sites in the Okanagan area of British Columbia, using both 70% acetone and 12% ethanol as extraction solvents. Tannins were analyzed by ultra-high pressure liquid chromatography (UHPLC) to determine how total tannins, mean degree of polymerization (mDP), and percent subunit composition varied. Tannins for each sample did vary by more than 20% with the exception of one sample set. All of the samples? mDP did not vary by more than 20%, with the exception of two sample sets; most of the percent subunit composition also did not vary by more than 20% with the exception of one sample set.  These same samples were then analyzed by methyl cellulose precipitation assay (MCP) to determine tannin content in relation to astringency. It was predicted that as more tannins bonded with polysaccharide over the course of berry development, the astringency would decrease. We found a low correlation between total tannins quantified by the MCP assay and by UHPLC (r2 < 0.52), and between total tannins quantified by the MCP assay and mDP calculated via analysis by UHPLC (r2 > 0.37).  A new gelatin adsorption assay to determine tannin quantity in wines was also developed. This method allows tannins in wine to bind with gelatin. Then, by recording the absorption of phenolic compounds at 280 nm before and after binding, we ascertained a value related to astringency. There was a good correlation between the Gelatin Adsorption Assay and the established MCP assay: r2= 0.99 when using model wine with the addition of grape seed extract, and r2= 0.98 when using real red wine samples. This method will allow for a cheaper way to evaluate tannins in red wines.  iii  Table of Contents Abstract ........................................................................................................................................... ii Table of Contents ........................................................................................................................... iii List of Tables .................................................................................................................................. v List of Figures ............................................................................................................................... vii Acknowledgments......................................................................................................................... xv Chapter 1: Introduction ................................................................................................................... 1 1.1 Grape Vine and Berry Characteristics ................................................................................... 1 1.2 Phenolics and Their Biosynthesis ....................................................................................... 10 1.3 Phenolic Accumulation During Ripening ........................................................................... 23 1.4 Extractability of Tannins from Grape Skin ......................................................................... 34 1.5 Thesis Aims and Hypotheses .............................................................................................. 38 Chapter 2: Research Chapter 1: Polyphenol from Pre-V?raison to Harvest ................................. 40 2.1 Synopsis .............................................................................................................................. 40 2.2 Materials and Methods ........................................................................................................ 41 2.3 Results and Discussion ........................................................................................................ 46 Chapter 3: Research Chapter 2: Comparison of Tannin Content with their Reactivity as   Measured by the MCP Assay ....................................................................................................... 66 3.1 Synopsis .............................................................................................................................. 66 3.2 Materials and Methods ........................................................................................................ 67 iv  3.3 Results and Discussion ........................................................................................................ 69 Chapter 4: Research Chapter 3: New Gelatin Adsorption Assay ................................................. 76 4.1 Synopsis .............................................................................................................................. 76 4.2 Materials and Methods ........................................................................................................ 77 4.3 Results and Discussion ........................................................................................................ 81 Chapter 5: Conclusion................................................................................................................... 87 5.1 Conclusion Summary .......................................................................................................... 87 5.2 Limitations/ Variation ......................................................................................................... 88 5.3 Suggestions for Future Research ......................................................................................... 89 References ..................................................................................................................................... 91 Appendices .................................................................................................................................. 107 Appendix A: Calibration Curves for Subunits ........................................................................ 107 Appendix B: Calibration Curves for mDP .............................................................................. 109 Appendix C: Correlation Between total tannins measured by MCP and Total Tannins Measured by UHPLC of mDP ................................................................................................ 112     v  List of Tables Table 1.1:  Total tannin v?raison to harvest. CE= catechin equivalents ....................................... 25 Table 1.2:  mDP v?raison to harvest  ............................................................................................ 28 Table 1.3:  Subunit composition in grapes skins as ripening proceeds ........................................ 30 Table 2.1:  The weight of 50 grape berry skins from pre-v?raison to harvest was  analyzed by linear regression ..................................................................................... 47 Table 2.2:  The total amount of tannins per berry from pre-v?raison to harvest was  analyzed by linear regression. N=8 for Naramata and Osoyoos and N=7  for Oliver .................................................................................................................... 48 Table 2.3:  The linear regression of total tannins measured by UHPLC from  pre-v?raison and post-v?raison was analyzed for each site and solvent  with ?an ?? ?value ?of ?0.05 ............................................................................................... 50 Table 2.4:  Average, standard deviation, and percent coefficient of variation for the  total amount of tannins during the entire sampling period for each site and  both extraction solvents  ............................................................................................ 51 Table 2.5:  The mean degree of polymerization of tannins from pre-v?raison to harvest  was analyzed by linear regression for each site and each solvent  ............................ 53 Table 2.6:  The linear regression of mPD of tannin molecules from grape skins  measured by UHPLC during pre-v?raison and post-v?raison was analyzed  for each site with an ?? ?value of 0.05 .......................................................................... 54 Table 2.7:   Average, standard deviation, and percent coefficient of variation for mDP  over the entire course of berry development for each site and solvent ...................... 55 Table 2.8:   The linear regression for the subunit composition of tannin molecules from  vi  grape skins measured by UHPLC for pre-v?raison and post-v?raison were  analyzed for each site with an ? ?value ?of ?0.05 ........................................................... 61 Table 2.9:   Linear regression for tannin subunit composition during development for  each site and both extraction solvents ........................................................................ 63 Table 2.10: Average, standard deviation, and percent coefficient of variation for tannin  subunit composition during development for each site and both extraction  solvents....................................................................................................................... 64 Table 3.1:  Total tannins measured by MCP were analyzed using linear regression to  access changes over the course of berry development for all sampling dates  at each site with ? ?of ?0.05 .......................................................................................... 70 Table 3.2:   Linear regression was analyzed for total tannins measured by MCP for  different sampling dates at each ?site ?with ?an ?? ?value ?of ?0.05 .................................... 72 Table 3.3:   Linear regression was analyzed for total tannins measured by MCP  compared to mean degree of polymerization (mDP) and for total tannins  measured by MCP compared to those measured by UHPLC, for each  sampling ?dates ?and ?site ?with ?an ?? ?value ?of ?0.05 ........................................................ 73 Table 4.1:   List of wine (winery and year) samples used to validate the new Gelatin  Adsorption Assay ....................................................................................................... 78      vii  List of Figures Figure 1.1:    Structure of a grape cluster and the cross section of a grape berry at maturity.  Re-drawn from Rib?reau-Gayon et al., 2006a. .......................................................... 2 Figure 1.2:    Berry weight changes throughout development from fruit set to ripeness.  Redrawn and adapted from Coombe and Hale 1973: Berry growth;  Phase I: early fruit development; Phase II: lag phase; Phase III: berry  ripening. ..................................................................................................................... 5 Figure 1.3:    Biosynthetic pathway of the major phenolic classes ............................................... 14 Figure 1.4:    Basic monomer tannin structure found in grape skins can be linked by a  carbon-carbon inter-flavan bond (C4-C6 or C4-C8) to form polymers. R1  can be a hydrogen group or a gallate group and R2 can be hydrogen or a  hydroxyl group ........................................................................................................ 15 Figure 1.5:    Structure of the flavanol-3-ol monomeric molecules that are subunits that  make up tannins in grape skins ................................................................................ 16 Figure 1.6:    Biosynthesis of (+)-catechin and (-)-epicatechin from caffeoyl CoA and  malonyl-CoA adapted and re-drawn from Adams (2006). CHS, chalcone  synthase; CHI, chalcone isomerase; F3H, flavanone-3-hydroxylase; DFR,  dihydroflavonol-4-reductase; LAR, leucoanthocyanidin reductase; ANS,  anthocyanidin synthase; ANR, anthocyanidin reductase; UFGT, UDP  glucose-flavonoid 3-O-glucosyl transferase. ........................................................... 17 Figure 1.7:    Basic structure of anthocyanidins, the precursors to anthocyanins.  Anthocyanins have a glucose molecule bonded to the oxygen which is  bonded to the carbon at position three (R1). In certain varieties,  viii  Cabernet franc and Merlot, but not Pinot noir, some esterification can  occur on the OH function of the glucose with coumaric or acetic acid.  R3 and R2 are substituted with either a hydrogen molecule (H), a  hydroxyl molecule (OH), or a methoxy molecule (OCH3) ..................................... 18 Figure 1.8:    Structure of the five anthocyanidins found in Pinot noir. Anthocyanidins  are precursors to anthocyanins where anthocyanins have a glucose  molecule bonded to the oxygen molecule at position 3 ........................................... 19 Figure 1.9:    Pathway showing anthocyanin biosynthesis ........................................................... 21 Figure 1.10:  Biosynthetic flavonoid pathway leading to the production of  proanthocyanidin polymer (condensed tannin) and anthocyanidin re-drawn  and adapted from Bogs et al. (2005); ANS, anthocyanidin synthase;  UFGT, UDP glucose-flavonoid 3-O-glucosyl transferase; LAR,  leucoanthocyanidin reducatase; ANR, anthocyanidin reductase. ............................ 22 Figure 2.1:    Extraction kinetics of Pinot noir grape skin when using 20 mL of 70%  acetone per g of grape skin as the solvent. Showing standard deviation  error bars; N=9 ......................................................................................................... 43 Figure 2.2:    Extraction kinetics of Pinot noir grape skin when using 20 mL of 12%  ethanol per g of grape skin as the solvent. Showing standard deviation  error bars; N=3 ......................................................................................................... 43 Figure 2.3:    The weight of fifty berry skins at each sampling date. Showing standard  deviation error bars; N= 6 ........................................................................................ 47 Figure 2.4:    Grape skin tannins extracted from Oliver, Naramata, and Osoyoos over  the course of berry development using 70% acetone as the solvent.  ix  Showing standard deviation error bars; N= 9. ......................................................... 49 Figure 2.5:    Grape skin tannins extracted from Oliver, Naramata, and Osoyoos over  the course of berry development using 12% ethanol as the solvent.  Showing standard deviation error bars; N= 9. ......................................................... 49 Figure 2.6:    Grape skin tannins mean degree of polymerization extracted from  Oliver (PN), Naramata (CF), and Osoyoos (CF) over the course of  berry development using 70% acetone as the solvent. Showing standard  deviation error bars; N= 9 ........................................................................................ 53 Figure 2.7:    Grape skin tannins mean degree of polymerization extracted from  Oliver (PN), Naramata (CF), and Osoyoos (CF) over the course of berry  development using 12% ethanol as the solvent. Showing standard  deviation error bars; N= 9 ........................................................................................ 54 Figure 2.8:    Oliver (Pinot noir) tannin subunit composition over development  extracted using 70% acetone. EGC: (-)-Epigallocatechin; ECG:  (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9 ............... 56 Figure 2.9:    Oliver (Pinot noir) tannin subunit composition over development  extracted using 12% ethanol. EGC: (-)-Epigallocatechin; ECG:  (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9 ............... 57 Figure 2.10:  Naramata (Cabernet Franc) tannin subunit composition over  development extracted using 70% acetone. EGC: (-)-Epigallocatechin;  ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin.  N= 9 ......................................................................................................................... 57 Figure 2.11:  Naramata (Cabernet Franc) tannin subunit composition over  x  development extracted using 12% ethanol. EGC: (-)-Epigallocatechin;  ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin.  N= 9 ......................................................................................................................... 58 Figure 2.12:  Osoyoos (Cabernet Franc) tannin subunit composition over  development extracted using 70% acetone. EGC: Epigallocatechin;  ECG: Epicatechin-3-O-gallate; EC: Epicatechin; C: Catechin. N= 9 ..................... 58 Figure 2.13:  Osoyoos (Cabernet Franc) tannin subunit composition over  development extracted using 12% ethanol. EGC: Epigallocatechin;  ECG: Epicatechin-3-O-gallate; EC: Epicatechin; C: Catechin. N= 9 ..................... 59 Figure 3.1:    Tannins quantified by MCP from Oliver (Pinot noir) throughout the  course of berry development expressed in epicatechin equivalence.  Showing standard deviation error bars; N= 9  ......................................................... 71 Figure 3.2: Tannins quantified by MCP from Naramata (Cabernet Franc)  throughout the course of berry development expressed in epicatechin  equivalence. Showing standard deviation error bars; N= 9 ..................................... 71 Figure 3.3:    Tannins quantified by MCP from Osoyoos (Cabernet Franc) throughout  the course of berry development expressed in epicatechin equivalence.  Showing standard deviation error bars; N= 9. ......................................................... 72 Figure 3.4:    Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin extract  from Oliver extracted with 70% acetone measured throughout berry  development.  N=9 at each sampling date. .............................................................. 74 Figure 4.1:    (-)-Epicatechin calibration curve performed at 280nm. Showing standard  xi  deviation error bars; N= 3. ....................................................................................... 80 Figure 4.2:    Reaction kinetics for tannin precipitating gelatin. Showing standard  deviation error bars; N= 4 ........................................................................................ 82 Figure 4.3:    Linearity of gelatin-tannin binding expressed in g L-1 (-)-epicatechin  equivalence from varying concentrations of grape seed extract in  model wine. Showing standard deviation error bars; N= 3 ..................................... 83 Figure 4.4:    Recovery of gelatin-tannin binding from a concentrated solution of  grape seed extract added to wine or model wine in varying amounts  to obtain different concentrations. Theoretical values represent 100%  recovery. Data expressed in (-)-epicatechin equivalence. Showing  standard deviation error bars; N= 3 ......................................................................... 83 Figure 4.5:    Correlation of MCP to the new Gelatin Adsorption Assay using grape  seed extract added to model wine in different amounts. Data expressed  in (-)-epicatechin equivalence. N= 3 ....................................................................... 84 Figure 4.6:    Correlation of MCP to the new Gelatin Adsorption Assay from twelve  different wines. Data is expressed in (-)-epicatechin equivalence and  each wine was analyzed in triplicate ....................................................................... 85 Figure A.1:    Calibration curve for catechin and epicatechin with or without  phloroglucinol. Showing standard deviation error bars; N= 3 .............................. 107 Figure A.2:    Calibration curve for epigallocatechin (EGC) with phloroglucinol  attached. Showing standard deviation error bars; N= 3 ......................................... 107 Figure A.3:    Calibration curve for epicatechin gallate (ECG) without phloroglucinol  attached. Showing standard deviation error bars; N= 3 ......................................... 108 xii  Figure A.4:    Calibration curve for epicatechin gallate (ECG) with phloroglucinol  attached. Showing standard deviation error bars; N= 3. ........................................ 108 Figure B.1:    Calibration curve for catechin (C) and epicatechin (EC) without  phloroglucinol, concentration expressed in mmol/L to be used in  calculation of mean degree of polymerization. Showing standard  deviation error bars; N= 3 ...................................................................................... 109 Figure B.2:    Calibration curve for catechin and epicatechin with phloroglucinol  attached, concentration expressed in mmol/L to be used in calculation  of mean degree of polymerization. Showing standard deviation error  bars; N= 3 .............................................................................................................. 109 Figure B.3:    Calibration curve for epigallocatechin (EGC) with phloroglucinol  attached, concentration expressed in mmol/L to be used in calculation  of mean degree of polymerization. Showing standard deviation error  bars; N= 3 .............................................................................................................. 110 Figure B.4:    Calibration curve for epicatechin gallate (ECG) without phloroglucinol,  concentration expressed in mmol/L to be used in calculation of mean  degree of polymerization. Showing standard deviation error bars; N= 3 .............. 110 Figure B.5:    Calibration curve for epicatechin gallate with phloroglucinol attached,  concentration expressed in mmol/L to be used in calculation of mean  degree of polymerization. Showing standard deviation error bars; N= 3 .............. 111 Figure C.1:   Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin extract  from Oliver extracted with 12% ethanol measured throughout berry  xiii  development ........................................................................................................... 112 Figure C.2:   Correlation between total tannin precipitated by MCP expressed in  epicatechin equivalence and mDP calculated through analysis by  UHPLC. Samples are of grape skin extract from Oliver extracted with  12% ethanol measured throughout berry development ......................................... 112 Figure C.3:   Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin extract  from Naramata extracted with 70% acetone measured throughout berry  development ........................................................................................................... 113 Figure C.4:   Correlation between total tannin precipitated by MCP expressed in  epicatechin equivalence and mDP calculated through analysis by UHPLC.  Samples are of grape skin extract from Naramata extracted with 70%  acetone measured throughout berry development ................................................. 113 Figure C.5:   Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin extract  from Naramata extracted with 12% ethanol measured throughout berry  development ........................................................................................................... 114 Figure C.6:   Correlation between total tannin precipitated by MCP expressed in  epicatechin equivalence and mDP calculated through analysis by  UHPLC. Samples are of grape skin extract from Naramata extracted with  12% ethanol measured throughout berry development ........................................ 114 Figure C.7:   Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin  xiv  extract from Osoyoos extracted with 70% acetone measured throughout  berry development ................................................................................................. 115 Figure C.8:   Correlation between total tannin precipitated by MCP expressed in  epicatechin equivalence and mDP calculated through analysis by UHPLC.  Samples are of grape skin extract from Osoyoos extracted with 70%  acetone measured throughout berry development ................................................. 115 Figure C.9:   Correlation between total tannins measured by MCP and by UHPLC  expressed in epicatechin equivalence. Samples are of grape skin extract  from Osoyoos extracted with 12% ethanol measured throughout berry  development ........................................................................................................... 116 Figure C.10: Correlation between total tannin precipitated by MCP expressed in  epicatechin equivalence and mDP calculated through analysis by UHPLC.  Samples are of grape skin extract from Osoyoos extracted with 12%  ethanol measured throughout berry development ................................................. 116         xv  Acknowledgments   This research project would not have been possible without the support of many people. I wish to express my gratitude to my two supervisors, Dr. C?dric Saucier and Dr. Melanie Jones who were tremendously helpful by providing useful comments, remarks, and engagement through the learning process of this masters thesis. I would also like to thank the members of my supervisory committee, Dr. Soheil Mahmoud and Dr. Miranda Hart; without their knowledge and guidance this study would not have been successful. A special thanks also to Dr. Adeline Delcambre because, without her knowledge and invaluable assistance, this study would not have been possible and also to Ryan Moss and Yann Andre for their guidance and support through the duration of this research project. I would like to thank my loved ones who have supported me throughout the entire process. I would also like to convey thanks to the sponsors who provided the funding which without this project would not have been possible; British Columbia Wine and Grape Council- Agriculture and Agri-Food Canada (Developing Innovative Agri-Products Grant), Canada Foundation for Innovation (Leader Opportunity Fund Grant), Agilent Technologies (Equipment Grant), and Natural Sciences and Engineering Research Council of Canada (Discovery Grant). 1  Chapter 1: Introduction 1.1 Grape Vine and Berry Characteristics The common wine and edible grapes are mostly woody or herbaceous lianas (tree-climbing plants) or shrubs with liana stems, from the genus Vitis in the family Vitaceae (Alleweldt and Possingham, 1988; Mullins et al., 1992). Inflorescences opposite to leaves and coiled tendrils characterize the Vitaceae, originating in Asia, but now grown primarily between 20? and 50? latitude, north or south of the equator (Alleweldt and Possingham, 1988; Mullins et al., 1992). Vitis contains approximately 60 species and is found natively in the temperate areas of the Northern hemisphere (Mullins et al., 1992). One of the most common wine grapes, Vitis vinifera, is native to the Mediterranean region, central Europe, and southwest Asia but has been spread throughout the world by human activity (Mullins et al., 1992). Vitis vinifera grape vines predominantly grow in drier, semi-arid climates where temperatures of the summer months, either July in the Northern hemisphere or January in the Southern hemisphere, vary between 15 ?C and 25 ?C (Conde et al., 2007). The acquisition of an adequate amount of water and nitrogen by vines of these regions is essential because of loamy sand or sandy loam soils in these areas, which are low in nitrogen and can become dry in the growing season (Winkel and Rambal, 1993; Bowen et al., 2005).  Vine and Berry Physiology  Vines produce clusters of grapes attached to the vine by the peduncle, which in turn extends into the rachis where individual berries are attached to the rachis by pedicels (Figure 1.1). The pedicel contains xylem vessels that extend into the berries, delivering water and nutrients to the berry from the vine (Rib?reau-Gayon et al., 2006a). During v?raison, which is the onset of ripening, the flow of water switches from primarily xylem to primarily phloem transport 2  (Findlay et al., 1987; Lang and Thorpe, 1989; Lang and During, 1991; Coombe, 1992; Creasy and Lombard, 1993; Bondada et al., 2005). It is however, not agreed on how this switch occurs. Diurnal solute partitioning (Bondada et al., 2005), un-functional tracheids (Findlay et al., 1987), the formation of an embolism (Lang and Thorpe, 1989; Coombe, 1992; Creasy and Lombard, 1993), or the in-ability of xylem cells, during phase two of berry growth, to lengthen causing gaps in the xylem (Lang and During, 1991) are all current theories explaining how restricted flow to the xylem occurs. This restriction in xylem flow, during v?raison, leads to decreased hydraulic conductivity in the berry. As a result of this process, sugary sap fills the berries. The sugar stays in the berries despite high water potentials in the vine (Creasy and Lombard, 1993).  Figure 1.1: Structure of a grape cluster and the cross section of a grape berry at maturity. Re-drawn from Rib?reau-Gayon et al., 2006a.    Vine development can be broken down into a number of growth stages associated with vine and berry maturity. During winter, the vines are dormant and have light or dark brown, 3  closed bud scales (Hellman, 2003). In the spring, the buds begin to swell but stay brown (Coombe, 1995; Hellman, 2003). When average daily temperatures reach 10 ?C, the shoots begin to grow, the buds burst, and green tips become visible (Hellman, 2003).  The leaves then begin to unfold until nine or more leaves have unfolded (Hellman, 2003).  At this time the inflorescences become visible and start to swell while the flowers get closely pressed together (Srinivasan and Mullins, 1981; Hellman, 2003). When the inflorescences are fully developed, the flowers separate. Flowering starts when the first caps are detached from the receptacle and continues until all the caps have fallen off, signifying the end of flowering and the start of fruit set (Hellman, 2003). Fruit set finishes two to three weeks after flowering starts (Mullins et al., 1992; Hellman, 2003). After fruit set, shoot growth comes to an end and the young fruits begin to swell and grow, clusters begin to hang, and the berries begin to touch (Hellman, 2003). Once the majority of berries are touching, the berries begin to soften, ripen and develop color, indicating the berries are in v?raison (Coombe, 1992; Hellman, 2003). When all the berries have changed color and the sugar and acid levels are at the amounts sought after by the winemaker, harvest takes place. After harvest, the leaves begin to lose color and fall off and the vine enters dormancy again (Hellman, 2003).    Growth Patterns and Compound Accumulation A double sigmoid growth pattern with two distinct growth periods (Figure 1.2) is observed in the berry, where changes in phenolic composition occur throughout maturation (Coombe and Hale, 1973; Considine and Knox, 1979; Kennedy and Waterhouse, 2000; Kennedy et al., 2001; Conde et al., 2007). Monomeric and polymeric flavanols accumulate in the skin during phase I, the first period of growth associated with the grape berries (Kennedy and Waterhouse, 2000; Kennedy et al., 2001). The first phase is associated with a rapid growth 4  period lasting 45 to 65 days where the berries have increased metabolic activity with the rapid accumulation of acids and elevated respiration (Harris et al., 1968; Pratt, 1971; Rib?reau-Gayon et al., 2006a). Phase II, or the lag period, occurs next with an absence of growth coinciding with v?raison (Rib?reau-Gayon et al., 2006a; Conde et al., 2007). During v?raison, there is a change in berry skin color with the berries becoming hard and acidic, with little sugar (Pratt, 1971; Conde et al., 2007). This phase lasts 8 to 15 days but can last longer if flowering is delayed (Rib?reau-Gayon et al., 2006a). During this time there is depletion in cytokinins and gibberellins required for growth and an increase in abscisic acid concentration (Hale, 1968; Rib?reau-Gayon et al., 2006a; Conde et al., 2007; Lacampagne et al., 2010). The next phase, phase III, coincides with a second period of growth (Rib?reau-Gayon et al., 2006a). The walls of the outer hypodermal cells swell, which correlates to an increase in fruit plasticity (Considine and Knox, 1979). This phase usually occurs in August (northern hemisphere) and lasts 35 to 55 days with the berries becoming larger, softer, sweeter, and less acidic, with robust flavour and color (Rib?reau-Gayon et al., 2006a; Conde et al., 2007). Total polyphenol contents follow a similar pattern as berry size, with a slow continuous increase from fruit set until v?raison (Considine and Knox, 1979). Then, 28 to 35 days after v?raison, a faster increase is seen (Considine and Knox, 1979). Towards harvest however, a decrease is observed in some cases (Pirie and Mulins, 1977; Considine and Knox, 1979; Delgado et al., 2004; Conde et al., 2007).  5   Figure 1.2: Berry weight changes throughout development from fruit set to ripeness. Redrawn and adapted from Coombe and Hale 1973: Berry growth; Phase I: early fruit development; Phase II: lag phase; Phase III: berry ripening.   Grape Skin Physiology  Grape skin consists of many phenolic compounds that influence the quality of wine. The accumulation of these compounds in the skin is influenced by many factors including varietal (Van Leeuwen et al., 2004; Chira et al., 2009; Revilla et al., 2010), vine vigor (Cortell et al., 2005), climate (Poni et al., 1994; Chira et al., 2011, Ferrer-Gallego et al., 2012), soil (Van Leeuwen et al., 2004; Morlat and Bodin, 2006; de Andres-de Prado et al., 2007), and agricultural practices such as irrigation (Van Zyl, 1987; Greenspan et al., 1996; Ojeda et al., 2002; Olle et al., 2011), fertilization (Spayd et al., 1994; Keller et al., 1999; Delgado et al., 2004; Bell and Henschke, 2005), and method used to train the vine (Jackson and Lombard, 1993). Grapes of the same variety, grown in different regions, can thus yield different amounts of polyphenols 6  (tannins and anthocyanins) and produce very different wines. A study by Chira et al. (2011) found that skin tannin mean degree of polymerization (mDP), percentage of galloylation (%G) and percentage of prodelphinidins (%P) were all affected by the varietal. Tannin monomer and dimer concentrations; however, were not affected by grape variety.  Depending on varietal, the surface area of the skin at maturity can increase up to 640-fold from the size at fruit set (Considine and Knox, 1981). The skin makes up 5-10% of the total dry weight of the berry and can be divided into three layers consisting of two distinct cell types (Considine and Knox, 1979; Pinelo et al., 2006). The first cell type is a single layer of clear epidermal cells on the outside of the berry (Considine and Knox, 1979; Hardie et al., 1996). The second cell type forms the hypodermal layers beneath the epidermis and the cells are called collenchmatous cells (Considine and Knox, 1979; Hardie et al., 1996). This cell type acts as a hydrophobic barrier that protects the grapes (Considine and Knox, 1979). The three layers of the grape skin consist of the cuticle which is the outermost layer, the intermediate epidermis, and the hypodermis which is the innermost layer (Hardie et al., 1996; Pinelo et al., 2006).  The hypodermal layers of the skin accumulate phenolics and their properties affect extraction into wine (Hanlin et al., 2010). Unlike other polyphenols found in grape skins, tannins have the unique ability to form complexes with proteins and polysaccharides (Haslam, 1974; Carvalho et al., 2006; Sarneckis et al., 2006; Escot et al., 2008). The ability of tannins to bind to proteins and polysaccharides in the cell wall has been correlated with a reduction in their release into wine (Downey et al., 2003; Hazak et al., 2005; Fournand et al., 2006; Cerpa-Calderon and Kennedy, 2008; McRae and Kennedy, 2011). Binding of tannins to proteins and polysaccharides involves hydrogen bonding and hydrophobic interactions (Oh et al., 1980; Haslam, 1988; McManus et al., 1985; McRae et al., 2010). Tannins are able to bind these molecules at different 7  sites on proteins and polysaccharides because they are amphipathic molecules, comprised of hydrophobic aromatic rings and hydrophilic hydroxyl groups (Haslam, 1988). There are many different proteins and polysaccharides in the cell wall that contain aromatic oxygen and glycosidic oxygen atoms and hydroxyl groups that form hydrogen bonds and hydrophobic interactions with tannin (McManus et al., 1985; Le Bourvellec et al., 2004; Rib?reau-Gayon et al., 2006b; Bindon et al., 2010a).   As the grape berry ripens the cell wall loosens as a result of a decrease in the strength and elasticity of the grape skin after v?raison and an increase in its extensibility (Huang et al., 2005). The epidermis and hypodermis swell after v?raison and there is degradation of the middle lamella in the cell walls (Considine and Knox 1979; Hardie et al., 1996: Huang et al., 2005). Also as the grape berry ripens, grape skin tannins are more easily extracted because there is degradation of the cell wall caused from the hydrolysis of structural polysaccharides (Nunan et al., 2001; Canals et al., 2005; Huang et al., 2005). The apoplast also becomes acidified by expansins after v?raison which breaks calcium bridges of the pectin molecules leading to loss of not only pectin but also calcium from the skin cell wall (Cosgrove, 2000; Huang et al., 2005). On the other hand, proteins that are covalently bound to grape skin cell walls increase with ripening (Huang et al., 2005). Wall-bound peroxidise, which catalyses the phenolic cross-link between polysaccharides and proteins in the cell walls, increases after v?raison (Huang et al., 2005). Peroxidase is found ionically bound to all layers of the cell walls but is more concentrated on the outer cell layers where it is covalently bound (Calder?n et al., 1993; Huang et al., 2005).   Components that comprise the cell wall also change as the berry ripens where berry sizes and chemical composition of the skin is dependent upon cultivar (Kok and Celik, 2004). As ripening proceeds the quantity of cell wall material decreases (Ortega-Regules et al., 2008). This 8  is because as the grape ripens the cell volume increases which consequently leads to a decrease in cell wall thickness (Baravon et al., 2000; Ortega-Regules et al., 2008). The chemical composition of the cell wall also changes during ripening. Galactose levels decrease during ripening whereas glucose, arabinose, xylose, fucose, mannose, and rhamnose in the cell wall either increase, decrease, or stay the same depending upon variety (Baravon et al., 2000; Ortega-Regules et al., 2008; Vicens et al., 2009). There are many different components of the cell wall; however, in all varieties during ripening the quantity of cell wall material and galactose decreases (Barnavon et al., 2000; Ortega-Regules et al., 2008; Vicens et al., 2009).  Overview of Polyphenols in Wine    Wine is very complex consisting of many interacting molecules that contribute to its intricate nature. The largest component of wine is water which depending on the variety, can range from 75 to 90% (v/v). Varying amounts of phenolics, organic acids, mineral salts and pectins contribute to the 15% variation observed (Conde et al., 2007). Ethanol, produced through the alcoholic fermentation of yeast, is the second largest contributor to the composition of wine, ranging from 8 to 13% (v/v) (Ciani and Picciotti, 1995; Conde et al., 2007). This high concentration of alcohol and the natural acidity of wine during fermentation inhibit the growth of pathogenic and noxious microorganisms that spoil wine (Conde et al., 2007; Waite and Daeschel, 2007). The sugar content can vary tremendously, with dry wines having less than 2 g L-1 and sweet wines reaching as high as 200 g L-1 (Domin? et al., 2004 as cited in Conde et al., 2007). The sugar content, as well as various nutrients, provides the yeast in the wine with a medium for ideal growth, thus allowing fermentation to commence (Conde et al., 2007). Fermentation results in the production of ethanol, which allows for better extraction of phenolic compounds compared to an aqueous solution (Canals et al., 2005; Sacchi et al., 2005; Downey and Hanlin, 2010). 9  Phenolics, specifically anthocyanins and tannins, affect the taste, color, bouquet, and mouth-feel properties of wine (Soleas et al., 1997). Anthocyanins are only found in red grape varieties and contribute the color to red wine (Mazza et al., 1999; Winkel-Shirley, 2001; Fournand et al., 2006; Rib?reau-Gayon et al., 2006b; He et al., 2010). They are a group of phenolic compounds that are responsible for the purple, blue or red colors found in plants (Goto and Kondo, 1991). Anthocyanin pigments are found in the vacuoles of epidermal tissue of flowers and fruit, where pH influences the chemical form, and hence the color, of these compounds (Goto and Kondo, 1991; Manach et al., 2004). Tannins are the main phenolic component of red wine and consist of two different classes: condensed tannins and hydrolysable tannins. Hydrolysable tannins are extracted from oak barrels or added during winemaking, whereas condensed tannins are produced in the grape berry and thus are of importance for this study (Herderich and Smith, 2005). Tannins contribute to the astringency and bitterness experienced when drinking wine due to their ability to form complexes with proteins and polysaccharides (Haslam, 1974; Carvalho et al., 2006; Sarneckis et al., 2006; Conde et al., 2007; Escot et al., 2008; Chira et al., 2011). Bitterness and astringency are important sensory components in red wine. Bitterness is a taste mediated by sensory receptors (Chandrashekar et al., 2000; Vidal et al., 2004a). Astringency is a tactile sensation caused from the precipitation of salivary proteins leading to the loss of mouth lubrication (Green, 1993; Gawel, 1998; Vidal et al., 2004a). Astringency is one of the prime contributors to mouth-feel ?properties ?ascribed ?to ?wines ?and ?is ?commonly ?referred ?to ?as ??drying', ?'roughing' ?and ?'puckering? (Gawel, 1998; McRae et al., 2013). The variation in mouth-feel and aging properties is attributed to the variation in tannin content, composition, and polymer length, with monomers being more bitter than astringent and larger molecular weight derivatives being 10  more astringent than bitter (Peleg et al., 1999; Vidal et al., 2003; Hanlin and Downey, 2009; Chira et al., 2011; McRae et al., 2013).  1.2 Phenolics and Their Biosynthesis Phenolics Overview Phenolics are a widespread group of more than 8000 specialized metabolites (Pereira et al., 2009; Dai and Mumper, 2010; Cartea et al., 2011), all of which contain an aromatic hydrocarbon ring with one or more hydroxyl groups associated with the ring structure directly (Soleas et al., 1997; Adams, 2006; Ribereau-Gayon et al., 2006b; Bowsher at al., 2008; Dai and Mumper, 2010). They account for approximately 40 percent of the organic carbon circulating in the biosphere (Croteau et al., 2000). Of these 8000 phenolics, more than 4000 come from a group known as the flavonoids (Harborne and Williams, 2000; Cheynier, 2005).   Grape skin flavonoids consist of the tannins and the anthocyanins, which are secondary metabolites that aid in plant survival (Bennett and Wallsgrove, 1994). Flavonoids can be produced in response to a particular stress or during normal plant development (Treutter, 2006). For example, they are produced as a protective mechanism against predators (Bennett and Wallsgrove, 1994; Lev-Yadun et al., 2009; Barbehenn and Constabel, 2011), disease (Dai et al., 1995; Lima et al., 2012), and UV-B radiation (Solovenko and Schmitz-Eiberger, 2003; Berli et al., 2011). Plants also use anthocyanins to communicate with pollinators and seed dispersers by the use of color, thereby enhancing reproductive success of the plant (Weiss, 1995; Schaefer et al., 2004). This allows consumption of sphenolics to have either direct toxic effects or to provide barriers (Bennett and Wallsgrove, 1994). It has been shown in many cases that insects prefer cultivars low in phenolics (Larson and Berry, 1984; Leszczynski et al., 1989).  Studies have also shown that phenolics produced by the plant cause resistance to other herbivores including birds and slugs (Bullard et al., 1980; Johnston and Pearce, 1994).  11   Tannins and anthocyanins along with other phenolic molecules have also been shown to have antioxidant properties in plants providing them with protection. The hydroxyl groups on phenolic compounds easily donate hydrogen to reactive oxygen and reactive nitrogen species (Paya et al., 1992; Porter et al., 2001; Choi et al., 2002; Valentao et al., 2002). If this donation occurs in a termination reaction then it breaks the cycle that would regenerate new oxygen or new nitrogen radicals (Pereira et al., 2009). The interaction of the phenolic compound with a reactive species generates a new radical from the antioxidant; however, this new radical is much more stable than the original reactive species (Parr and Bolwell, 2000; Nijveldt et al., 2001; Pereira et al., 2009). The stable phenolic radical then can either diffuse away or can be reduced back to what it was originally (Parr and Bolwell, 2000). Phenolic compounds are also effective at stopping the production of free radicals by chelating metal (Moran et al., 1997; Mira et al., 2002). Phenolics with 2,3-double bonds and both the catechol group in the B-ring and the 3-hydroxyl group are most effective at reducing iron, while phenolics with more hydroxyl groups are most effective at reducing copper (Mira et al., 2002). Phenolic compounds can also inhibit enzymes that are involved in the generation of radicals (Pereira et al., 2009).  The benzenoid rings and hydrogen bonding potential of phenolic compounds, especially tannins, allow them to bind to proteins, such as lipoxygenase, and inactivate them (Adams, 2006; Pereira et al., 2009). Anthocyanins have also been shown to be directly involved in photoprotection either by shielding leaf tissue or by scavenging reactive oxygen species (Wang et al., 1997; Archetti et al., 2009; Zhang et al., 2012). They shield the leaf by absorbing light thereby reducing its penetration to the mesophyll and reducing the production of reactive oxygen species (Steyn et al., 2002; Manetas et al., 2003, Merzlyak et al., 2008). 12  Phenolic Structures and Properties  Grape skin phenolics can be broken down into two classes: the flavonoids and the non-flavonoids. Flavonoids consist of the tannins and anthocyanins and all share the same basic C6-C3-C6 structure containing two phenols (rings A and B) joined by a pyran ring (ring C) (Soleas et al., 1997). The non-flavonoids consist of the phenolic acids and the stilbenes. Phenolic acids have either a C6-C3 structure and are referred to as hydroxycinnamic acids or a C6-C1 structure and are referred to as the hydroxybenzoic acids (Rib?reau-Gayon et al., 2006b). This C6-C3 or C6-C1 linkage corresponds to the carboxyl linkage to the benzyl ring (Rib?reau-Gayon et al., 2006b). Stilbenes consist of two aromatic rings linked by a double bond and are found in oligomeric and polymeric forms (Monagas et al., 2005).  Phenolics originate from the biochemical pathway beginning with phenylalanine (Figure 1.3) (Parr and Bolwell, 2000; Adams, 2006; Cartea et al., 2011). Phenylalanine is produced from shikimic acid which is a product of the shikimic pathway that combines products from the pentose phosphate pathway and glycolysis (Parr and Bolwell, 2000; Conde et al., 2007). Phenylalanine is converted into cinnamic acid by the enzyme phenylalanine ammonia lyase (Blount et al., 2000; Conde et al., 2007). Phenylalanine ammonia lyase is the key enzyme in secondary metabolite production. It regulates the flux into the production of secondary metabolites, the phenylpropanoid pathway, and not primary metabolites (Howles et al., 1996). Cinnamic acid then transforms into coumaric acid by the enzyme cinnamate-4-hydroxylase, then coumaric acid is transformed into 4-courmaroyl-CoA by the enzyme 4-hydroxycinnamate: CoA ligase (Croteau et al., 2000; Achnine et al., 2004; Conde et al., 2007).  4-courmaroyl-CoA combines with three molecules of malonyl-CoA, produced from the acetate pathway from acetyl-CoA, starting the phenylpropanoid pathway (Adams, 2006; Conde et al., 2007). Coumaric acid can also be transformed, through a series of steps, into simple phenolics such as the phenolic 13  acids caftaric acid, coutaric acid, fertaric acid and quercetin (Conde et al., 2007). The phenylpropanoid pathway goes on to generate more complex phenolic compounds such as stilbenes, anthocyanins, monomeric flavanols, and polymeric flavanols, depending on which enzyme is utilized. For example at the start of the phenylpropanoid pathway, chalcone synthase leads to the production of the flavonoids, whereas stilbene synthase (SS) leads to the production of stilbenes, such as resveratrol (Conde et al., 2007).   14   Figure 1.3: Biosynthetic pathway of the major phenolic classes (Adams, 2006; Conde et al., 2007; He et al., 2010).  Tannins  Condensed tannins are polymeric flavan-3-ol molecules composed of flavanol monomer subunits and are found in the hypodermal layers in the skin (Adams, 2006; Rib?reau-Gayon et al., 2006b). All tannins share a basic structure (Figure 1.4) consisting of two benzene cycles 15  bonded by a saturated oxygenated heterocycle (Soleas et al., 1997; Adams, 2006; Rib?reau-Gayon et al., 2006; Dai and Mumper, 2010). The structure consists of the A-ring, a phloroglucinol derivative, which is linked to the C or pyran ring, which in turn is linked to the B or phenolic ring (Adams, 2006). The properties of the flavonoid monomers, their bonding, esterification to other compounds, and functional properties are the basis for tannin classification (Soleas et al., 1997).    Figure 1.4: Basic monomer tannin structure found in grape skins can be linked by a carbon-carbon inter-flavan bond (C4-C6 or C4-C8) to form polymers. R1 can be a hydrogen group or a gallate group and R2 can be hydrogen or a hydroxyl group.  The subunits (Figure 1.5) that make up tannins in grape skin are (-)-epicatechin, (-)-epigallocatechin, (+)-catechin, and (-)-epicatechin-3-O-gallate. These monomers can condense to form tannin polymers (proanthocyanins) with great complexity forming polymers with up to 80 subunits (Souquet et al., 1996; Adams, 2006). (-)-Epicatechin-3-O-gallate makes up a large portion of polymeric tannin subunits, this monomer consists of an epicatechin subunit condensed with a gallate group at the oxygen in position C3 of the pyran ring (Downey et al., 2003; Fournand et al., 2006). Tannin oligomers are mainly linked through C4-C8 (and sometimes C4-C6) known as B-type bonds (Fletcher et al., 1977; Foo and Porter, 1980; Adams, 2006; Hanlin et al., 2010). An additional bond can occur via an ether bond between C2-C5 or C2-C7, known as 16  A-type (Vidal et al., 2004b). It is currently unknown how this inter-flavan bond is formed between tannin monomers. It has been suggested however, that this polymerization occurs by the action of enzymatic or non-enzymatic oxidation in vacuoles through the use of vesicle or membrane transporters powered by tonoplast proton pumps (Abrahams et al., 2003; Baxter et al., 2005; Zhao et al., 2010).   Figure 1.5: Structure of the flavanol-3-ol monomeric molecules that are subunits that make up tannins in grape skins.  The production of monomeric tannins requires the action of several enzymes that join caffeoyl-CoA and malonyl-CoA from the shikimate pathway to produce tannins (Figure 1.6) (Adams, 2006). (+)-Catechin and (-)-epicatechin differ only by the stereochemistry of the hydroxyl group on C3 (pyran ring C) (Adams, 2006). The pyran ring is only found in R stereochemistry in wine and grapes and the two asymmetric centers C2 and C3 lead to four isomers (Adams, 2006). 2,3-trans-flavan-3-ol is produced from flavanonol by dihydroflavanol reductase, which can produce (+)-catechin directly by leucoanthocyanidin reducatase because it has the 2,3-trans configuration (Adams, 2006). (-)-Epicatechin has the 2,3-cis configuration and because of the stereochemistry cannot be directly converted from 2,3-trans-flavan-3-ol and has to be produced from cyanidin by anthocyanidin reductase (Xie et al., 2003; Adams, 2006). Anthocyanidin produces (-)-epigallocatechin from delphinidin (Xie et al., 2003).  17   Figure 1.6: Biosynthesis of (+)-catechin and (-)-epicatechin from caffeoyl CoA and malonyl-CoA adapted and re-drawn from Adams (2006). CHS, chalcone synthase; CHI, chalcone isomerase; F3H, flavanone-3-hydroxylase; DFR, dihydroflavonol-4-reductase; LAR, leucoanthocyanidin reductase; ANS, anthocyanidin synthase; ANR, anthocyanidin reductase; UFGT, UDP glucose-flavonoid 3-O-glucosyl transferase.    Anthocyanins Anthocyanins are also found in the hypodermal cells of the grape skin and are the second most abundant polyphenol (Adams, 2006). All anthocyanins share a basic structure, including two benzene rings bonded by an unsaturated cationic oxygenated heterocycle (Rib?reau-Gayon et al., 2006b). Like the tannins, anthocyanins consist of an A-ring, a C or pyran ring, and a B or phenolic ring (Adams, 2006).  The oxygen molecule in the pyran ring is where the basic anthocyanin structure differs from the basic tannin structure. Anthocyanins also have an unsaturated cationic oxygenated heterocycle, whereas tannins have a saturated oxygenated 18  heterocycle (Rib?reau-Gayon et al., 2006b). They differentiate by the way they are substituted at the R groups (Figure 1.7).   Figure 1.7: Basic structure of anthocyanidins, the precursors to anthocyanins. Anthocyanins have a glucose molecule bonded to the oxygen which is bonded to the carbon at position three (R1). In certain varieties, Cabernet franc and Merlot, but not Pinot noir, some esterification can occur on the OH function of the glucose with coumaric or acetic acid. R3 and R2 are substituted with either a hydrogen molecule (H), a hydroxyl molecule (OH), or a methoxy molecule (OCH3).  Anthocyanins found in grape skin are delphinidin, cyanidin, petunidin, peonidin, and malvidin. Anthocyanins are classified as either glycoside or acylglycosides where acylation is made with p-coumaric, caffeic and acetic acids (Mazza and Francis, 1995; Rib?reau-Gayon et al., 2006b; He et al., 2010). In some varieties, such as Pinot noir, acylation is not present; therefore, they produce five (Figure 1.8) of the twenty-five anthocyanins (Cheynier et al., 2006; Adams, 2006). Anthocyanins can also be classified as monoglucoside or diglucosides. In V. vinifera species, such as Pinot noir and Cabernet franc, only monoglucoside anthocyanins can be produced (Rib?reau-Gayon et al., 2006b). In this case, glucose molecules can only be linked to anthocyanidins at position C3 to form 3-O-monoglucoside anthocyanins because they lack the ability to produce diglucosides (Ford et al., 1998; Rib?reau-Gayon et al., 2006b; Janvary et al., 2009). In other Vitis species, glucose molecules can be linked at both the C3 and C5 to produce diglucosides (Rib?reau-Gayon et al., 2006b; Janvary et al., 2009). 19   Figure 1.8: Structure of the five anthocyanidins found in Pinot noir. Anthocyanidins are precursors to anthocyanins where anthocyanins have a glucose molecule bonded to the oxygen molecule at position 3.  Anthocyanins are synthesised in the flavonoid pathway (Figure 1.9) starting with the production of chalcone. Chalcone is produced through the condensation of three molecules of malonly-CoA and one molecule of p-coumaroyl-CoA by the action of chalcone synthase (Forkmann, 1991; Holton and Cornish, 1995; He et al., 2010). Chalcone is converted to naringenin by chalcone isomerase, ?and ?then ?naringenin ?is ?oxidized ?by ?flavanone ?3?-hydroxylase to form dihydrokaempferol (Sparvoli et al., 1994; He et al., 2010). Dihydrokaempferol acts as a substrate ?for ?flavonoid ?3?-hydroxylase and ?flavonoid ?3?,5?-hydroxylase, to produce the corresponding dihydroflavonols; dihydroquercetin, and dihydromyricetin, respectively (Sparvoli et al., 1994; He et al., 2010). These dihydroflavonols are sequentially reduced to their leucoanthocyanidins by dihydroflavonol 4-reductase (Boss et al., 1996; Bogs et al., 2006). Leucoanthocyanidins are then reduced to their corresponiding anthocyanidins by anthocyanidin 20  synthase, which can then be glycosylated to their corresponding anthocyanins by UDP glucose-flavonoid 3-O-glucosyl transferase (He et al., 2010).    21   Figure 1.9: Pathway showing anthocyanin biosynthesis (Matus et al., 2009; He et al., 2010). CHS, chalcone ?synthase;? ?CHI, ?chalcone ?isomerase;? ?F3H, ?flavanone ?3?-hydroxylase;? ?F3?H, ?flavonoid ?3?-hydroxylase; F3?5?H, ?flavonoid ?3?,5?-hydroxylase; DFR, dihydroflavonol 4-reductase; ANS, anthocyanidin synthase; UFGT, UDP glucose-flavonoid 3-O-glucosyl transferase.  22  The production of anthocyanins and condensed tannins (Figure 1.10) shares common steps. This involves the formation of flavan-3,4-diols which contributes to anthocyanin synthesis and to extension units of condensed tannins (Stafford as cited in Bogs et al. 2005). Leucocyanidin is reduced by leucoanthocyanidin reductase to catechin. Leucocyanidin can then be made into cyanidin by anthocyanin synthase. Anthocyanidin reductase can then reduce cyanidin to epicatechin, both of which can form the terminal subunit of the condensed tannin (Bogs et al., 2005). If UDP glucose-flavonoid 3-O-glucosyl transferase is used on cyanidin instead of anthocyanidin synthase, then the anthocyanin cyanidin-3-glucocide is produced (Bogs et al., 2005).   Figure 1.10: Biosynthetic flavonoid pathway leading to the production of proanthocyanidin polymer (condensed tannin) and anthocyanidin re-drawn and adapted from Bogs et al. (2005); ANS, anthocyanidin synthase; UFGT, UDP glucose-flavonoid 3-O-glucosyl transferase; LAR, leucoanthocyanidin reducatase; ANR, anthocyanidin reductase.  23  1.3 Phenolic Accumulation During Ripening Tannin Accumulation Tannin synthesis occurs early in berry development peaking around v?raison, which coincides with the production of anthocyanins. Anthocyanins are only found in red grape varieties and contribute the color to red wine (Mazza et al., 1999; Winkel-Shirley, 2001; Fournand et al., 2006; Rib?reau-Gayon et al., 2006b; He et al., 2010). The genes responsible for production of enzymes required for tannin production are down-regulated while the genes responsible for production of enzymes required for anthocyanin production are up-regulated (Sparvoli et al., 1994; Boss et al., 1996; Bogs et al., 2005; Bogs et al., 2007; Verries et al., 2008). Once this switch occurs it can be observed in the color change from green to red berries caused from the pigmented anthocyanins.   Total Tannins The variation in tannin content found in different grape samples can be the result of differences in variety, terroir (environment, climate, and soil), predatory stresses, or method used to extract tannins. Most authors agree that tannins decrease after v?raison (Harbertson et al., 2002; Kennedy et al., 2002; Canals et al., 2005; Hanlin and Downey, 2009); conversely, some found that tannins increase (Estaban et al., 2001), while many others found that they stayed the same (Table 1.1) (Ojeda et al., 2002; Canals et al., 2005, Hanlin and Downey, 2009, Olle et al., 2011). Harbertson (2002) sampled Cabernet Sauvignon and Syrah, and Kennedy (2002) sampled Cabernet Sauvignon, nevertheless they all extracted tannins, through various mechanisms, using 66 to 70% (v/v) acetone as the solvent and found that tannins decrease after v?raison.    Hanlin and Downey (2009) used frozen grape skin ground to a powder and found that Shiraz 2003-04 and 2004-05 samples were consistent with one another and that total tannin decreased pre-v?raison to v?raison then stayed the same from v?raison to harvest. The Cabernet 24  Sauvignon samples differed, however, as the total tannin amount in the 2003-04 samples decreased from pre-v?raison to v?raison to harvest while the 2004-05 samples stayed the same v?raison to harvest (Hanlin and Downey, 2009). Gagn? (2006) ground their grape skin samples to a fine powder under liquid nitrogen and homogenized in 20 mL of 0.2 M Tris-HCl buffer, pH 7.5, containing 2.5% of EDTA. They found that the internal cell fractions of the grape skins decreased for both the 2004 and 2005 seasons while the cell wall fractions for both seasons stayed the same (Gagn? et al., 2006). Ojeda (2002) and Olle (2011) sampled Shiraz and both extracted tannins with 70% acetone, although with different methods, and found that these tannins increased pre- to post-v?raison but stayed the same to harvest. Canals (2005) found that when they extracted Tempranillo grapes with 0 to 13% ethanol total tannins either decreased from v?raison to harvest of they stayed the same. While Esteban (2001) extracted Tempranillo grapes with 50% methanol and found that total tannins increased from v?raison to harvest.         25  Table 1.1: Total tannin v?raison to harvest. CE= catechin equivalents. Author Sample Total Tannin Amounts Total Tannin from V?raison to Harvest Esteban et al., 2001 Tempranillo V?raison: tannins 124.69 mg 100 berries-1           Harvest: tannins 273.33 mg 100 berries-1 Increased Harbertson et al., 2002 Cabernet Sauvignon V?raison: 0.7 mg berry-1 CE                                     harvest: 0.58 mg berry-1 CE Decreased  Syrah V?raison: 1.1 mg berry-1 CE                                      Harvest: 0.51 mg berry-1 CE Decreased Kennedy et al., 2002 Cabernet Sauvignon V?raison: tannin 930 extension units, nmole berry-1; Harvest: tannin 910 extension units, nmole berry-1 Decreased Ojeda et al., 2002 Shiraz Pre-v?raison: 2.5 mg CE fresh skin-1; Post-v?raison: 3.3 mg CE fresh skin-1; Harvest 3.45 mg CE fresh skin-1 Increased before v?raison stayed the same after Downey et al., 2003 Shiraz Pre-v?raison: 0.4 extension subunits mg berry-1; 0.02 terminal subunits mg berry-1. V?raison: 3.1 extension subunits mg berry-1; 0.06 terminal subunits mg berry-1. Harvest: 1.1 extension subunits mg berry-1; 0.05 terminal subunits mg berry-1 Increased before v?raison to v?raison then decreased after; overall increase Canals et al., 2005 Tempranillo (1st stage) Pre-v?raison:1.36 g L-1; V?raison: 1.54 g L-1; Post-v?raison: 1.26 g L-1 Increased before decreased after  Tempranillo (2nd stage) Pre-v?raison:1.59 g L-1; V?raison: 2.06 g L-1; Post-v?raison: 2.10 g L-1 Increased before v?raison stayed the same after  Tempranillo (3rd stage) Pre-v?raison:1.92 g L-1; V?raison: 2.70 g L-1; Post-v?raison: 2.55 g L-1 Increased before v?raison decreased after Gagn? et al., 2006 Cabernet Sauvignon (2004) V?raison: internal cell fraction 5.2 mg berry-1, cell wall fraction 2.5 mg berry-1; Harvest: internal cell wall fraction 3.4 mg berry-1, cell wall fraction 2.8 mg berry-1 Internal cell fraction decreased, cell wall fraction stayed the same  Cabernet V?raison: internal cell fraction 3.5 mg berry-1, Internal cell 26  Sauvignon (2005) cell wall fraction 0.5 mg berry-1; Harvest: internal cell wall fraction 1.2 mg berry-1, cell wall fraction 0.4 mg berry-1 fraction decreased, cell wall fraction stayed the same Hanlin and Downey 2009 Shiraz 2003-04 Pre-v?raison: 5.9 mg g berry-1; V?raison: 1 mg g berry-1; Harvest: 1 mg g berry-1 Decreased before v?raison stayed the same  Shiraz 2004-05 Pre-v?raison 3.5 mg g berry-1; V?raison: 1 mg g berry-1; Harvest: 0.9 mg g berry-1 Decreased before v?raison stayed the same  Cabernet Sauvignon 2003-04 Pre-v?raison: 7.3 mg g berry-1; V?raison: 2.5 mg g berry-1; Harvest: 1 mg g berry-1 Decreased  Cabernet Sauvignon 2004-05 Pre-v?raison: 5.2 mg g berry-1; V?raison: 1 mg g berry-1; Harvest: 1 mg g berry-1 Decreased before v?raison stayed the same Olle et al., 2011 Shiraz Pre-v?raison: tannins 1.605 mg berry-1; Post-v?raison: 3.423 mg berry-1; Harvest: tannin 3.285 mg berry-1 Increased before v?raison then stayed the same after  Grape Skin Tannin Mean Degree of Polymerization Grape skin tannins consists of long polymer chains with up to 50 mean degrees of polymerization (mDP) (Table 1.2) made mostly of (+)-catechin terminal subunits and (-)-epicatechin and (-)-epigallocatechin extension subunits (Downey et al., 2003; Bordiga et al., 2011). The majority of flavanols are synthesized pre-v?raison but mDP tends to increase from v?raison till harvest (Kennedy et al., 2001; Gagn? et al., 2006; Bordiga et al., 2011). Some authors have found that grape skin tannins mDP either decrease from v?raison to harvest (Downey et al., 2003; Hanlin and Downey, 2009) or stay the same (Gagn? et al., 2006; Bindon and Kennedy, 2011; Olle et al., 2011).  27  Kennedy and colleagues (2001) using Shiraz berries found that there was a continual increase in polymer length of their tannins from green berries to v?raison to red berries. Bordiga (2011) using Cabernet Sauvignon and Nebbiolo grapes also found that the polymer lengths of their tannins increased from v?raison to harvest. Downey (2003) found that there was an initial increase in length of skin polymers from 25 to 40 subunits in the early stages of berry development starting at fruit-set which stayed constant at 30 to 40 subunits until v?raison. Four weeks post-v?raison there was a decrease in mDP from 25 to 30 subunits which again decreased to 20 subunits at time of harvest (Downey et al., 2003). Hanlin and Downey (2009) also found that their Cabernet Sauvignon 2003-04 and Shiraz 2004-05 samples mDP decreased from v?raison to harvest but their Cabernet Sauvignon 2004-05 and Shiraz 2003-04 samples mDP stayed the same. Gagn? (2006) using two vintages of Cabernet Sauvignon (2004 and 2005) found that there was a slight to no change in polymer length in the tannins found in the internal cell fraction while there was an increase in the tannins found in the cell wall fraction. Bindon and Kennedy (2011) using samples of Cabernet Sauvignon and Olle (2011) using samples of Shiraz both found that the polymer length of their tannins stayed the same from v?raison to harvest          28  Table 1.2: mDP v?raison to harvest. Author Sample mDP mDP v?raison to harvest  Method Kennedy et al., 2001 Shiraz Green berries 7.3, V?raison green 10.6, V?raison red 11.3, Harvest 27.0 Increased Phloroglucinolysis Downey et al., 2003 Shiraz Pre-v?raison 25-40, V?raison 30-40, Harvest 20 Decreased Phloroglucinolysis Gagn? et al., 2006 Cabernet Sauvignon (2004) V?raison: internal cell fraction 2.8, cell wall fraction 3.2. Harvest: internal cell fraction 2.4, cell wall fraction 8. No change in the internal cell wall fraction with an increase in cell wall fraction. Thioacidolysis  Cabernet Sauvignon (2005) V?raison: internal cell fraction 1.8, cell wall fraction 3.8. Harvest: internal cell fraction 1, cell wall fraction 6.5. Slight increase in the internal cell wall fraction with an increase in cell wall fraction. Thioacidolysis Hanlin and Downey 2009 Cabernet Sauvignon 2003-04 Pre-v?raison 30, V?raison 32, Harvest 27 Decreased Phloroglucinolysis  Cabernet Sauvignon 2004-05 Pre-v?raison 32, V?raison 29, Harvest 31 Stayed the same Phloroglucinolysis  Shiraz 2003-04 Pre-v?raison 28, V?raison 29, Harvest 31 Increased Phloroglucinolysis  Shiraz 2004-05 Pre-v?raison 29, V?raison 30, Harvest 26 Decreased Phloroglucinolysis Bindon and Kennedy 2011 Cabernet Sauvignon Pre-v?raison 17.3, Post-v?raison 27.2, Harvest 26.9 Stayed the same Phloroglucinolysis Bordiga et al., 2011 Cabernet Sauvignon Pre-v?raison 21, V?raison 27.3, Harvest 36.6 Increased Phloroglucinolysis  Nebbiolo Pre-v?raison 21.5, V?raison 46.1, Harvest 50.2 Increased Phloroglucinolysis Olle et al., 2011 Shiraz Pre-v?raison 30.6, Post-v?raison 32.6, Harvest 24.6 Stayed the same Phloroglucinolysis  Subunit Composition Grape skin tannins subunit composition (Table 1.3) varies considerably between varieties, vintages, and methods used during extraction and analysis (Gagn? et al., 2006; Downey 29  and Hanlin, 2010; Olle et al., 2011). However, there is usually very little change from v?raison to harvest within each variety on a given field (Downey et al., 2003; Bordiga et al., 2011; Olle et al., 2011). Depending upon variety (+)-catechin can be the main subunit; however, (-)-epigallocatechin can also dominate (Gagn? et al., 2006; Hanlin and Downey, 2009; Mattivi et al., 2009; Olle et al., 2011). (+)-Catechin accounts for approximately 6 to 77% of the subunits at v?raison and 5 to 54% of the subunits at harvest when examining Cabernet Sauvignon and Shiraz from different sites (Gagn? et al., 2006; Hanlin and Downey, 2009; Olle et al., 2011). (-)Epicatechin accounts for approximately 5 to 65% at v?raison and 8 to 68% at harvest, (-)-epicatechin-3-O-gallate accounts for approximately 3 to 7% at v?raison and 5 to 8% at harvest, and (-)-epigallocatechin accounts for approximately 15 to 40% at v?raison and 22 to 54% at harvest (Gagn? et al., 2006; Hanlin and Downey, 2009; Olle et al., 2011). The monomers of these compounds do not affect the overall tannin content because they are found in extremely small amounts (Downey et al., 2003; Fournand et al., 2006). In skin the most common terminal subunit is (+)-catechin with (-)-epicatechin and (-)-epicatechin-3-O-gallate present in much lower quantities (Souquet et al., 1996; Kennedy et al., 2001; Downey et al., 2003; Hanlin and Downey, 2009). (+)-Catechin accounts for approximately 33 to 95% of the terminal subunits in a sample at v?raison and 44 to 82% at harvest, when examining Cabernet Sauvignon and Shiraz from different sites (Downey et al., 2003; Verries et al., 2008; Bordiga et al., 2011).  (-)-Epicatechin makes up approximately 5 to 42% at v?raison and 18 to 44% at harvest, while (-)-epicatechin-3-O-gallate makes up approximately 7 to 33% at v?raison and 6 to 13% of the terminal subunits at harvest (Downey et al., 2003; Verries et al., 2008; Bordiga et al., 2011). (-)-Epicatechin and (-)-epigallocatechin are the most common extension subunit followed by (-)-epicatechin-3-O-gallate and (+)-catechin at much lower 30  quantities (Souquet et al., 1996; Downey et al., 2003; Hanlin and Downey, 2009). (-)-Epicatechin comprises approximately 36 to 59% of the extension subunits in a sample at v?raison and 42 to 59% at harvest (Downey et al., 2003; Verries et al., 2008; Bordiga et al., 2011). (-)-Epigallocatechin represents approximately 44 to 59% of the extension subunits in a sample at v?raison and 29 to 58% at harvest (Downey et al., 2003; Verries et al., 2008; Bordiga et al., 2011). (+)-Catechin composes approximately 1 to 3% at v?raison and 1 to 7% at harvest and (-)-epicatechin-3-O-gallate composes approximately 2 to 6% at v?raison and 1 to 7% of the extension subunits at harvest (Downey et al., 2003; Verries et al., 2008; Bordiga et al., 2011). Table 1.3: Subunit composition in grapes skins as ripening proceeds.  Author  Sample Subunit Composition Percent Composition in a Sample Change in Composition to Harvest Downey et al., 2003 Shiraz Extension Subunits Catechin: v?raison 0.1 mg berry-1, harvest 0.1 mg berry-1 3.1% v?raison, 7.1% harvest 4% increase   Epicatechin: v?raison 1.5 mg berry-1, harvest 0.8 mg berry-1 46.9% v?raison, 57.1% harvest 10.2% increase   Epicatechin-gallate: v?raison 0.2 mg berry-1, harvest 0.1 mg berry-1 6.3% v?raison, 7.1% harvest 0.8% increase   Epigallocatechin: v?raison 1.4 mg berry-1; harvest 0.4 mg berry-1 43.8% v?raison, 28.6% harvest 15.2% decrease  Shiraz Terminal Subunits Catechin: v?raison 0.01 mg flavanols berry-1, harvest 0.02 mg flavanols berry-1 33.33% v?raison, 50% harvest 16.67% increase   Epicatechin: v?raison 0.01 mg berry-1, harvest 0.015 mg berry-1 33.33% v?raison, 37.5% harvest 4.17% increase   Epicatechin-gallate: v?raison 0.01 mg berry-1, harvest 0.005 mg berry-1 33.33% v?raison, 12.5% harvest 20.83% decrease  Shiraz Monomers Catechin: v?raison 0.025 mg berry-1, harvest 0.009mg/berry 64.1% v?raison, 39.1% harvest 25% decrease   Epicatechin: v?raison 0.004 mg berry-1, harvest 0.012 mg berry-1 10.3% v?raison, 52.3% harvest 42% increase   Epicatechin-gallate: v?raison 0.01 mg berry-1, harvest 0.002 mg berry-1 25.6% v?raison, 8.7% harvest 16.9% decrease Gagn? et Cabernet Catechin: v?raison 0.01 mg flavanols 10% v?raison, 3.2% 31  al., 2006 Sauvignon (2004) berry-1, harvest 0.02 mg flavanols berry-1 6.8% harvest decrease   Epicatechin: v?raison 0.04 mg flavanols berry-1, harvest 0.17 mg flavanols berry-1 40% v?raison, 57.6% harvest 17.6% increase   Epicatechin-gallate: v?raison 0.01 mg flavanols berry-1, harvest 0.015 mg flavanols berry-1 10% v?raison, 5.1% harvest 4.9% decrease   Epigallocatechin: v?raison 0.04 mg flavanols berry-1, harvest 0.09 mg flavanols berry-1  40% v?raison, 30.5% harvest 9.5% decrease  Cabernet Sauvignon (2005) Catechin: v?raison 0.15 mg flavanols berry-1, harvest 0.07 mg flavanols berry-1 76.9% v?raison, 53.8% harvest 23.1% decrease   Epicatechin: v?raison 0.01 mg g berry-1, harvest 0.01 mg g berry-1 5.1% v?raison, 7.7% harvest 2.6% increase   Epicatechin-gallate: v?raison 0.005 mg flavanols berry-1, harvest 0.01 mg flavanols berry-1 2.6% v?raison, 7.7% harvest 5.1% increase   Epigallocatechin: 0.03 mg flavanols berry-1, harvest 0.04 mg flavanols berry-1 15.4% v?raison, 30.8% harvest 15.4% increase Verries et al., 2008 Shiraz Extension Subunits Catechin: v?raison 1.3 mole%, harvest 2.2 mole% 1.4% v?raison, 2.3% harvest 0.9% increase   Epicatechin: v?raison 56.2 mole%, harvest 57.2 mole% 58.5% v?raison, 59.2% harvest 0.7% increase   Epicatechin-gallate: v?raison 5.1 mole%, harvest 3.6 mole% 5.3% v?raison, 3.7% harvest 1.6% decrease   Epigallocatechin: v?raison 33.5 mole%; harvest 33.6 mole% 3.5% v?raison, 34.8% harvest 31.5% increase  Shiraz Terminal Subunits Catechin: v?raison 3.7 mole%, harvest 2.8 mole% 94.9% v?raison, 82.4% harvest 12.5% decrease   Epicatechin: v?raison 0.2 mole%, harvest 0.6 mole% 5.1% v?raison, 17.6% harvest 12.5% increase Hanlin and Downey 2009 Cabernet Sauvignon 2003-04 Catechin: v?raison 0.05 mg g berry-1, harvest 0.02 mg g berry-1 71.4% v?raison, 66.7% harvest 4.7% decrease   Epicatechin: v?raison 0.02 mg g berry-1, harvest 0.01 mg g berry-1 28.6% v?raison, 33.3% harvest 4.7% increase  Cabernet Sauvignon 2004-05 Catechin: v?raison 0.025 mg g berry-1, harvest 0.02 mg g berry-1;  62.5% v?raison, 66.7% harvest 4.2% increase   Epicatechin: v?raison 0.015 mg g 37.5% v?raison, 4.2% 32  berry-1, harvest 0.01 mg g berry-1 33.3% harvest decrease  Shiraz 2003-04 Catechin: v?raison 0.03 mg g berry-1, harvest 0.02 mg g berry-1 75% v?raison, 66.7% harvest 8.3% decrease   Epicatechin: v?raison 0.01 mg g berry-1, harvest 0.01 mg g berry-1 25% v?raison, 33.3% harvest 8.3% increase  Shiraz 2004-05 Catechin 0.03 mg g berry-1, harvest 0.02 mg g berry-1 75% v?raison, 66.7% harvest 8.3% decrease   Epicatechin: v?raison 0.01 mg g berry-1, harvest 0.01 mg g berry-1 25% v?raison, 33.3% harvest 8.3% increase Bordiga et al., 2011 Cabernet Sauvignon Terminal Subunits Catechin: v?raison 52 mole%, harvest 53 mole% 52% v?raison, 53% harvest 1% increase   Epicatechin: v?raison 40.6 mole%, harvest 41.4 mole% 40.6% v?raison, 41.4% harvest 0.8% increase   Epicatechin-gallate: 7.4 mole%, harvest 5.5 mole% 7.4% v?raison, 5.5% harvest 1.9% decrease  Cabernet Sauvignon Extension Subunits Catechin: v?raison 3.4 mole%, harvest 1.7 mole% 3.4% v?raison, 1.7% harvest 1.7% decrease   Epicatechin: v?raison 43.5 mole%, harvest 41.8 mole% 43.5% v?raison, 41.8% harvest 1.7% decrease   Epicatechin-gallate: v?raison 3 mole%, harvest 1.1 mole% 3% v?raison, 1.1% harvest 1.9% decrease   Epigallocatechin: v?raison 50.1 mole%, harvest 55.4 mole%  50.1% v?raison, 55.4% harvest 5.3% increase  Nebbiolo Terminal Subunits Catechin: v?raison 48.8 mole%, harvest 50.2 mole% 48.8% v?raison, 50.2% harvest 1.4% increase   Epicatechin: v?raison 42.1 mole%, harvest 44 mole% 42.1% v?raison, 44% harvest 1.9% increase   Epicatechin-gallate: v?raison 9.1 mole%, harvest 5.8 mole% 9.1% v?raison, 5.8% harvest 3.3% decrease  Nebbiolo Extension Subunits Catechin: v?raison 2.8 mole%, harvest 1.2 mole% 2.8% v?raison, 1.2% harvest 1.6% decrease   Epicatechin: v?raison 36.4 mole%, harvest 39.4 mole% 36.4% v?raison, 39.4% harvest 3% increase   Epicatechin-gallate: v?raison 1.8 mole%, harvest 1.3 mole% 1.8% v?raison, 1.3% harvest 0.5% decrease   Epigallocatechin: v?raison 59 mole%, harvest 58 mole% 59% v?raison, 58% harvest 1% decrease Olle et al., 2011 Shiraz Catechin: v?raison 0.302 mg berry-1, harvest 0.161 mg berry-1 5.8% v?raison, 4.9% harvest 0.9% decrease 33    Epicatechin: v?raison 3.408 mg berry-1, harvest 2.217 mg berry-1 65.1% v?raison, 67.5% harvest 2.4% increase   Epicatechin-gallate: v?raison 0.354 mg berry-1, harvest 0.177 mg berry-1 6.8% v?raison, 5.4% harvest 1.4% decrease   Epigallocatechin: v?raison 1.172 mg berry-1, harvest 0.731 mg berry-1 22.4% v?raison, 22.2% harvest 0.2% decrease  Anthocyanin Accumulation Anthocyanins accumulate in grape skin starting at v?raison, which coincides with color change. Total anthocyanins can range from 18 to 163 mg 100 berry skins-1 and their content increases from v?raison until harvest and have a positive correlation to sugar content (Pirie and Mullins, 1977; Revilla et al., 2010). The maximum anthocyanin concentration typically occurs 20-25 days after v?raison correlating to a sugar content of 19-21% (Roggero et al., 1986; Mazza et al., 1999). The most abundant anthocyanin in red grapes is malvidin-3-O-glucoside, representing 75% of the total anthocyanins present (Keller et al., 1999).  Anthocyanin accumulation is closely associated with sugar accumulation in berries with anthocyanin concentration reaching a maximum at 20-25 ?Brix (Boss et al., 1996; Yokotsuka et al., 1999). The accumulation of sugar in the berries causes high osmotic potentials in skin cells, which induce anthocyanin synthesis (Do and Cormier, 1991). Methoxylated anthocyanins continue to increase as sugar is accumulated in the skin while coumarylated anthocyanins initially increase up until 170 g L-1 then they rapidly decrease (Do and Cormier, 1991; Fournand et al., 2006). During accumulation of pulp sugar, skin anthocyanins composition changes significantly with the amounts of delphinidin, cyanidin, and petunidin derivatives reached a maximum before those of peonidin and malvidin derivatives (Fournand et al., 2006). After maximums are reached delphinidin, petunidin and malvidin derivatives and cyanidin and peonidin derived anthocyanins remain relatively constant during ripening (Boss et al., 1996).  34  Some of the genes involved in the biosynthesis of anthocyanins in grape berries including ANR, LAR, PAL CHS, CHI, F3H, DFR and LDOX were found to be expressed during the first 2-4 weeks post-flowering with no UFGT expression (Sparvoli et al., 1994; Boss et al., 1996; Bogs et al., 2005). Expression then decreased during the lag phase (6 to 8 weeks post-flowering) but increased during v?raison (10 weeks post-flowering) where the gene for UFGT was also turned on (Sparvoli et al., 1994; Boss et al., 1996; Bogs et al., 2005). Condensed tannin accumulation in grape skin is complete at v?raison when levels of ANR, LAR and LDOX decline and anthocyanin accumulation commences at the same time when levels of UFGT levels rise (Bogs et al., 2005; Verries et al., 2008; Gagn? et al., 2009). There is a competition between ANR and UFGT for cyanidin which before v?raison causes a diversion away from the production of anthocyanins to the production of epicatechin (Bogs et al., 2005).  The onset of anthocyanin accumulation in the skin at v?raison suggests that regulatory genes must also be in place that influences the expression of anthocyanin biosynthetic genes (Boss et al., 1996). Transcription factor VvMYBPA1 controls the pathway that expresses LAR and ANR both of which produce condensed tannins (Bogs et al., 2007; Deluc et al., 2008; Gagn? et al., 2009; Lacampagne et al., 2010). It activates the promoters for LAR and ANR along with many others involved in the flavonoid pathway but does not activate the promoter that inscribes UFGT (Bogs et al., 2007; Gagn? et al., 2009). This suggests that condensed tannins in grapes are regulated by VvMYBPA1 where its expression is decreased two weeks post-v?raison when anthocyanins accumulate (Bogs et al., 2007; Gagn? et al., 2009).  1.4 Extractability of Tannins from Grape Skin  Unlike other ployphenols found in grape skins, tannins have the ability to form complexes with proteins and polysaccharides (Haslam, 1974; Carvalho et al., 2006; Sarneckis et 35  al., 2006; Escot et al., 2008). Due to this ability tannins contribute to the astringency and bitterness experienced when drinking wine (Gawel, 1998; Carvalho et al., 2006; Escot et al., 2008; Chira et al., 2011). The binding of tannins to proteins and polysaccharides involves hydrogen bonding and hydrophobic interactions (Oh et al., 1980; Haslam, 1998; McManus et al., 1985; McRae et al., 2010). They are able to bind these molecules at different sites on each molecule because they are amphipathic molecules, comprised of hydrophobic aromatic rings and hydrophilic hydroxyl groups (Haslam, 1998).   The ability of tannins to bind to proteins and polysaccharides has been correlated to preventing their release into wine (Downey et al., 2003; Hazak et al., 2005; Fournand et al., 2006; Cerpa-Calderon and Kennedy, 2008; McRae and Kennedy, 2011). The level of tannins in the berry measured at harvest does not represent the level of tannins found in wine (Harbertson et al., 2002; Hazak et al., 2005). The incomplete extraction of tannins out of the berry is attributed to tannins binding to other components found in the cell wall (Downey et al., 2003; Hazak et al., 2005; Fournand et al., 2006; Cerpa-Calderon and Kennedy, 2008; Hanlin et al., 2010). There are many different proteins and polysaccharides in the cell wall that contain aromatic oxygen, glycosidic oxygen, and hydroxyl groups that form hydrogen bonds and hydrophobic interactions with tannins (McManus et al., 1985; Le Bourvellec et al., 2004; Rib?reau-Gayon et al., 2006b; Bindon et al., 2010a). The binding of tannins to cell wall material influences its extractability thus affecting its concentration in wine.  Solvent Effects   To improve the extractability of grape skin tannins, cell wall material must be degraded during extraction to disrupt the interactions between the cell wall and tannins allowing for their release into solvent. The type of solvent used in extraction greatly influences the type and composition of tannins extracted (Lapornik et al., 2005; Pinelo et al., 2005; Fournand et al., 36  2006; Bindon et al., 2010b). The type of solvent affects where tannins of varying molecular weight and varying degrees of polymerization will be extracted from (Fournand et al., 2006; Bindon et al., 2010b). As the molecular weight of polymeric tannins increase so does their affinity for cell walls (Bindon et al., 2010b). If a solvent is not strong enough or if the extraction does not proceed long enough, only small molecular weight tannins will be extracted and the higher molecular weight tannins will be trapped within the cell wall (Downey and Hanlin, 2010).   The most common types of solvents used in phenolic extractions are acetone, ethanol, methanol, and ethyl acetate, all with varying water content. Acetone is commonly used when extracting phenolics from the skins of grapes. A study by Downey and Hanlin (2010) compared different concentrations of acetone and ethanol used in extracting Shiraz grape skin tannins. Aqueous acetone of 50 to 70% extracted the highest amount of tannins when compared to other concentrations of acetone and varying concentrations of ethanol. A 50% ethanol solution extracts the highest amount of tannins when compared to other concentrations of ethanol (Downey and Hanlin, 2010). A 50% ethanol solvent yields similar tannin subunit composition as 70% acetone but does not produce similar results for tannin concentration or polymer length (Downey and Hanlin, 2010). A similar study by Canals and colleagues (2005) found even though an ethanol solvent is not the most effective at extracting phenolic compounds it can be used when comparing to wine. When tasting is required in a laboratory setting, an ethanol solvent can be used since it is safe for human consumption.  Extractable and Non-Extractable Grape Skin Tannins  During the process of red wine making, tannins are extracted from the grape skin. The rate of tannin extraction is not only dependent upon the tannin content in the grape but also on the wine making process (Sun et al., 1999). Despite the best efforts of wine makers, grape skin tannins are only partially extracted. Grape skin cell wall material acts as a barrier that inhibits the 37  movement of tannins into solution, whether it is into wine during wine making or solvent during lab practices (Barnavon et al., 2000; Ortega-Regules et al., 2008; Bindon et al., 2010a).   Studies show that a large factor that influences extractability is the mean degree of polymerization (mDP) (Fournand et al., 2006; Bindon et al., 2010a; Hanlin et al., 2010). As the polymerization of tannins increase, the number of reactive sites for binding to the cell wall also increases (Hanlin et al., 2010). After a 5 hour extraction of 90 fresh V. vinifera var. Shiraz berry skins in 150 mL of a hydroalcoholic solution containing 12% ethanol (v/v), 2 g L-1 potassium hydrogen tartrate, and 100 mg L-1 SO2, Fournand and colleagues (2006) recovered only 3% of the tannins present in the sample. They found that the main variable in this procedure was mDP (Fournand et al., 2006). Tannins that had been extracted into the hydroalcoholic solution had a smaller mDP than those that were not extracted (Fournand et al., 2006). Galloylation rate was found to be slightly higher in the non-extracted compounds whereas B-ring trihydroxylation rate was not affected (Fournand et al., 2006).  Extractability of Grape Skin Tannins with Ripening  As the grape berry ripens, the cell wall loosens as a result of a decrease in the strength and elasticity of the grape skin after v?raison and an increase in its extensibility (Huang et al., 2005). The epidermis and subepidermis swell after v?raison and there is degradation of the middle lamella in inner cell walls (Considine and Knox, 1979; Hardie et al., 1996; Huang et al., 2005). Also as the grape berry ripens, grape skin tannins are more easily extracted because there is degradation of the cell wall caused from the hydrolysis of structural polysaccharides (Nunan et al., 2001; Canals et al., 2005; Huang et al., 2005). One type of structural polysaccharide is pectin which is an acidic polysaccharide rich in galacturonans (Fry, 2004). Pectin is part of the wall matrix, linked divalently to each other by calcium bridges and linked to skeletal cellulose microfibrils (Fry, 2004). Pectin content in the skin cell wall decreases with ripening as pectinase 38  hydrolyzes pectins and as calcium bridges between pectin break, due to acidification of the apoplast from expansins (Huber, 1983; Cosgrove, 2000; Nunan et al., 2001; Huang et al., 2005). On the other hand, proteins that are covalently bound to grape skin cell walls increase with ripening (Huang et al., 2005). Wall bound peroxidise, which catalyses the phenolic cross-link between polysaccharides and proteins in the cell walls, increases after v?raison (Huang et al., 2005). Peroxidase is found ionically bound to all layers of the cell walls but is more concentrated on the outer cell layers where it is covalently bound (Calder?n et al., 1993; Huang et al., 2005).    1.5 Thesis Aims and Hypotheses  The first aim of this study was to follow the changes in phenolic content in grape skin throughout time, from pre-v?raison to harvest thus producing a phenolic profile (Chapter 2). The berries were harvested from two different varieties across three different vineyards: Cabernet Franc grapes from two vineyards and Pinot Noir grapes from one vineyard. Based on the literature we hypothesized that: 1. The total amount of tannins would change over 20% from pre-v?raison to harvest. 2. The subunit composition and mDP difference would not differ significantly from pre-v?raison to harvest and would fall below a 20% coefficient variation.  The second aim of this study was to examine the tannin reactivity with proteins over time (Chapter 3). The methyl cellulose precipitation assay was used for the quantification of tannins ability to bind to proteins by measuring total tannins. Based on the literature we hypothesized that: 39  3. Total grape skin tannins, as measured by the methyl cellulose assay, would decrease over time, from pre-v?raison to harvest.  4. The total amount of tannins measured with the methyl cellulose assay would not correlate to the total amount of tannins or mDP measured by UHPLC from pre-v?raison to harvest. The third aim was to develop a new gelatin adsorption assay method that quantifies wine and grape extract tannins (Chapter 4). We hypothesized that: 5. The results of the new Gelatin Adsorption Assay will be directly correlated to results of the methyl cellulose assay.              40  Chapter 2: Research Chapter 1: Polyphenol from Pre-V?raison to Harvest  2.1 Synopsis  Harvest is a critical time for viticulturists, since grape maturity signifies when the berries are ready to be picked.  Determining the best harvest time is extremely difficult because of the number of factors influencing berry maturity such as ?Brix, total acidity, pH, color, and polyphenol content. Many different ways to determine grape ripeness, and therefore subsequent wine quality, have been established (Francis et al., 2005; Sarneckis et al., 2006). One such method includes in-field analysis to determine grape ripeness and provide useful markers to determine the state of the grapes.  Phenolic ripeness is generally the most useful marker to determine when grapes are ready for harvest and is usually done on-site by tasting the grapes. This method of analysis is extremely inaccurate and subjective since it is based on the wine-maker?s ?palate. ?There ?is ?currently ?no ?easy ?analytical ?method ?to ?determine ?phenolic ?ripeness ?in ?the field. In order to develop such a method, researchers need to determine how phenolics change and accumulate in the berry or grape skin over time. This has been done for many regions and many varieties (Pirie and Mullins, 1977; Kennedy et al., 2001; Harbertson et al., 2002; Downey et al., 2003; Conde et al., 2007; Hanlin and Downey, 2009; Olle et al., 2011) although, to our knowledge, no such study has been performed in the Okanagan Valley. A phenolic profile of grapes in each region of the Okanagan Valley for each variety grown in that region would provide insight into how grape vines respond to their specific climate. This profile can then be managed by viticulturists to produce wines of higher quality and be utilized by researchers to develop an on-site method to determine phenolic ripeness. In our project, we analyzed skin tannins over time and produced a phenolic profile using phloroglucinolysis via UHPLC-MS. Phloroglucinolysis provided information on subunit composition, conversion yield, and mean degree of polymerization of the polyphenols. We could 41  distinguish monomers that were extension units from terminal subunits, because the phloroglucinol attached to the extension unit, whereas the terminal subunits remained free. This method allowed for the identification, quantification, and purification of phenolics from samples of grape skin extract.   2.2 Materials and Methods Sampling, Data Collection and Isolation of Grape Skin   At three different sites, 10 clusters of Vitis vinifera L. berries were picked from both sides of the vine from two adjacent designated rows (5 clusters per row) containing 25 vines each. Pinot Noir (PN) grapes were picked in Oliver and Cabernet Franc (CF) grapes were picked in Naramata and Osoyoos. The PN grapes, clone 115 with no rootstock, were sampled from a plot containing 1089 vines per acre that were irrigated using sprinkler irrigation. The CF grapes, clone 214 on 101-14 rootstock, were sampled from two separate plots (Naramata and Osoyoos) containing 2070 vines per acre that were irrigated using drip irrigation. Representative clusters were picked fourteen days apart starting pre-v?raison, August 8th, until harvest which was October 27th for PN and November 7th for CF in 2011.  To limit oxidation, berries were picked, pruned, weighed, and stored at -20?C until separation took place. Fifty representative grapes were selected by sampling grapes of all sizes, for each site in each sampling for processing; this was done in triplicate to determine reproducibility for both solvents used (50 berries x 3 = 150 berries per solvent). From here on every process was done with this triplicate. The skins from the berries were then manually separated using a scalpel and while being processed the skin was kept at -20?C and only removed from the freezer for short periods of time to limit thawing. To limit oxidation, the separated skins were kept on ice until they were weighed and stored for future extraction. 42  Chemicals Deionized water was purified using a MilliQ water system (Millipore, Bedford, MA). Ethanol HPLC grade was purchased from Commercial Alcohols (Brampton, ON, CA). Phloroglucinol, L-ascorbic acid, hydrochloric acid, sodium acetate, formic acid, (+)-catechin, (-)-epicatechin, (-)-epicatechin-3-O-gallate, and (-)-epigallocatechin were purchased from Sigma Aldrich (St Louis, MO, USA). Acetone, methanol, and acetonitrile all HPLC grade were purchased from Fisher Scientific (Waltham, MA, USA). Extraction  In the next stage of sample preparation, extraction kinetics were performed on two solvents to determine the optimal times required for tannin extraction based on absorbance; 70% acetone in water was used as one solvent and 12% ethanol in water was used as the other solvent. The latter solvent had a similar ethanol content to wine. Both acetone (Figure 2.1) and ethanol (Figure 2.2) gave similar results, thus an extraction time of 16 hours was used. The skin from 50 berries from each site, solvent, and sampling date in triplicate were placed into 125 mL Erlenmeyer flasks. Twenty mL of 70% acetone or 12% ethanol per g of skin extract was poured into the flasks and had nitrogen blown in for 3 minutes to remove oxygen. Then magnetic stir bars were placed into the flasks and they were placed onto magnetic stir plates and left for 16 hours. The flasks were then removed from the stir plates and the contents were suction filtered into 500 mL round bottom flasks and roto-evaporated (Hei-VAP Advantage) to dryness at 35?C. Next, the extracts were re-suspended in approximately 25 to 45 mL of de-ionized water, transferred to 50 mL disposable centrifuge tubes, and frozen at -80?C. The extracts were freeze dried using a LABCONCO freeze dry system/ freezone 4.5 then weighed to obtain yield.  43   Figure 2.1: Extraction kinetics of Pinot noir grape skin when using 20 mL of 70% acetone per g of grape skin as the solvent. Showing standard deviation error bars; N=9   Figure 2.2: Extraction kinetics of Pinot noir grape skin when using 20 mL of 12% ethanol per g of grape skin as the solvent. Showing standard deviation error bars; N=3.  Phloroglucinolysis In the initial stage of sample analysis, phloroglucinolysis reagent was prepared using 50 g L-1 phloroglucinol, 10 g L-1 ascorbic acid, and 0.1 M hydrochloric acid in methanol. One mL of 00.0250.050.0750.10.1250.150.1750.20.2250.250 2 4 6 8 10 12 14 16 18 20 22 24Absorbance of Grape Skin Extracted with 70% Acetone Time (hr) 00.20.40.60.810 2 4 6 8 10 12 14 16 18 20 22 24Absorbance of Grape Skin Extracted with 12% Ethanol  Time (hr) 44  this reagent was combined with 20 mg of skin extract and placed in a thermomixer (Eppendorf, Thermomixer R) for 20 minutes at 50?C. Then 200 ?L of skin extract/reagent was mixed with 1 mL of aqueous sodium acetate (40 mM) and filtered using 25 mm syringe filter ?with ?0.45 ??m ?PTFE membrane (VWR international). The phloroglucinolysis procedure was adapted from Kennedy and Jones (2001) and, hence, phloroglucinolysis cleavage products were assessed using retention times from Kennedy and Jones (2001).   UHPLC-MS The Ultra-High Performance Liquid Chromatography- ElectroSpray Ionization- Quadrupole- Time of Flight (UHPLC-ESI-Q-TOF) model used was an Agilent 1290 Series, Agilent Technologies 6530 Accurate-Mass Q-TOF LC/MS (Santa Clara, CA) and the procedure used was adapted from Kennedy and Waterhouse (2000). From this procedure optimal column length, retention times, and flow rate were determined for our specific model. The following series of columns were used: a Zorbax SB-AQ C18 (2.1 x 150 mm, 1.8 ?m) column, attached to a SB-AQ C18 (2.1 x 100 mm, 1.8 ?m) column, which was attached to a SB C18 (2.1 x 50 mm, 1.8 ?m) column (Agilent Technologies, Mississauga, ON, CA). The columns were thermostated at 40?C and wavelengths of 280 nm and 520 nm were monitored. The flow rate used was 0.25 mL min-1, with an injection volume of 2 ?L. Water was placed in solvent bottle A, and acetonenitrile was placed in solvent bottle B; both solvents were HPLC grade and were acidified with 0.1% formic acid. The gradient started with 10% B, then at 48 minutes changed to 18.72% B, then from 49 to 52 minutes went up to 100% B, and at 53 minutes went back down to 10% B, with 4 minutes of post-time to re-equilibrate the column. The extracted ion chromatogram (EIC) analyses were performed in negative mode, which is more sensitive than the positive mode. The formation of different adducts (potassium or sodium) which interferes with analysis, is common when using positive mode, when analyzing tannins, but absent when using negative mode. The 45  optimized parameters for the detection of tannin subunits were as follows: drying gas (N2) flow rate 10 L min-1, gas temperature 325?C, nebulizer pressure 25 psig, sheath gas (N2) temperature 350?C, sheath gas flow 12 L min-1, nozzle voltage 1000 V, fragmentor voltage 100 V, skimmer 60 V. The assignment for monomers and phloroglucinol adducts was determined by their retention times, EIC and Targeted MSMS (tandem mass spectrometry). (+)-Catechin and (-)-epicatechin have the same molecular weight (same EIC), but the (+)-catechin elutes before (-)-epicatechin. Tannin Concentration Calculation  To complete this stage of analysis, the concentration of tannin was calculated by converting the diode array detector (DAD) values obtained from UHPLC analysis into mg L-1 by using calibration curves. The calibration curve for (-)-epicatechin was obtained by running a pure (-)-epicatechin sample at 17 different concentrations (0.05, 0.01, 0.1, 0.25, 0.5, 0.75, 1, 2.5, 5, 7.5, 10, 15, 20, 25, 50, 100, 150, and 200 mg L-1) through the UHPLC with the method described above. From this calibration curve, the monomer curves with and without phloroglucinol adduct were determined following the relative mass response previously calculated by Kennedy and Jones (2001).  Calibration curves can be seen in Appendix A Figures A.1 to A.4. Next, this value was multiplied by the concentration factor (0.3 L mg-1) then multiplied by the extract weight per berry (g) to produce values in mg berry-1.  Mean Degree of Polymerization Calculation To calculate the mean degree of polymerization (mDP), tannin concentration was converted into mmol L-1 through the multiplication of values obtained in the previous section by the molecular weight of each molecule. The calibration curves expressed in mmol L-1 can be 46  seen in Appendix B, Figures B.1 to B.5. Then mDP was calculated by adding all subunits together and dividing that total by all the terminal subunits (molecules without a phloroglucinol unit attached) to obtain a value in mmol L-1. Statistical Analysis In the final step of analysis, nine replicates (three replicates from each site) of 50 skins each were analyzed for both solvents at each sampling date in each vineyard. Averages, standard deviation, percent coefficient of variation, and linear regression were calculated on Microsoft Excel 2007 to compare the changes in total tannin concentration, subunit composition, and mDP over the course of berry development. Linear regression was calculated for the entire sampling period and during two developmental periods: (i) pre-v?raison, where the majority of the berries were green, to v?raison; and (ii) post-v?raison, where v?raison was completed and all berries were red, until commercial harvest.  2.3 Results and Discussion  The skin weight obtained from the grapes at all three sites increased between the first and the last sampling dates (Figure 2.3; Table 2.1).  The linear regression throughout berry development also had a positive slope; however, at the Oliver site it was not significant (Table 2.1).  47   Figure 2.3: The weight of fifty berry skins at each sampling date. Showing standard deviation error bars; N= 6  Table 2.1: The weight of 50 grape berry skins from pre-v?raison to harvest was analyzed by linear regression; N=7 for Pinot noir and N=8 for Cabernet Franc. A t-test was also done to compare weights between the first and last sampling dates for each site; N=9. Site Slope R2 P value P value (t-test) Oliver (PN) 0.021 0.43 0.11 < 0.001 Naramata (CF) 0.99 0.046 < 0.001 < 0.001 Osoyoos (CF) 0.044 0.84 0.0014 < 0.001   Total tannins  Overall, we saw a significant increase in the concentration of total tannins per berry from the start of sampling to harvest in the Naramata samples; however, no changes in tannins extracted from grapes skins from Oliver or Osoyoos were observed (Figures 2.4 to 2.5; Table 2.2).     01234567816-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovWeight of Fifty Berries Skin (g) Sampling Date Oliver (PN)Naramata (CF)Osoyoos (CF)48   Table 2.2: The total amount of tannins per berry from pre-v?raison to harvest was analyzed by linear regression. N=8 for Naramata and Osoyoos and N=7 for Oliver. Site Solvent Slope R2 P value Oliver (PN) 70% Acetone 0.0185 0.078 0.55  12% Ethanol 0.0003 0.0085 0.84 Naramata (CF) 70% Acetone 0.0326 0.88 0.00052  12% Ethanol 0.0087 0.82 0.0022 Osoyoos (CF) 70% Acetone 0.0187 0.49 0.052  12% Ethanol -0.0023 0.17 0.32   V?raison occurred tentatively between the September 5 (green berries) and the September 19 (red berries) sampling date for each site. Tannins from all three sites generally did not vary during the pre-v?raison and post-v?raison periods, when considered separately (Figure 2.4 to 2.5). Even though there were no significant changes observed during these two periods, the same trends of an initial increase during pre-v?raison then a decrease post-v?raison occurred at each site, except for skins from the Naramata site, where tannins tended to increase post-v?raison (Table 2.3).   49   Figure 2.4: Grape skin tannins extracted from Oliver, Naramata, and Osoyoos over the course of berry development using 70% acetone as the solvent. Showing standard deviation error bars; N= 9.   Figure 2.5: Grape skin tannins extracted from Oliver, Naramata, and Osoyoos over the course of berry development using 12% ethanol as the solvent. Showing standard deviation error bars; N= 9.  024681001-Aug 21-Aug 10-Sep 30-Sep 20-Oct 09-NovTotal Tannins (mg berry-1 ) Sampling Date Oliver (PN)Naramata (CF)Osoyoos (CF)00.511.522.501-Aug 21-Aug 10-Sep 30-Sep 20-Oct 09-NovTotal Tannins (mg berry-1 ) Sampling Date Oliver (PN)Naramata (CF)Osoyoos (CF)50  Table 2.3: The linear regression of total tannins measured by UHPLC from pre-v?raison and post-v?raison was analyzed for each site and solvent with ?an ?? ?value ?of ?0.05. ?Pre-v?raison was sampled on August 8th to September 19th and post-v?raison was sampled on September 19th to October 27th for Oliver and November 7th for Naramata and Osoyoos. Pre-v?raison N=3 and post v?raison N=4 for Pinot noir and N=5 for Cabernet Franc.   Pre-V?raison Post-V?raison Site Solvent Slope R2 P value Slope R2 P value Oliver (PN) 70% Acetone 0.1391 0.83 0.27 -0.0946 0.7415 0.14  12% Ethanol 0.0051 0.47 0.52 -0.0063 0.88 0.063 Naramata (CF) 70% Acetone 0.012 0.19 0.71 0.0244 0.67 0.092  12% Ethanol 0.0019 0.044 0.87 0.0093 0.62 0.11 Osoyoos (CF) 70% Acetone 0.0211 0.52 0.49 -0.0058 0.039 0.75  12% Ethanol 0.0031 0.11 0.79 -0.0016 0.025 0.80  The percent coefficient of variation for total tannins was calculated for each site and both extraction solvents (Table 2.c4). This indicates how much the total tannin concentration changed over the course of development. It was hypothesized that the total tannin amount would vary more than 20% throughout development. We found this to be the case, with the exception of tannins from Oliver extracted with 12% ethanol, which varied by only 13.51% throughout the course of development. Despite this we did see a significant increase in total tannin from the start of sampling to harvest in the majority of our field experiment (Table 2.c4). When comparing the solvents used, we generally saw the same patterns in accumulation; nevertheless, when grapes skins were extracted with 70% acetone there was a larger yield then those extracted with 12% ethanol.       51  Table 2.4: Average, standard deviation, and percent coefficient of variation for the total amount of tannins during the entire sampling period for each site and both extraction solvents. N=8 for Naramata and Osoyoos and N=7 for Oliver. Site Solvent  Average (mg berry-1) Standard Deviation (mg berry-1) Coefficient of Variation Oliver (PN) 70% Acetone 5.7335 1.7326 30.22%  12% Ethanol 1.0437 0.141 13.51% Naramata (CF) 70% Acetone 3.3202 1.0906 32.85%  12% Ethanol 1.435 0.3286 22.90% Osoyoos (CF) 70% Acetone 4.1667 0.937 22.49%  12% Ethanol 1.697 0.3413 20.11%  Studies by Ojeda (2002), Downey (2003), and Olle (2011) observed an overall increase in total tannins, like that of our Naramata samples; however, in our samples we saw a continual increase throughout development. Downey (2003) sampled Shiraz from Willunga, South Australia and found that these tannins first increased pre- to post-v?raison but then decreased from post-v?raison to harvest (Downey et al., 2003). Others such as Ojeda (2002) and Olle (2011) sampled Shiraz from Montpellier, France in 70 L covered outdoor pots and found that these tannins increased pre- to post-v?raison but stayed the same to harvest. By contrast, Hanlin and Downey (2009) observed an overall decrease in total tannin amounts in Shiraz and Cabernet Sauvignon grape skins during two different growing seasons from Sunraysia region of Southeast Australia. In each case tannins decreased from pre- to post-v?raison then the values stayed the same for Shiraz in both growing seasons and for Cabernet Sauvignon in the 2004 to 2005 growing season. Total tannins then decreased further from post-v?raison to harvest in the 2003 to 2004 growing season for Cabernet Sauvignon grape skins (Hanlin and Downey, 2009).  The total amount of tannins extracted from grape skin clearly differs depending on variety, environment, climate, predatory stresses, and method used to extract the tannins (Canals et al., 2005; Hanlin and Downey, 2009; 2010; Bordiga et al., 2011). Most authors agree that 52  tannins either decrease post-v?raison corresponding to the accumulation of anthocyanins (Harbertson et al., 2002, Kennedy et al., 2002, Canals et al., 2005; Hanlin and Downey, 2009), or they stay the same (Ojeda et al., 2002; Canals et al., 2005, Hanlin and Downey, 2009, Olle et al., 2011). In our case, tannins extracted from berries from Oliver and Osoyoos stayed the same; conversely, the grapes from Naramata saw an increase in total tannin amount, which has been previously observed in another study (Estaban et al., 2001). This variations in tannin concentration; nevertheless, differed from the trends seen in the skin weight. The same tannin amounts were observed at harvest for all of the three sites despite size, which inferred there were other factors influencing tannin accumulation. Mean Degree of Polymerization The mDP found in grape skin extract was determined through analysis via UHPLC by dividing all the subunits by the terminal units. The mDP of grape skin tannin varies tremendously among varieties and of the same varieties in different climates; however, it does not change immensely throughout development but can be seen to increase slightly (Kennedy et al., 2001; Downey et al., 2003; Bindon and Kennedy, 2011; Olle et al., 2011). In our study polymerization increased from pre-v?raison to harvest in all samples with the exception of the grapes from the site in Osoyoos (Figure 2.6 and 2.7; Table 2.5). This is consistent with studies on Shiraz from the Univeristy of Adelaide, Waite campus (South Australia) (Kennedy et al., 2001), Cabernet Sauvignon and Shiraz from the Sunraysia region of Southeast Australia (Hanlin and Downey, 2009), Cabernet Sauvignon from Longhorne Creek, South Australia (Bindon and Kennedy, 2011), and Cabernet Sauvignon from Piemonte, Italy (Bordiga et al., 2011). When the two developmental periods, pre-v?raison and post-v?raison, were examined separately, changes in polymerization were too small to be detected statistically (Table 2.6).   53  Table 2.5: The mean degree of polymerization of tannins from pre-v?raison to harvest was analyzed by linear regression for each site and each solvent. N=8 for Naramata and Osoyoos and N=7 for Oliver. Site Solvent Slope R2 P value Oliver (PN) 70% Acetone 0.1252 0.63 0.033  12% Ethanol 0.111 0.62 0.035 Naramata (CF) 70% Acetone 0.1314 0.77 0.0041  12% Ethanol 0.0471 0.69 0.011 Osoyoos (CF) 70% Acetone 0.0426 0.4 0.092  12% Ethanol 0.0227 0.14 0.36    Figure 2.6: Grape skin tannins mean degree of polymerization extracted from Oliver (PN), Naramata (CF), and Osoyoos (CF) over the course of berry development using 70% acetone as the solvent. Showing standard deviation error bars; N= 9.  051015202530354016-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovMean Degree of Polymerization Sampling Date Oliver (PN)Naramata (CF)Osoyoos (CF)54   Figure 2.7: Grape skin tannins mean degree of polymerization extracted from Oliver (PN), Naramata (CF), and Osoyoos (CF) over the course of berry development using 12% ethanol as the solvent. Showing standard deviation error bars; N= 9.  Table 2.6: The linear regression of mPD of tannin molecules from grape skins measured by UHPLC during pre-v?raison and post-v?raison ?was ?analyzed ?for ?each ?site ?with ?an ?? ?value ?of ?0.05. ?Pre-v?raison was sampled on August 8th to September 19th and post-v?raison was sampled on September 19th to October 27th for Oliver and November 7th for Naramata and Osoyoos. Pre-v?raison N=3 and post v?raison N=4 for PN and N=5 for CF.   Pre-V?raison Post-V?raison Site Solvent Slope R2 P value Slope R2 P value Oliver (PN) 70% Acetone 0.1229 0.66 0.4 0.0572 0.063 0.75  12% Ethanol -0.0045 0.0012 0.98 0.2212 0.72 0.15 Naramata (CF) 70% Acetone -0.0077 0.0046 0.96 0.175 0.68 0.085  12% Ethanol -0.0585 0.71 0.36 0.06 0.71 0.074 Osoyoos (CF) 70% Acetone 0.007 0.13 0.76 0.0119 0.013 0.86  12% Ethanol -0.044 0.98 0.97 0.0895 0.48 0.19   Despite the increase in grape skin mDP observed in both solvents from Oliver and Naramata, all but two samples satisfied our prediction of less than 20% variation (Table 2.7). The two samples that varied by more than 20% were from Oliver extracted with 12% ethanol (27.6%) and Naramata extracted with 70% acetone (20.87%). This result was consistent with the 051015202516-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovMean Degree of Polymerization Sampling Date Oliver (PN)Naramata (CF)Osoyoos (CF)55  little changes in mDP throughout berry development reported in the literature (Hanlin and Downey, 2009; Bordiga et al., 2011; Olle et al., 2011). It should be noted that free monomers were not considered in this study. The absence of quantifying these monomers would have affected the mDP and means that our data generated slightly higher mDP values than actual values. In previous studies free monomers have not been quantified because they are in such low amounts that they do not affect composition very much (Downey et al., 2003; Hanlin and Downey, 2009).  Table 2.7: Average, standard deviation, and percent coefficient of variation for mDP over the entire course of berry development for each site and solvent. N=8 for Naramata and Osoyoos and N=7 for Oliver. Site and Solvent Average Standard Deviation Percent Coefficient of Variation Oliver 70% Acetone 25.7618 4.877 18.93% Oliver 12% Ethanol 15.325 4.229 27.60% Naramata 70% Acetone 23.8275 4.974 20.87% Naramata 12% Ethanol 13.9433 1.961 14.06% Osoyoos 70% Acetone 22.6275 2.584 11.42% Osoyoos 12% Ethanol 12.8458 1.911 14.87%   Subunit Composition The percent subunit composition was also determined by analysis via UHPLC. The composition of subunits typically does not change much (less than 20% variation) throughout berry development (Gagn? et al., 2006; Verries et al., 2008; Hanlin and Downey, 2009; Bordiga et al., 2011; Olle et al., 2011); this is confirmed by our results (PN grapes in Oliver Figure 2.8 and 2.9; CF grapes in Naramata Figure 2.10 and Figure 2.11, and Osoyoos Figure 2.12 and Figure 2.13). (+)-Catechin accounted for 42 to 69% of the subunit composition for all sites with the exception of the berries from Oliver extracted with 12% ethanol, where (+)-catechin ranged from 83 to 87% of the subunit composition. (-)-Epicatechin comprised 1 to 3% of the subunits 56  for most of the sites, with the exception of the berries from Oliver extracted with 70% acetone, which ranged from 6 to 10%, and Osoyoos extracted with 12% ethanol, whose composition stayed at 3% until the harvest sampling date when (-)-epicatechin formed 7% of the subunits. (-)-Epicatechin-3-O-gallate comprised 4 to 13% of the tannin subunits detected in the berries at each site, with the exception of Oliver extracted with 70% acetone, which ranged from 31 to 49%. (-)-Epigallocatechin ranged from 2 to 5% of the subunits found in PN grapes in Oliver extracted with both solvents and 17 to 30% of the subunits found in CF grapes in Naramata and Osoyoos extracted with both solvents.   Figure 2.8: Oliver (Pinot noir) tannin subunit composition over development extracted using 70% acetone. EGC: (-)-Epigallocatechin; ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9.  0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 27thSubunit Composition (%) Sampling Date EGCECGECC57   Figure 2.9: Oliver (Pinot noir) tannin subunit composition over development extracted using 12% ethanol. EGC: (-)-Epigallocatechin; ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9.   Figure 2.10: Naramata (Cabernet Franc) tannin subunit composition over development extracted using 70% acetone. EGC: (-)-Epigallocatechin; ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9.  0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 27thSubunit Composition (%) Sampling Date EGCECGECC0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 31st Nov 7thSubunit Composition (%) Sampling Date EGCECGECC58   Figure 2.11: Naramata (Cabernet Franc) tannin subunit composition over development extracted using 12% ethanol. EGC: (-)-Epigallocatechin; ECG: (-)-Epicatechin-3-0-gallate; EC: (-)-Epicatechin; C: (+)-Catechin. N= 9.   Figure 2.12: Osoyoos (Cabernet Franc) tannin subunit composition over development extracted using 70% acetone. EGC: Epigallocatechin; ECG: Epicatechin-3-O-gallate; EC: Epicatechin; C: Catechin. N= 9.  0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 31st Nov 7thSubunit Composition (%) Sampling Date EGCECGECC0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 31st Nov 7thSubunit Composition (%) Sampling Date EGCECGECC59   Figure 2.13: Osoyoos (Cabernet Franc) tannin subunit composition over development extracted using 12% ethanol. EGC: Epigallocatechin; ECG: Epicatechin-3-O-gallate; EC: Epicatechin; C: Catechin. N= 9.    As observed previously for Cabernet Sauvignon and Shiraz grapes by Hanlin and Downey (2009), (+)-catechin consistently comprised the highest percentage of subunits for PN and CF at both sites; however, some studies have found that (-)-epicatechin made up the highest percentage of subunits for Cabernet Sauvignon and Shiraz berries (Gagn? et al., 2006; Olle et al., 2011). In our study, (-)-epicatechin had the lowest percent composition for each sample at each site. A study by Gagn? (2006) also found (-)-epicatechin to be in the lowest composition for Cabernet Sauvignon berries grown in the 2005 growing season; conversely, in the year before, (-)-epicatechin was found at levels higher than the levels of (+)-catechin in that sample. In both CF cases (-)-epigallocatechin formed the next highest percentage of subunits, but this is not the case for the PN samples. In other studies, (-)-epigallocatechin has consistently been reported at high percent composition, ranging from 15 to 59% of the overall composition (Downey et al., 2003; Gagn? et al., 2006; Bordiga et al., 2011; Olle et al., 2011). (-)-Epicatechin-3-O-gallate usually makes up less than 10% of the subunit composition (Gagn? et al., 2006; 0%20%40%60%80%100%Aug 8th Aug 22nd Sept 5th Sept 19th Oct 3rd Oct 17th Oct 31st Nov 7thSubunit Composition (%) Sampling Date EGCECGECC60  Verries et al., 2008; Bordiga et al., 2011; Olle et al., 2011); however, in our study, for the site in Oliver extracted with 70% acetone, it was found to represent 40% of the tannin composition. High levels have also been seen in the literature for Shiraz from Willunga, South Australia (Downey et al., 2003). Subunit composition did not change much throughout development in our study; therefore, no clear trends are present to describe accumulation and concentrations of specific subunits.  Despite the fact that no change was observed in subunit composition pre-v?raison or post-v?raison, in tannins extracted from Oliver or Osoyoos, significant changes were observed in grape skin extracted from Naramata. When extracted with 12% ethanol, (-)-epigallocatechin remained constant from 17% pre-v?raison to 19% post-v?raison then significantly increased to 26% at harvest with an overall increase of 9% (Table 2.8). (-)-Epigallocatechin can also be seen to increase in other studies; from v?raison to harvest a 31.5% increase was observed in Shiraz grape skin from Montpellier, France (Verries et al., 2008). (-)-Epicatechin from the site in Naramata extracted with 70% acetone showed the same trend, constant levels were observed pre-v?raison but then increased post-v?raison (Table 2.8).         61  Table 2.8: The linear regression for the subunit composition of tannin molecules from grape skins measured by UHPLC for pre-v?raison and post-v?raison ?were ?analyzed ?for ?each ?site ?with ?an ?? ?value ?of ?0.05.  Pre-v?raison N=3 and post v?raison N=4 for Pinot noir and N=5 for Cabernet Franc.   Pre-V?raison Post-V?raison Tannin Monomer Site and Solvent Slope R2 P value Slope R2 P value (+)-Catechin Oliver 70% Acetone 0.0436 0.49 0.51 -0.0385 0.74 0.14  Oliver 12% Ethanol 0.0052 0.49 0.51 -0.0047 0.87 0.068  Naramata 70% Acetone 0.0076 0.2 0.71 0.013 0.5733 0.14  Naramata 12% Ethanol 0.0015 0.068 0.83 0.0053 0.49 0.19  Osoyoos 70% Acetone 0.0161 0.62 0.42 -0.0031 0.029 0.79  Osoyoos 12% Ethanol 0.005 0.5 0.5 -0.002 0.071 0.66 (-)-Epicatechin Oliver 70% Acetone 0.0076 0.56 0.46 -0.0016 0.26 0.49  Oliver 12% Ethanol 0.0001 0.27 0.65 -0.0002 0.82 0.096  Naramata 70% Acetone 0.0001 0.25 0.67 0.0009 0.93 0.008  Naramata 12% Ethanol 0.00005 0.038 0.88 0.0001 0.22 0.43  Osoyoos 70% Acetone 0.0006 0.98 0.083 -0.0004 0.44 0.22  Osoyoos 12% Ethanol 0.0001 0.73 0.35 0.0007 0.41 0.24 (-)-Epigallocatechin Oliver 70% Acetone 0.0031 0.67 0.39 -0.0006 0.34 0.42  Oliver 12% Ethanol 0.0001 0.11 0.78 -0.006 0.34 0.42  Naramata 70% Acetone 0.0038 0.19 0.72 0.009 0.75 0.058  Naramata 12% Ethanol 0.0003 0.013 0.93 0.0042 0.9 0.013  Osoyoos 70% Acetone 0.004 0.13 0.77 -0.0011 0.018 0.83  Osoyoos 12% Ethanol -0.0006 0.027 0.9 0.0001 0.0024 0.94 (-)-Epicatechin-3-O-Gallate Oliver 70%  Acetone 0.0849 0.99 0.072 -0.0537 0.75 0.14  Oliver 12% -0.0003 0.4 0.56 -0.0011 0.89 0.058 62  Ethanol  Naramata 70% Acetone 0.0005 0.2 0.71 0.0015 0.44 0.22  Naramata 12% Ethanol 0.00002 0.005 0.96 -0.0002 0.098 0.61  Osoyoos 70% Acetone 0.001 0.15 0.74 -0.0013 0.12 0.56  Osoyoos 12% Ethanol -0.0014 0.98 0.087 -0.0005 0.21 0.44   Throughout berry development an overall increase in subunit composition has been observed for all the Naramata samples with the exception of (-)-epicatechin-3-O-gallate which did not display any significant changes in composition (Table 2.9). Similarly, an increase was also observed in (+)-catechin and (-)-epigallocatechin for the Osoyoos grapes extracted with 70% acetone; notably, Osoyoos extracted with 12% ethanol detected no changes in composition with the exception of (-)-epicatechin-3-O-gallate which decreased (Table 2.9). This trend was also found in the literature; (-)-epicatechin-3-O-gallate terminal subunits decreased 20.8% from v?raison to harvest in Shiraz grape skins from Willunga, South Australia (Downey et al., 2003) and has also been observed for (+)-catechin which decreased 23.1% from Cabernet Sauvignon grape skins from Pessac-L?ognan appellation near  Bordeaux, France (Gagn? et al., 2006).       63  Table 2.9: Linear regression for tannin subunit composition during development for each site and both extraction solvents. N=8 for Naramata and Osoyoos and N=7 for Oliver. Tannin Monomer Site and Solvent Slope R2 P value (+)-Catechin Oliver 70% Acetone 0.0077 0.077 0.55  Oliver 12% Ethanol 0.0007 0.055 0.61  Naramata 70% Acetone 0.0184 0.86 0.00091  Naramata 12% Ethanol 0.0049 0.75 0.0058  Osoyoos 70% Acetone 0.0136 0.55 0.035  Osoyoos 12% Ethanol -0.0009 0.061 0.56 (-)-Epicatechin Oliver 70% Acetone 0.0024 0.38 0.14  Oliver 12% Ethanol 6.00E-05 0.18 0.33  Naramata 70% Acetone 0.0009 0.94 < 0.001  Naramata 12% Ethanol 0.0001 0.62 0.021  Osoyoos 70% Acetone 0.0003 0.37 0.11  Osoyoos 12% Ethanol 0.0003 0.34 0.13 (-)-Epigallocatechin Oliver 70% Acetone 0.0007 0.30 0.21  Oliver 12% Ethanol -0.0001 0.39 0.13  Naramata 70% Acetone 0.0103 0.90 0.00035  Naramata 12% Ethanol 0.0036 0.90 0.00032  Osoyoos 70% Acetone 0.0061 0.53 0.042  Osoyoos 12% Ethanol 0.0001 0.0094 0.82 (-)-Epicatechin-3-O-Gallate Oliver 70% Acetone 0.0077 0.046 0.65  Oliver 12% Ethanol -0.0004 0.49 0.079  Naramata 70% Acetone 0.003 0.84 0.0014  Naramata 12% Ethanol 0.0001 0.08 0.50  Osoyoos 70% Acetone -0.0012 0.31 0.15  Osoyoos 12% Ethanol -0.0018 0.83 0.0018  The percent coefficient of variation was then calculated for each site extracted with both solvents by taking standard deviation for each subunit composition percent and dividing it by the average of each subunit composition percent (Table 2.10). For each site, the (+)-catechin subunit composition in grape skins varied less than 20% (1.8% to 12.5%), as did the (-)-epigallocatechin subunit composition, which ranged from 4.8% to 18.1%. (-)-Epicatechin subunit variation was less than 20% for all sites and solvent, except for Osoyoos berries extracted with 12% ethanol, 64  which varied by 39.2%; the rest of the samples ranged from 7.9% to 18.0%. As for (-)-epicatechin-3-O-gallate, its variation was consistently the highest; Osoyoos grape skin extracted with 70% acetone produced a 38.2% variation and grape skin extracted with 12% ethanol produced a 47.2% variation. The rest of the samples varied between 15.4% and 19.0% (-)-epicatechin-3-O-gallate. Although a few types of subunits had a higher than 20% variation, overall we did not see a significant change in subunit composition in our field experiments.  Table 2.10: Average, standard deviation, and percent coefficient of variation for tannin subunit composition during development for each site and both extraction solvents. N=8 for Naramata and Osoyoos and N=7 for Oliver. Tannin Monomer Site and Solvent Average Standard Deviation Coefficient of Variation Overall Percent Change (+)-Catechin Oliver 70% Acetone 48.22% 6.01% 12.47% 7.47% decrease  Oliver 12% Ethanol 84.91% 1.56% 1.84% 3.35% increase  Naramata 70% Acetone 61.96% 2.08% 3.35% 4.49% decrease  Naramata 12% Ethanol 66.29% 2.62% 3.96% 3.98% decrease  Osoyoos 70% Acetone 61.95% 2.16% 3.48% 5.73% increase  Osoyoos 12% Ethanol 65.94% 2.09% 3.17% 2.18% increase (-)-Epicatechin Oliver 70% Acetone 8.79% 1.15% 13.11% 0.09% decrease  Oliver 12% Ethanol 3.14% 0.25% 7.91% 0.28% increase  Naramata 70% Acetone 1.91% 0.34% 17.97% 0.41% increase  Naramata 12% Ethanol 3.03% 0.31% 10.12% 0.77% decrease  Osoyoos 70% Acetone 1.87% 0.17% 8.96% 0.06% increase  Osoyoos 12% Ethanol 3.41% 1.34% 39.18% 4.11% increase (-)-Epigallocatechin Oliver 70% Acetone 2.54% 0.25% 9.81% 0.41% increase 65   Oliver 12% Ethanol 4.46% 0.45% 10.15% 1.08% decrease  Naramata 70% Acetone 27.98% 1.35% 4.84% 3.83% increase  Naramata 12% Ethanol 21.95% 3.96% 18.06% 9.11% increase  Osoyoos 70% Acetone 29.07% 1.55% 5.33% 1.35% increase  Osoyoos 12% Ethanol 23.69% 1.94% 8.19% 2.10% increase (-)-Epicatechin-3-O-Gallate Oliver 70% Acetone 40.45% 7.13% 17.63% 7.15% increase  Oliver 12% Ethanol 7.49% 1.43% 19.06% 2.55% decrease  Naramata 70% Acetone 8.14% 1.26% 15.42% 0.26% increase  Naramata 12% Ethanol 8.73% 1.52% 17.43% 4.36% decrease  Osoyoos 70% Acetone 7.11% 2.71% 38.15% 7.02% decrease  Osoyoos 12% Ethanol 6.95% 3.28% 47.16% 8.39% decrease       66  Chapter 3: Research Chapter 2: Comparison of Tannin Content with their Reactivity as Measured by the MCP Assay 3.1 Synopsis The Methyl Cellulose Precipitation (MCP) assay quantifies total grape tannin content based on the interaction between methyl cellulose and tannins, where insoluble polymer tannin complexes are produced and precipitated out of the solution (Sarneckis et al., 2006; Mercurio and Smith, 2008). The tannin-methylcellulose complex is then what the assay measures by subtracting the absorbance of the solution without precipitate (total phenolics) from the solution with the precipitate (phenolics minus tannin) (Sarneckis et al., 2006; Mercurio and Smith, 2008). In this assay, total grape tannin indicates the total grape tannin that have the ability to react with proteins and precipitate out of solution, thereby measuring the reactivity of the tannin, to predict astringency. The amount of tannins measured here is related to astringency by representing the amount of tannins that are able to bind to salivary proteins (Sarneckis et al., 2006; Mercurio et al., 2007). Tannin content obtained from the MCP method is directly correlated to the astringency-related wine ?tasting ?descriptor ??drying?;? ?therefore, ?astringency ?levels ?can ?be ?obtained (Mercurio and Smith, 2008). The MCP assay has been correlated to perceived astringency with an r2 value of 0.83 (Mercurio and Smith, 2008) and in a more recent study, an r2 value of 0.59 (C?ceres-Mella et al., 2013). Tannin reactivity was examined in our study over the development of the grape berries through the use of the MCP assay. As tannins ripen they generally increase in polymerization, which has been correlated to a higher astringency (Goldstein and Swain, 1963; Gawel, 1998; Peleg et al., 1999; Vidal et al., 2003). However, the practical observation of grape growers and winemakers is that the astringency of grape skin tannin decreases with maturity. In our study, we predicted that MCP values would decrease with ripening because this assay is based on the 67  reactivity of tannins. The trends in astringency, as inferred by MCP values, were then compared to the trends in the total tannins and mDP measured by UHPLC, which are not based on reactivity of tannins.  We predicted that there would not be a significant correlation between total tannins measured by MCP and UHPLC and between tannins measured by MCP and mDP.  3.2 Materials and Methods Sampling, Data Collection and Isolation of Grape Skin  The berry sampling and processing described in Chapter 2 were also used for the MCP assay described in this chapter.   Chemicals Deionized water was purified using a MilliQ water system (Millipore, Bedofrd, MA, USA). Sodium hydroxide, L-(-)-tartaric acid, (-)-epicatechin, and methyl cellulose were purchased from Sigma Aldrich (St Louis, MO, USA). Ethanol HPLC grade was purchased from Commercial Alcohols (Brampton, ON, CA), Acetone HPLC grade was purchased from Fisher Scientific (Waltham, MA, USA), and ammonium sulfate was purchased from VWR-BDH (West Chester, PA, USA). Extraction The extraction procedure described in Chapter 2 was also used for the MCP assay described in this chapter. Methylcellulose Assay   The MCP assay was conducted on the same freeze-dried extracts described in Chapter 2. To analyze grape skin extract, a 0.04% methyl cellulose solution was prepared in a 1 L volumetric flask by adding 300 mL of de-ionized water and heating it on a magnetic stir plate until it reached 80?C. Then 0.4 g of methyl cellulose was added to the flask and the contents 68  were stirred vigorously to avoid clumping. Next, 700 mL of cold (0-5?C) de-ionized water was added to the flask and the solution was left to stir overnight until it became clear. Solutions of methyl cellulose were considered unstable after two weeks and thus replaced (Sarneckis et al., 2006).  This procedure used was that of Sarneckis et al., (2006). The control used in this assay was prepared by adding 4 mg of grape skin extract to a 15 mL disposable centrifuge tube and adding 1 mL of de-ionized water to the tube. The samples were then sonicated (VWR: Symphony model 97043-968) to dissolve the extract (4 mg mL-1). Then 2 mL of ammonium sulphate and 7 mL of de-ionized water was added to the tube and left to sit for 10 minutes. The samples (0.4 mg mL-1) were then centrifuged (Thermo scientific Sorvall ST 16R) for 5 minutes at 4?C and 4000 rpm. The treatment used in this assay was prepared by adding 4 mg of grape skin extract to a 15 mL disposable centrifuge tube, then 1 mL of de-ionized water was added to the tube and sonicated to dissolve the extract (4 mg mL-1). Next, 3 mL of methyl cellulose was added to the tube and mixed by inverting 10 times, followed by the addition of 2 mL of ammonium sulphate and 4 mL of de-ionized water. The solution (0.4 mg mL-1) was then left to sit for 10 minutes, and then centrifuged for 5 minutes at 4?C and 4000 rpm. The spectrophotometer (Agilent 8453 UV-Visible system) was first blanked with 3 mL of de-ionized water; then, for both control and treatment samples, 3 mL of supernatant was pipetted into a 1 cm quartz cuvette, placed in the spectrophotometer, and absorbance was recorded at 280 nm.  Tannin reactivity by MCP analysis was calculated and results were expressed in mg L-1 (-)-epicatechin equivalence through the use of an epicatechin calibration curve (from 1 to 200 mg L-1 at 280 nm). Furthermore, MCP results were expressed in mg berry-1 by dividing the skin extract powder (g) by the number of berries (50) then multiplying this by the MCP constant that 69  was calculated by dividing the MCP (-)-epicatechin equivalence (mg L-1) by the concentration of extract powder used in the MCP assay (0.4 g L-1). Statistical Analysis In the final step of analysis, nine replicates of 50 skins each were analyzed for both solvents at each sampling date in each vineyard. Averages, standard deviations, percent coefficients of variation, and linear regression were calculated on Microsoft Excel 2007 to compare the changes in total tannin concentration as measured by MCP over the course of berry development. Linear regressions were calculated both for the entire sampling period and separately, for two developmental periods: pre-v?raison, where the majority of the berries were green; and post-v?raison, where v?raison was completed and all berries were red.   3.3 Results and Discussion  Total Tannins as Measured by the Methyl Cellulose Precipitation Assay  The MCP assay detects tannins that are able to bind to methyl cellulose protein, and can be used as an index for astringency. We had hypothesized that the total tannins measured by MCP would decrease during ripening. Despite this, the opposite was observed. The total tannins expressed through the analysis by MCP showed an overall increase in tannin content, and thus astringency, over the entire course of development for all berries extracted with 12% ethanol and for berries from Naramata extracted with 70% acetone (Table 3.1).     70  Table 3.1: Total tannins measured by MCP were analyzed using linear regression to access changes over the course of berry development for all sampling dates at each site ?with ?? ?of ?0.05. ?N=7 for Pinot noir and N=8 for Cabernet Franc berries.   Site Solvent Slope R2 P value Oliver (PN) 70% Acetone 0.0063 0.33 0.17  12% Ethanol 0.0062 0.76 0.010 Naramata (CF) 70% Acetone 0.0126 0.83 0.0018  12% Ethanol 0.0073 0.80 0.0028 Osoyoos (CF) 70% Acetone 0.0075 0.34 0.13  12% Ethanol 0.0077 0.71 0.0088  In the next stage of the analysis, berry development was split into two developmental periods, pre-v?raison and post-v?raison, to access changes in tannin concentration during these specific times (Figure 3.1 to 3.3). Tannin amount quantified via MCP showed no change during the two developmental periods, with the exception of Oliver extracted 12% ethanol and Naramata extracted with 70% acetone during post-v?raison (Table 3.2). In the Oliver sample (Figure 3.1) tannin amount remained constant pre-v?raison but increased post-v?raison from 0.3309 mg berry-1 to 0.7740 mg berry-1 at harvest. In the Naramata sample (Figure 3.2) total tannins increased from 1.2221 mg berry-1 post-v?raison to 2.1081 mg berry-1 at harvest.   71   Figure 3.1: Tannins quantified by MCP from Oliver (Pinot noir) throughout the course of berry development expressed in epicatechin equivalence. Showing standard deviation error bars; N= 9.   Figure 3.2: Tannins quantified by MCP from Naramata (Cabernet Franc) throughout the course of berry development expressed in epicatechin equivalence. Showing standard deviation error bars; N= 9.  00.511.522.516-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovTannin by MCP (mg berry-1 ) Sampling Date 70% Acetone12% Ethanol00.511.522.5316-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovTannin by MCP (mg berry-1 ) Sampling Date 70% Acetone12% Ethanol72   Figure 3.3: Tannins quantified by MCP from Osoyoos (Cabernet Franc) throughout the course of berry development expressed in epicatechin equivalence. Showing standard deviation error bars; N= 9.  Table 3.2: Linear regression was analyzed for total tannins measured by MCP for different sampling dates at each site with an ? ?value ?of 0.05. Pre-v?raison was sampled on August 8th, post-v?raison was sampled on September 19th and harvest was sampled on October 27th for Oliver and November 27th for Naramata and Osoyoos. Pre-v?raison N=3 and post v?raison N=4 for Pinot noir and N=5 for Cabernet Franc.   Pre-V?raison Post-V?raison Site Solvent Slope R2 P value Slope R2 P value Oliver (PN) 70% Acetone 0.0246 0.79 0.30 -0.0023 0.029 0.83  12% Ethanol -0.0002 0.0075 0.94 0.0124 0.93 0.038 Naramata (CF) 70% Acetone 0.0125 0.69 0.37 0.019 0.80 0.040  12% Ethanol 0.0029 0.90 0.20 0.0106 0.71 0.074 Osoyoos (CF) 70% Acetone 0.0125 0.34 0.60 0.0007 0.0014 0.95  12% Ethanol 0.0113 0.82 0.28 0.0082 0.39 0.26  To my knowledge, no one has measured grape skin tannins by MCP throughout the course of berry development. The values obtained at harvest for each sample nevertheless, did fall in the same range as other grape skin extracts studied (Seddon and Downey, 2008; Harbertson and Downey, 2009). Additional research is needed to see if MCP is applicable to grape skin extracts or a new assay that correlates with sensory perception is required.  00.511.522.533.516-Jul 05-Aug 25-Aug 14-Sep 04-Oct 24-Oct 13-NovTannin by MCP (mg berry-1 ) Sampling Date 70% Acetone12% Ethanol73  Comparison of Total Tannins and mDP from MCP and UHPLC  Total tannins examined through analysis by MCP represent tannins that are able to bind to proteins in solution. The total tannins from berries extracted with 70% acetone from Oliver showed a low correlation (r2 value of 0.33) between analysis by MCP and by UHPLC methods (Figure 3.4; Table 3.3).  When the mDP calculated from analysis via UHPLC to total tannins calculated by MCP (Figure 3.5) was compared, there was an even smaller correlation (r2 value of 0.042). The low correlation observed here is seen throughout the rest of the samples and can be seen in Appendix C (PN grapes in Oliver extracted with 12% ethanol Figure C.1 to C.2; CF grapes in Naramata Figure C.3 to C.6; Osoyoos Figure C.7 to C.10). In each case, the low correlation was significant; with the exception of the berries extracted with 70% acetone from Osoyoos when comparing tannins by MCP to mDP, or the berries extracted with 12% ethanol from Oliver when comparing tannins measured by MCP to those measured by UHPLC (Table 3.3). Table 3.3: Linear regression was analyzed for total tannins measured by MCP compared to mean degree of polymerization (mDP) and for total tannins measured by MCP compared to those measured by UHPLC, for each sampling dates and site ?with ?an ?? ?value ?of ?0.05 ?N=62 ?for ?Pinot noir and N=71 for Cabernet Franc.   Tannins by MCP vs mDP Tannins by MCP vs UHPLC Site Solvent Slope R2 P value Slope R2 P value Oliver 70% Acetone 2.1944 0.16 0.0012 2.3937 0.33 < 0.001  12% Ethanol 3.469 0.14 0.0023 -0.0114 0.0004 0.87 Naramata 70% Acetone 2.3016 0.36 < 0.001 1.481 0.48 < 0.001  12% Ethanol 2.3914 0.41 < 0.001 0.8067 0.52 < 0.001 Osoyoos 70% Acetone 0.2907 0.026 0.18 0.7139 0.19 < 0.001  12% Ethanol 1.0123 0.089 0.011 0.2527 0.064 0.032  74   Figure 3.4: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Oliver extracted with 70% acetone measured throughout berry development.  N=9 at each sampling date.   Figure 3.5: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Oliver extracted with 70% acetone measured throughout berry development. N=9 at each sampling date.   0246810120 0.5 1 1.5 2 2.5Tannin by UHPLC (mg berry-1 ) Tannin by MCP (mg berry-1) 0510152025303540450 0.5 1 1.5 2 2.5mDP (mmol L-1) Tannin by MCP (mg berry-1) 75  It was hypothesized that there would be little correlation between tannins quantified by MCP and by UHPLC, or between total tannins quantified by MCP and mDP calculated by UHPLC. We observed very little correlation, thus, our hypothesis was supported. It is unclear however, what is causing this discrepancy. Since mDP and subunit composition did not vary by much, there must be other factors; such as, climate, soil, cultivar, and human practices, involved causing a variation in astringency accessed by MCP (Van Leeuwen and Seguin, 2006). These factors may be contributing to the discrepancy between tannin amounts and perceived astringency or the discrepancy may be caused by the MCP assay precipitating pectins and over estimating tannin concentration. By contrast, we hypothesized that astringency measured by MCP would decrease over the course of berry development. This hypothesis was not supported by our findings; in fact, we saw the opposite; MCP increased. Further research is needed to validate the results of our study by sensory analysis to see if the MCP assay is a valid method for grape skin tannin analysis.      76  Chapter 4: Research Chapter 3: New Gelatin Adsorption Assay 4.1 Synopsis  Tannins contribute to the astringency experienced when drinking wine due to their ability to bind with proteins (Haslam, 1974; Carvalho et al., 2006; Sarneckis et al., 2006; Conde et al., 2007; Escot et al., 2008; Chira et al., 2011). In nature, the capability of salivary proteins to bind tannins is important because tannins can inhibit gastrointestinal enzymes that break down plant protein (Zucker, 1983; Baxter et al., 1997; Charlton et al., 2002). The inactivation of these enzymes is counteracted by salivary proteins that neutralize tannins before they reach the gastrointestinal tract (Boyd et al., 1965; Zucker, 1983; Baxter et al., 1997). The tannins are rendered inactive in the mouth, which corresponds to the astringency, bitterness, and mouth-feel properties experienced when drinking wine. Tannin-protein binding mainly involves hydrogen bonds and hydrophobic interactions (Oh et al., 1980; Murray et al., 1994; Haslam, 1998; McManus et al., 1985; McRae et al., 2010). Hydrogen bonds occur between the hydroxyl groups found on tannin subunits and the carbonyl groups found on salivary proteins, more specifically the basic proline-rich proteins whose only function is to bind tannins (Hagerman and Butler, 1981; Murray et al., 1994; Haslam, 1998; Simon et al., 2003; McRae and Kennedy, 2011). Hydrophobic interactions involve the stacking of the phenol ring (B ring) from the tannin subunit with the proline residue (Oh et al., 1980; Murray et al., 1994; Haslam, 1996; Baxter et al., 1997). Tannin-protein binding can also involve Van der Waals forces and ionic forces to a lesser extent (Oh et al., 1980; Saucier et al., 1997; Fontoin et al., 2008). Tannins are also able to bind these molecules at different sites on each molecule because they are amphipathic molecules, comprised of hydrophobic aromatic rings and hydrophilic hydroxyl groups (Haslam, 1998). Since proteins become compacted and unsystematically coiled as more tannins bind, the tannin-protein complexes to become spherical 77  (J?bstl et al., 2004). After the initial formation of the tannin-protein complex, cross-links occur within the complex forming aggregates that combine to form colloidal particles leading to the precipitation of the complex (Kallithraka et al., 1998; Simon et al., 2003; J?bstl et al., 2004, Fountoin et al., 2008; Dinnella et al., 2009). To investigate this process in our study, tannin precipitation was assessed through the development of a new method using gelatin. This new Gelatin Adsorption Assay was based on the same tannin-protein binding principles as the MCP assay. However due to the elimination of the use of a centrifuge this procedure was more cost effective and therefore had more potential to be used by viticulturists.     4.2 Materials and Methods Chemicals Gelatin Extra N?1, a commercial oenological gelatin was purchased from Laffort Oenologie, Bordeaux, France. Jackson-Triggs: ?Proprietor?s ?Selection ?Merlot ?2009 ?was ?used ?as ?a ?test wine during development of the assay. The wine used for sampling can be found in Table 4.1 and were purchased in Kelowna, British Columbia, Canada. Deionized water was purified using a MilliQ water system (Millipore, Bedford, MA, USA). Sodium hydroxide, L-(-)-tartaric acid, and methyl cellulose were purchased from Sigma Aldrich (St Louis, MO, USA). Ethanol HPLC grade was purchased from Commercial Alcohols (Brampton, ON, CA), ammonium sulfate was purchased from VWR-BDH (West Chester, PA, USA), and commercial grape seed extract, Biotan, was purchased from Laffort Oenologie (Bordeaux, FR).    78  Table 4.1: List of wine (winery and year) samples used to validate the new Gelatin Adsorption Assay.  Wine Winery Year Pinot noir Calona 2011 Pinot noir Arrow Leaf 2010 Pinot noir Cedar Creek 2008 Merlot Sandhill 2010 Merlot Arrow Leaf 2009 Merlot Grey Monk 2009 Merlot Peller 2009 Syrah Peller 2010 Syrah Sandhill 2010 Cabernet Sauvignon Grey Monk 2010 Cahors/Malbec Chateau Labrande 2009 Merlot-Tannat Brumont 2011  Gelatin Preparation First, gelatin was prepared in 50 mL centrifuge tubes at a concentration of 75 g L-1 and was prepared by dissolving the gelatin in water. The mixture was then inverted several times and vortex for 10 seconds before being put into a 60?C water bath. After 15 minutes the solution was inverted gently several times to homogenize the mixture. After 30 minutes the gelatin was fully dissolved and was removed from the water bath and again inverted several times to ensure homogeny. Liquefied gelatin (3 mL) was then poured into 15 mL centrifuge tubes and had any bubbles pipetted out. Finally the tubes were placed into a 3?C refrigerator until the gelatin completely solidified, approximately 2 hours.  Sample Preparation After solidification, the gelatin was allowed to come to room temperature (20?C +/- 2?C), before any experiments were performed. Then 200 ??L ?of ?room-temperature red wine was added to the test tubes right on top of the gelatin and swirled gently to allow the wine to completely cover the top of the gelatin. The wine was allowed to sit on the gelatin for 3 hours to allow for tannin binding, then 9.8 mL of deionized water was added to the test tube and the tube was 79  inverted 5 times. Next, 3 mL of the diluted wine sample was filtered using 25 mm syringe filter with ?0.45 ??m ?PTFE ?membrane ?(VWR ?International). The control used in this experiment was prepared in the same way, except red wine was added to empty test tubes instead of ones containing gelatin. UV-Visible Measurement and Tannin Concentration Calculation Absorbance was measured by spectrophotometer (Agilent 8453 UV-Visible system) which was first blanked with 3 mL of de-ionized water then, for both control and treatment, 3 mL of filtered supernatant was pipetted into a 1 cm quartz cuvette. The cuvette was next placed in the spectrophotometer and absorbance was recorded at 280 nm. The tannin concentration was then calculated as: Tannin (mg/L) = (((A280control- A280gelatin) ? 0.0083) / 0.0127))*50 ???????was the slope and 0.0083 was the y-intercept measured in the calibration experiment with (-)-epicatechin (Figure 4.1) and 50 was the dilution factor involved in our protocol.  80   Figure 4.1: (-)-Epicatechin calibration curve performed at 280nm. Showing standard deviation error bars; N= 3.  Linearity To determine linearity, commercial grape seed extract (GSE) was added to model wine (pH 3.61 (adjusted with NaOH), ethanol 12%, water 88%, 5 g L-1 tartaric acid) at different amounts to prepare nine different concentrations (0.25, 0.5, 0.75, 1, 1.5, 2, 3, 4, and 5 g L-1). Each concentration was added to the gelatin and underwent the procedure three times. By using the first order calibration function, linearity was accepted for an r2 value larger than 0.95 (Sarneckis et al., 2006).   Accuracy/ Recovery  To determine recovery, different amounts of commercial GSE were added to model wine and to test wine to produce concentrations of 1.5, 1, 0.75, 0.5, and 0.25 g L-1. Each concentration, as well as the wine without added GSE, was assayed three times using the Gelatin Adsorption Assay.  The theoretical value was then calculated by adding the absorbance value for wine without the commercial GSE plus, the values obtained from analysis of model wine with y = 0.0127x + 0.0083 R? = 0.9999 00.511.522.50 20 40 60 80 100 120 140 160 180 200Absorbance (280nm) Epicatechin Concentration (mg L-1) 81  GSE. This value was then converted into g L-1 (-)-epicatechin equivalence through the use of the (-)-epicatechin calibration curve. New Gelatin Adsorption Assay Correlation to MCP Next, to determine correlation between our new assay and the MCP assay, a stock solution containing 2.0 g L-1 of commercial GSE and test wine was prepared. This solution was then diluted five separate times to make solutions with 1.5, 1, 0.75, 0.5, and 0.25 g L-1 concentrations. Each concentration further underwent both the new Gelatin Adsorption Assay and the MCP assay in triplicate using 10 mm quartz cuvettes in both cases. The MCP assay was performed as outlined by Sarneckis et al. (2006) and had a dilution factor of 40. Results were graphed against each other to show correlation.   Statistical Analysis In the final step of analysis, three replicates for each experiment were analyzed. Statistical analyses including averages, standard deviation, t-tests, and linear regression were performed using Microsoft Excel 2007 to compare the new Gelatin Adsorption assay to the MCP assay.  4.3 Results and Discussion Through the above process, a new method for tannin analysis was developed in order to produce an easier and cheaper way to measure tannins in relation to astringency. The new Gelatin Adsorption Assay was developed by determining the most effective way to perform an accurate assay. As this assay was developed, a number of parameters were optimized such as gelatin concentration, amount of gelatin and sample, time for gelatin to solidify, best way to obtain a smooth surface (data not shown), and kinetics (Figure 4.2). Kinetics were performed on the gelatin in order to determine the optimal time required for tannins to precipitate gelatin to its full potential. This time was determined to be 3 hours of incubation.  82  Subsequently, the linearity and recovery of the Gelatin Adsorption Assay were assessed to determine the accuracy of the experiment. The linearity (Figure 4.3) of the new Gelatin Adsorption Assay was examined by diluting a stock solution of grape seed extract and model wine to varying concentrations. This was done in order to determine if the addition of more tannin would result in the precipitation of more gelatin, in a linear trend. The gelatin was precipitated in a linear fashion with an r2 value of 0.99 which is optimal considering linearity is accepted at an r2 value of greater than 0.95 (Sarneckis et al., 2006). A recovery experiment (Figure 4.4) was then performed on five different concentrations (1.5, 1, 0.75, 0.5, and 0.25 g L-1) to determine how accurate the method was. Each concentration yielded a percent recovery of greater than 100%.   Figure 4.2: Reaction kinetics for tannin precipitating gelatin. Showing standard deviation error bars; N= 4.  y = 1.285x-0.404 R? = 0.9479 00.10.20.30.40.50.60.70 50 100 150 200 250Absorbance at 280 nm (AU) Time (min) 83   Figure 4.3: Linearity of gelatin-tannin binding expressed in g L-1 (-)-epicatechin equivalence from varying concentrations of grape seed extract in model wine. Showing standard deviation error bars; N= 3.   Figure 4.4: Recovery of gelatin-tannin binding from a concentrated solution of grape seed extract added to wine or model wine in varying amounts to obtain different concentrations. Theoretical values represent 100% recovery. Data expressed in (-)-epicatechin equivalence. Showing standard deviation error bars; N= 3.    y = 3.5347x - 0.1331 R? = 0.9996 00.511.522.533.540 0.2 0.4 0.6 0.8 1 1.2Gelatin Tannin (g L-1) Concentration (g L-1) 00.511.522.533.544.550 0.25 0.5 0.75 1 1.5Gelatin Tannin (g L-1) Concentration (g L-1) TheoreticalActual84  The MCP assay (Sarneckis et al., 2006) was used as a reference method to validate tannin precipitation of gelatin in relation to astringency. Figure 4.5 shows correlation of the Gelatin Adsorption Assay to MCP by recording absorbance for the same solutions of commercial GSE in model wine at different concentrations. Data from both assays were then converted to (-)-epicatechin equivalence through the use of an (-)-epicatechin calibrations curve (Figure 4.1) and corrected using their own dilution factor (40 for MCP and 50 for the Gelatin Adsorption Assay). Data specifies a direct correlation of the new Gelatin Adsorption Assay to MCP by analysis via linear regression. Regression yielded a slope of 0.4042, a R2 value of 0.99 and, a P value of < 0.0001 at ?-value of 0.05 signifying that there was no difference in data variance. This indicated that the new Gelation Adsorption Assay should be as effective at quantifying the ability of tannins to cause astringency when drinking wine, as the MCP method.   Figure 4.5: Correlation of MCP to the new Gelatin Adsorption Assay using grape seed extract added to model wine in different amounts. Data expressed in (-)-epicatechin equivalence. N= 3.    y = 0.4042x - 0.1633 R? = 0.9893 00.20.40.60.811.21.41.60 0.5 1 1.5 2 2.5 3 3.5 4Tannin by Gelatin (g L-1) Tannin by MCP (g L-1) 85  Twelve different red wines were then analyzed by MCP and the new Gelatin Adsorption Assay (Figure 4.6): three Pinot noir, four Merlot, two Syrah, and one Cabernet Sauvignon were sampled from a variety of wineries throughout the Okanagan, and one Cahors/Malbec blend and one Merlot-Tannat were sampled from two wineries in France. The total tannin precipitation ranged from 2.3 to 4.2 g L-1 (-)-epicatechin equivalence for the Gelatin Adsorption Assay and 0.6 to 2.1 g L-1 (-)-epicatechin equivalence for the MCP assay. The tannin concentrations produced through analysis by MCP fall in the same ranges for a variety of wines reported in the literature (Sarneckis et al., 2006; Mercurio and Smith, 2008; Mercurio et al., 2010; C?ceres-Mella et al., 2013).  The data also showed a good correlation between the two methods with an r2 value of 0.82 and a P value of < 0.0001.    Figure 4.6: Correlation of MCP to the new Gelatin Adsorption Assay from twelve different wines. Data is expressed in (-)-epicatechin equivalence and each wine was analyzed in triplicate.  We observed that our hypothesis was supported; the results of the new Gelatin Adsorption Assay were directly correlated to results of the methyl cellulose assay. However in the future, a larger data set of wines should be investigated to confirm the robustness of the y = 1.1661x + 1.8089 R? = 0.8215 00.511.522.533.544.50 0.5 1 1.5 2 2.5Gelatin Tannin (g L-1) MCP Tannin (g L-1) 86  correlation observed. This method will provide a more cost effective alternative to the MCP method as it eliminates the use of a centrifuge. Also, the MCP assay uses methyl cellulose and ammonium sulfate while the gelatin assay only uses gelatin.                    87  Chapter 5: Conclusion 5.1 Conclusion Summary Tannins are affected by abiotic and biotic stresses that lead to changes in phenolic ripeness; the amount of polyphenols, the structure of polyphenols and extractability from grapes into wine is affected. Biosynthetic processes are altered by abiotic and biotic stresses which lead to variation in phenolic ripening where some polyphenols may not be at optimal conditions when harvested. Based on these properties, a more effective way to measure phenolic ripeness needs to be developed. Our work was the initial step towards finding the appropriate way to measure phenolic ripeness on-site. To our knowledge, no studies like ours have been performed in the Okanagan area of British Columbia. Our results indicated that the total amount of grape skin tannins changed over 20% during berry development while mDP and percent subunit composition would not most of the time, supporting our hypothesis. The literature shows that total tannins increase as the berries ripened, up until v?raison, then theoretically should decrease or stay the same until harvest due to anthocyanins starting to accumulate at v?raison (Boss et al., 1996; Bogs et al., 2005; Gagn? et al., 2009). This however, was only the case for one sample in our study. Tannin profiles for this area will help wine makers understand how tannins accumulate in the grape berries. These results indicate total tannin levels, which will help winemakers decide which varieties should be grown in the area to achieve the best wine possible. Even though polyphenols are present at small concentrations in wine they vastly affect the bouquet, colour, taste and mouth-feel properties of wine. Anthocyanins are responsible for the color while tannins contribute to the bitterness, astringency and mouth-feel properties. We hypothesized that as the grape ripens, astringency should decrease (Goldstein and Swain, 1963; Gawel, 1998; Peleg et al., 1999; Vidal et al., 2003). This was not observed in any of the samples; in fact, we saw that astringency increased. We also predicted that there would be little correlation 88  between astringency accessed by MCP with tannin polymerization and tannin amounts measured by UHPLC and this was generally what we found. Since mDP and subunit composition did not vary by much, there must be other factors involved causing a variation in astringency accessed by MCP and contributing to the discrepancy between tannin amounts and perceived astringency. The new Gelatin Adsorption Assay was found to be correlated to the MCP assay for red wine and was an effective way to quantify total tannins in relation to astringency in red wine. The gelatin used in this method is closer to the proline-rich salivary proteins found in the mouth than the methyl cellulose used in the MCP assay. It is also cheaper to run due to the elimination of the centrifuge step.    5.2 Limitations/ Variation The preparation of grape skin before extraction and the extraction technique are important factors in quantifying tannin amounts. The way the skin is treated before extraction is important in influencing the amount of tannins that the solvents are able to extract. In this study, two different solvents were used: 70% acetone, which is a commonly used solvent for extractions, and 12% ethanol, which is comparable to wine. For each analysis of tannins using 70% acetone as a solvent, the extracts consistently produced higher yields than those extracted with 12% ethanol.  Seemingly, 70% acetone is better at extracting tannins from grape skin than 12% ethanol (Canals et al., 2005; Harbertson and Downey, 2009; Downey and Hanlin 2010).   The influence of extraction methodology on grape skin tannin composition is not the only factor contributing to the variation observed. There is also a variety effect, which is seen when comparing PN to CF berries, and a site effect seen by analysis of CF from Naramata and Osoyoos. Sampling also took place in a year with high precipitation rates unusual to the sampling area. Despite these differences, the total tannin amount pre-v?raison to harvest did 89  usually vary by more than 20% while the mDP and percent subunit composition usually did not vary by more than 20%. There was variation between species and areas; nevertheless, these same trends in tannin accumulation and composition are observed in other studies (Kennedy et al., 2001; Ojeda et al., 2002; Gagn? et al., 2006; Hanlin and Downey, 2009; Bindon and Kennedy, 2011; Bordige et al., 2011; Olle et al., 2011).  There were also different properties that interfered with both the UHPLC and MCP methods which could have affected correlation and lead to variation within samples. A-type interflavan bonds that increase as tannins are oxidized are resistant to acid catalyzed cleavage preformed when samples undergo phloroglucinolysis (McRae et al., 2010). Tannins with these bonds are not as readily broken down into their monomeric parts and therefore are not completely quantified in analysis by UHPLC, but can still be precipitated during the MCP assay leading to variation between methods. There could have also been other factors, such as peptides, that were inhibiting the precipitation of tannins during the MCP assay causing a low correlation to UHPLC. These other compounds that could inhibit MCP binding need to be examined. 5.3 Suggestions for Future Research The main issues for viticulturists are being able to control the timing of ripening, colorization, and acidity while being able to balance aromas and flavour components, all of which influence or are influenced directly by polyphenol content. Skin ripening can be determined by studying the polyphenol composition in grape skins before their extraction into wine. By studying accumulation of tannins and other molecules by UHPLC over the course of development, biological markers could be determined which correspond to and indicate phenolic ripeness. Then, on-site methods could be developed which quantify these biological markers and determine the optimal harvest date.  90  We had predicted that astringency would decrease as the grape berry ripened; however, this was not observed in any of our samples and contradicts what has been shown in the literature. Since there is a discrepancy between what we observed and what has been shown in the literature, astringency should be accessed by sensory analysis to confirm our results. Furthermore, it should be assessed whether the MCP assay is a good test for analysis of astringency from grape skin tannins. The new Gelatin Adsorption Assay was found to be correlated to MCP for red wine; nevertheless, more wines and wine of different varieties with higher tannin amounts need to be assessed to add to the correlation factor. Methods for analysis of grape skin and seed extracts by the Gelatin Adsorption Assay also need to be optimized and established in order for quantification of extracts to be available.               91  References Abrahams S, Lee E, Walker AR, Tanner GJ, Larkin PJ, Ashton AR. 2003. The Arabidopsis TDS4 gene encodes leucoanthocyanidin dioxygenase (LDOX) and is essential for proanthocyanidin synthesis and vacuole development. Plant Journal 35:624-636.  Achnine L, Blancaflor EB, Rasmussen S, Dixon RA. 2004. Colocalization of L-phenylalanine ammonia-lyase and cinnamate 4-hydroxylase for metabolic channelling in phenylpropanoid biosynthesis. The Plant Cell 16:3098-3109.  Adams DO. 2006. Phenolics and ripening in grape berries. American Journal of Enology and Viticulture 57(3):249-256.  Alleweldt G, Possingham JV. 1988. Progress in grapevine breeding. TAG Theoretical and Applied Genetics 75(5):669-673.  Archetti M, Doring TF, Hagen SB, Hughes NM, Leather SR, Lee DW, Lev-Yadun S, Manetas Y, Ougham HJ, Schaberg PG, Thomas H. 2009. Unravelling the evolution of autumn colors: An interdisciplinary approach. Trends in Ecology and Evolution 24(3):166-173.   Barbehenn RV, Constabel PC. 2011. Tannins in plant-herbivore interactions. Phytochemistry 72(13):1551-1565.  Barnavon L, Doco T, Terrier N, Ageorges A, Romieu C, Pellerin P. 2000. Analysis of cell wall neutral ?sugar ?composition, ??-galactosidase activity and a related cDNA clone throughout the development of Vitis vinifera grape berries. Plant Physiology and Biochemistry 38(4):289-300.  Baxter IR, Young CJ, Armstrong G, Foster N, Bogenschutz N, Cordova T, Peer WA, Hazen SP, Murphy AS, Harper JF. 2005. A plasma membrane H-ATPase is required for the formation of proanthocyanidins in the seed coat endothelium of Arabidopsis thaliana. Proceedings of the National Academy of Sciences USA 102(7):2649-2654.  Baxter NJ, Lilley TH, Haslam E, Williamson MP. 1997. Multiple interactions between polyphenols and a salivary proline-rich protein repeat result in complexation and precipitation. Biochemistry 36(18):5566-5577.  Bell S-J, Henschke PA. 2005. Implications of nitrogen nutrition for grapes, fermentation and wine. Australian Journal of Grape and Wine Research 11(3):242-295.  Bennett RN, Wallsgrove RM. 1994. Tansley Review No. 72. Secondary metabolites in plant defence mechanisms. New Phytologist 127(4):623-633.  Berli FJ, Fanzone MN, Piccoli P, Bottini RN. 2011. Solar UV-B and ABA are involved in phenol metabolism of Vitis vinifera L. increasing biosynthesis of berry skin polyphenols. Journal of Agricultural and Food Chemistry 59(9):4874-4884. 92   Bindon KA, Smith PA, Kennedy JA. 2010 a. Interaction between grape-derived proanthocyanidins and cell wall material. 1. Effect on proanthocyanidin composition and molecular mass. Journal of Agricultural and Food Chemistry 58(4):2520-2528.  Bindon KA, Smith PA, Holt H, Kennedy JA. 2010 b. Interaction between grape-derived proanthocyanidins and cell wall material. 2. Implications for vinification. Journal of Agricultural and Food Chemistry 58(19):10736-46.  Bindon KA, Kennedy JA. 2011. Ripening-induced changes in grape skin proanthocyanidins modify their interaction with cell walls. Journal of Agricultural and Food Chemistry 59:2696-2707.  Blount JW, Korth KL, Masoud SA, Rasmussen S, Lamb C, Dixon RA. 2000. Altering expression of cinnamic acid 4-hydroxylase in transgenic plants provides evidence for a feedback loop at the entry point into the phenylpropanoid pathway. Plant Physiology 122(1):107-116.  Bogs J, Downey MO, Harvey JS, Ashton AR, Tanner GJ, Robinson SP. 2005. Proanthocyanidin synthesis and expression of genes encoding leucoanthocyanidin reductase and anthocyanidin reductase in developing grape berries and grapevine leaves. Plant Physiology 139(2):652-663.  Bogs J, Ebadi A, McDavid D, Robinson SP. 2006. Identification of the flavonoid hydroxylases from grapevine and their regulation during fruit development. Plant Physiology 140(1):279-291.  Bogs J, Jaffa FW, Takos AM, Walker AR, Robinson SP. 2007. The grapevine transcription factor VvMYBPA1 regulates proanthocyanidin synthesis during fruit development. Plant Physiology 143(3):1347-1361.  Bondada BR, Matthews MA, Shackel KA. 2005. Functional xylem in the post-veraison grape berry. Journal of Experimental Botany 56(421):2949-2957.  Bordiga M, Travaglia F, Locatelli M, Coisson JD, Arlorio M. 2011. Characterisation of polymeric skin and seed proathicyanidins during ripening in six Vitis vinifera L. cv. Food Chemistry 127:180-187.  Boss PK, Davies C, Simon PR. 1996. Analysis of the expression of anthocyanin pathway genes in developing Vitis vinifera L. cv Shiraz grape berries and the Implications for pathway regulation. Plant Physiology 111(4):1059-1066.  Bowen P, Bogdanoff C, Estergaard B, Marsh S, Usher K, Smith C, Frank G. 2005. Geology and wine 10: Use of geographic information system technology to assess viticulture performance in the Okanagan and Similkameen Valleys, British Columbia. Journal of the Geological Association of Canada 32(4):161-176.  Bowsher C, Steer M, Tobin A. 2008. Plant biochemistry. In: Bowsher C. author. Phenolics. Garland Science: Taylor & Francis Group. p. 363-397. 93   Boyd EM, Bereczky K, Godi I. 1965. The acute toxicity of tannic acid administered intragastrically. Canadian Medical Association Journal 92:1292-1297.  Bullard RW, Garrison MV, Kilburn SR, York JO. 1980. Laboratory comparisons of polyphenols and their repellent characteristics in bird-resistant sorghum grains. Journal of Agricultural and Food Chemistry 28(5):1006-1011.  C?ceres-Mella A, Pe?a-Neira A, Narv?ez-Bastias J, Jara-Campos C, L?pez-Solis R, Canals JM. 2013. Comparison of analytical methods for measuring proanthocyanidins in wines and their relationship with perceived astringency. International Journal of Food Science and Technology doi: 10.1111/ijfs.12253.  Calder?n AA, Zapata JM, Mu?oz R, Barcel? AR. 1993. Localization of peroxidise in grapes using nitrocellulose blotting of freezing/thawing fruits. HortScience 28(1):38-40.  Canals R, Llaudy MC, Valls J, Canals JM, Zamora F. 2005. Influence of ethanol concentration on the extraction of color and phenolic compounds from the skin and seeds of Tempranillo grapes at different stages of ripening. Journal of Agricultural and Food Chemistry 53:4019-4025.  Cartea ME, Francisco M, Soengas P, Velasco P. 2011. Phenolic compounds in Brassica vegetables. Molecules 16:251-280.  Carvalho E, Mateus N, Plet B, Pianet I. Dufourc E, De Freitas V. 2006. Influence of wine pectic polysaccharides on the interaction between condensed tannins and salivary proteins. Journal of Agricultural and Food Chemistry 54(23):8936-44.  Cerpa-Calderon FK, Kennedy JA. 2008. Berry integrity and extraction of skin and seed proanthocyanidins during red wine fermentation. Journal of Agricultural and Food Chemistry 56(19):9006-14.  Chandrashekar J, Mueller KL, Hoon MA, Adler E, Feng L, Guo W, Zuker CS, Ryba NJP. 2000. T2Rs function as bitter taste receptors. Cell 100(6):703-711.  Charlton AJ, Baxter NJ, Khan ML, Moir AJG, Haslam E, Davis AP, Williamson MP. 2002. Polyphenol/peptide binding and precipitation.  Journal of Agricultural and Food Chemistry 50(6):1593-1601.  Cheynier V, Duenas-Paton M, Salas E, Maury C, Souquet J-M, Sarni-Manchado P, Fulcrand H. 2006. Structure and properties of wine pigments and tannins. American Journal of Enology and Viticulture 57(3):298-305.  Cheynier V. 2005. Polyphenols in foods are more complex than often thought. American Journal of Clinical Nutrition 81:223S-229S.  94  Chira K, Lorrain B, KI, Teissedre P-L. 2011. Tannin composition of Cabernet-Sauvignon and Merlot grapes from the Bordeaux area for different vintages (2006 to 2009) and comparison to tannin profile of five 2009 vintage mediterranean grapes varieties. Molecules 16(2):1519-1532.  Chira K, Schmauch G, Saucier C, Fabre S, Teissedre P-L. 2009. Grape variety effect on proanthocyanidin composition and sensory perception of skin and seed tannin extracts from Bordeaux wine grapes (Cabernet Sauvignon and Merlot) for two consecutive vintages (2006 and 2007). Journal of Agricultural and Food Chemistry 57(2):545-553.  Choi HR, Choi JS, Han YN, Chung HY. 2002. Peroxynitrite scavenging activity of herb extracts. Phytotherapy Research 16(4):364-367.  Ciani M, Picciotti G. 1995. The growth kinetics and fermentation behaviour of some non-Saccharomyces yeasts associated with wine-making. Biotechnology Letters 17(11):1247-1250.  Conde C, Silva P, Fontes N, Dias A, Tavares R, Sousa M, Agasse A, Delrot S, Geros H. 2007. Biochemical changes throughout grape berry development and fruit and wine quality. Food 1(1):1-22.  Considine JA, Knox RB. 1979. Development and histochemistry of the cells, cell walls, and cuticle of the dermal system of fruit of the grape, Vitis vinifera L. Protoplasma 99(4):347-365.  Considine JA, Knox RB. 1981. Tissue origins, cell lineages and patterns of cell division in the developing dermal system of the fruit of Vitis vinifera L. Planta 151(5):403-412.  Coombe BG. 1992. Research on development and ripening of the grape berry. American Journal of Enology and Viticulture 43(1):101-110.  Coombe BG. 1995. Growth stages of the grapevine: Adoption of a system for identifying grapevine growth stages. Australian Journal of Grape and Wine Research 1(2):104-110.  Coombe BG, Hale CR. 1973. The hormone content of ripening grape berries and the effects of growth substance treatments. Plant Physiology 51(4):629-634.  Cortell JM, Halbleib M, Gallagher AV, Righetti TL, Kennedy JA. 2005. Influence of vine vigor on grape (Vitis vinifera L. Cv. Pinot Noir) and wine proanthocyanidins. Journal of Agricultural and Food Chemistry 53(14):5798-5808.  Cosgrove DJ. 2000. Loosening of plant cell walls by expansions. Nature 407:321-6.  Creasy GL, Lombard PB. 1993. Vine water stress and peduncle girdling effects on pre- and post-v?raison grape berry growth and deformability. American Journal of Enology and Viticulture. 44(2):193-197.  95  Croteau R, Kutchan TM, Lewis NG. 2000. Natural products (secondary metabolites). In: Buchanan B, Gruissem W, Jones R, eds. Biochemistry and Molecular Biology of Plants. Beltsville: American Society of Plant Physiologist 1250-1318.   Dai J, Mumper RJ. 2010. Plant phenolics: extraction, analysis and their antioxidant and anticancer properties. Molecules 15:7313-7352.  Dai GH, Andary C, Mondolot-Cosson L, Boubals D. 1995. Histochemical studies on the interaction between three species of grapevine, Vitis vinifera, V. rupestris and V. rotundifolia and the downy mildew fungus, Plasmopara viticola. Physiological and Molecular Plant Pathology 46(3):177-188.  de Andres-de Prado R, Yuste-Rojas M, Sort X, Andres-Lacueva C, Torres M, Lamuela-Raventos RM. 2007. Effect of soil type on wines produced from Vitis vinifera L. Cv. Grenache in Commercial Vineyards. Journal of Agricultural and Food Chemistry 55(3):779-786.  Delgado ?R, ?Mart?n ?P, ?del ?Alamo ?M, Gonzalez M. 2004. Changes in the phenolic composition of grape berries during ripening in relation to vineyard nitrogen and potassium fertilisation rates. Journal of the Science of Food and Agriculture 84:623-630.  Deluc L, Bogs J, Walker AR, Ferrier T, Decendit A, Merillon J-M, Robinson SP, Barrieu F. 2008. The transcription factor VvMYB5b contributes to the regulation of anthocyanin and proanthocyanidin biosynthesis in developing grape berries. Plant Physiology 147(4):2041-2053.  Dinnella C, Recchia A, Fia G, Bertuccioli M, Monteleone E. 2009. Saliva characteristics and individual sensitivity to phenolic astringent stimuli. Chemical Senses 34(4):295-304.  Do CB, Cormier F. 1991. Accumulation of peonidin 3-glucoside enhanced by osmotic stress in grape (Vitis vinifera L.) cell suspension. Plant Cell, Tissue and Organ Culture 24(1):49-54.  Downey MO, Harvey JS, Robinson SP. 2003. Analysis of tannins in seeds and skins of Shiraz grapes throughout berry development. Australian Journal of Grape and Wine Research 9(1):15-27.  Downey MO, Hanlin RL. 2010. Comparison of ethanol and acetone mixtures for extraction of condensed tannin form grape skin. South African Journal for Enology and Viticulture 31(2):154-159.  Escot S, Feuillat M, Dulau L, Charpentier C. 2008. Release of polysaccharides by yeast and the influence of released polysaccharides on color stability and wine astringency. Australian Journal of Grape and Wine Research 7(3):153-159.  Esteban MA, Villanueva MJ, Lissarrague JR. 2001. Effect of irrigation on changes in the anthocyanin composition of the skin of cv Tempranillo (Vitis vinifera L) grape berries during ripening. Journal of the Science of Food and Agriculture 81:409-420.  96  Ferrer-Gallego R, Hern?ndez-Hierro JM, Rivas-Gonzalo JC, Escribano-Bail?n MT. 2012. Influence of climatic conditions on the phenolic composition of Vitis vinifera L. cv. Graciano. Analytica Chimica Acta 732:73-77.  Findlay N, Oliver KJ, Nil N, Coombe BG. 1987. Solute accumulation by grape pericarp cells. Journal of Experimental Botany 38(4):668-679.  Fletcher AC, Porter LJ, Haslam E, Gupta RK. 1977. Plant proanthocyanidins. Part 3. Conformational and configurational studies of natural procyanidins. Journal of the Chemical Society, Perkin Transaction I 1628-1637.   Fontoin H, Saucier C, Teissedre P-L, Glories Y. 2008. Effect of pH, ethanol and acidity on astringency and bitterness of grape seed tannin oligomers in model wine solution. Food Quality and Preference. 19(3):286-291.  Foo LY, Porter LJ. 1980. The phytochemistry of proanthocyanidin polymers. Phytochemistry 19:1747-1754.  Ford CM, Boss PK, Hoj PB. 1998. Cloning and characterization of Vitis vinifera UDP-glucose: flavonoid 3-O-glucosyltransferase, a homologue of the enzyme encoded by the maize bronze-1locus that may primarily serve to glucosylate anthocyanidins in vivo. Journal of Biological Chemistry 273(15):9224-9233.  Forkmann G. 1991. Flavonoids as flower pigments: The formation of the natural spectrum and its extension by genetic engineering. Plant Breeding 106(1):1-26.  Fournand D, Vicens A, Sidhoum L, Souquet J-M, Moutounet M, Cheynier V. 2006. Accumulation and extractability of grape skin tannins and anthocyanins at different advanced physiological stages. Journal of Agricultural and Food Chemistry 54(19):7331-7338.  Francis L, Hoj P, Dambergs R, Gishen M, Barros Lopez MD, Godden P, Henschke P, Waters E, Herderich M, Pretorius I. 2005. Objective measures of grape quality- are they achievable? Australian & New Zealand Wine Industry Journal 20(3):12-18.  Fry SC. 2004. Primary cell wall metabolism: Tracking the careers of wall polymers in living plant cells. New Phytologist 161(3):641-675.  Gagn? S, Saucier C, G?ny L. 2006. Composition and cellular localization of tannins in Cabernet sauvignon skins during growth. Journal of Agricultural and Food Chemistry 54:9465-9471.  Gagn? S, Lacampagne S, Claisse O, G?ny L. 2009. Leucoanthocyanidin reductase and anthocyanin reductase gene expression and activity in flowers, young berries and skins of Vitis vinifera L.cv. Cabernet-Sauvignon during development. Plant Physiology and Biochemistry 47(4):282-290.  97  Gawel R. 1998. Red wine astringency: a review. Australian Journal of Grape and Wine Research 4(2):74-95.  Goldstein JL, Swain T. 1963. Changes in tannins in ripening fruits. Phytochemistry 2(4):371-383.  Goto T, Kondo T. 1991. Structure and molecular stacking of anthocyanins- flower color variation. Angewandte Chemie International Edition in English 30(1):17-33.  Green BG. 1993. Oral astringency: A tactile component of flavor. Acta Psychologica 84:119-125.  Greenspan MD, Schultz HR, Matthews MA. 1996. Field evaluation of water transport in grape berries during water deficits. Physiologia Plantarum 97(1):55-62.  Hagerman AE, Butler LG. 1981. The specificity of proanthocyanidin-protein interaction. The Journal of Biological Chemistry 256(9):4494-4497.  Hale CR. 1968. Growth and senescence of the grape berry. Australian Journal of Agricultural Research 19(6):939-945.  Hanlin RL, Downey MO. 2009. Condensed tannin accumulation and composition in skin of Shiraz and Cabernet Sauvignon grapes during berry development. American Journal of Enology and Viticulture 60(1):13-23.  Hanlin RL, Hrmova M, Harbertson JF, Downey MO. 2010. Review: Condensed tannin and grape cell wall interactions and their impact on tannin extractability into wine. Australian Journal of Grape and Wine Research 16(1):173-188.  Harbertson JF, Downey MO. 2009. Investigating differences in tannin levels determined by methylcellulose and protein precipitation. American Journal of Enology and Viticulture 60(2):246-249.  Harbertson JF, Kennedy JA, Adams DO. 2002. Tannin in skins and seeds of Cabernet sauvignon, Syrah, and Pinot noir berries during ripening. American Journal of Enology and Viticulture 53(1):54-59.  Harborne, JB, Williams, CA. 2000. Advances in flavonoid research since 1992. Phytochemistry 55:481-504.  Hardie WJ, O'Brien TP, Jaudzems VG. 1996. Morphology, anatomy and development of the pericarp after anthesis in grape, Vitis vinifera L. Australian Journal of Grape and Wine Research 2(2):97-142.  Harris JM, Kriedemann PE, Possingham JV. 1968. Anatomical aspects of grape berry development. Vitis 7:106-119. 98   Haslam E. 1974. Polyphenol-protein interactions. Biochemistry Journal 139:285-288.  Haslam E. 1996. Natural polyphenols (vegetable tannins) as drugs: possible modes of action. Journal of Natural Products 59(2):205-215.  Haslam E. 1998. Molecular recognition- phenols and polyphenols. In: Haslam E. author. Practical polyphenolics: From structure to molecular recognition and physiological action. Cambridge: Cambridge University Press. p 138-177.  Hazak JC, Harbertson JF, Lin CH, Ro BH, Adams DO. 2005. The phenolic components of grape berries in relation to wine composition. Acta Horticulturae 689:189-196.  He F, Mu L, Yan G-L, Liang N-N, Pan Q-H, Wang J, Reeves MJ, Duan C-Q. 2010. Biosynthesis of anthocyanins and their regulation in colored grapes. Molecules 15(12):9057-9091.  Hellman E. 2003. Grapevine structure and function. In: Oregon Viticulture. Hellman, E. W. (Ed.). Oregon State University Press, Corvallis. p. 5-19.  Herderich MJ, Smith PA. 2005. Analysis of grape and wine tannins: Methods, applications and challenges. Australian Journal of Grape and Wine Research 11:205-214.  Holton TA, Cornish EC. 1995. Genetics and biochemistry of anthocyanin biosynthesis. The Plant Cell 7(7):1071-1083.  Howles PA, Sewalt VJH, Paiva NL, Elkind Y, Bate NJ, Lamb C, Dixon RA. 1996. Overaxpression of L-phenylalanine ammonia-lyase in transgenic tobacco plants reveals control points for flux into phenylpropanoid biosynthesis. Plant Physiology 112(4):1617-1624.  Huang X-M, Huang H-B, Wang H-C. 2005. Cell walls of loosening skin in post-veraison grape berries lose structural polysaccharides and calcium while accumulate structural proteins. Scientia Horticlturae 104:249-263.  Huber DJ. 1983. The role of cell wall hydrolase in fruit softening. Horticultural Reviews 5:189-219.  Jackson DI, Lombard PB. 1993. Environmental and management practices affecting grape composition and wine quality - A review. American Journal of Enology and Viticulture 44(4):409-430.  Janvary L, Hoffmann T, Pfeiffer J, Hausmann L, Topfer R, Fischer TC, Schwab W. 2009. A double mutation in the anthocyanin 5-O-glucosyltransferase gene disrupts enzymatic activity in Vitis vinifera L. Journal of Agricultural and Food Chemistry 57(9):3512-3518.  J?bstl ?E, ?O?Connell ?J, ?Fairclough PA, Williamson MP. 2004. Molecular model for astringency produced by polyphenol/protein interactions. Biomacromolecules. 5(3):942-949.  99   Johnston KA, Pearce RS. 1994. Biochemical and bioassay analysis of resistance of potato (Solanum tuberosum L.) cultivars to attack by the slug Deroceras reticulatum (Muller). Annals of Applied Biology 124(1):109-131.  Kallithraka S, Bakker J, Clifford MN. 1998. Evidence that salivary proteins are involved in astringency. Journal of Sensory Studies. 13(1):29-43.   Keller M, Pool RM, Henick-Kling T. 1999. Excessive nitrogen supply and shoot trimming can impair colour development in Pinot Noir grapes and wine. Australian Journal of Grape and Wine Research 5(2):45-55.   Kennedy JA, Waterhouse AL. 2000. Analysis of pigmented high-molecular-mass grape phenolics using ion-pair, normal-phase high-performance liquid chromatography. Journal of Chromatography A 866(1):25-34.  Kennedy JA, Jones GP. 2001. Analysis of proanthocyanidin cleavage products following acid-catalysis in the presence of excess phloroglucinol. Journal of Agricultural and Food Chemistry 49:1740-1746.  Kennedy JA, Hayasaka Y, Vidal S, Waters EJ, Jones GP. 2001. Composition of grape skin proanthocyanidins at different stages of berry development. Journal of Agricultural and Food Chemistry 49(11):5348-5355.  Kennedy JA, Matthews MA, Waterhouse AL. 2002. Effect of maturity and vine water status on grape skin and wine flavonoids. American Journal of Enology and Viticulture 53(4):268-274.  Kennedy JA, Ferrier J, Harbertson JF, Peyrot des Gachons C. 2006. Technical Brief: Analysis of tannins in red wine using multiple methods: Correlation with perceived astringency. American Journal of Enology and Viticulture 57(4):481-485.   K?k D, ?elik S. 2004. Determination of characteristics of grape berry skin in some table grape cultivars (V. vinifera L.). Journal of Agronomy 3(2):141-146.  Lacampagne S, Gagn? S, G?ny L. 2010. Involvement of abscisic acid in controlling the proanthocyanidin biosynthesis pathway in grape skin: New elements regarding the regulation of tannin composition and lecuoanthocyanindin reductase (LAR) and anthocyanidin reductase (ANR) activities and expression. Journal of Plant Growth Regulation 29:81-90.  Lang A, During H. 1991. Partitioning control by water potential gradient: Evidence for compartmentation breakdown in grape berries. Journal of Experimental Botany 42(9):1117-1122.  Lang A, Thorpe MR. 1989. Xylem, phloem and transpiration flows in a grape: Application of a technique for measuring the volume of attached fruits to high resolution using Archimedes' principle. Journal of Experimental Botany 40(10):1069-1078. 100   Lapornik ?B, ?Pro?ek ?M, ?Wondra ?AG. ?2005. ?Comparison ?of ?extracts ?prepared ?from ?plant ?by-products using different solvents and extraction time. Journal of Food Engineering 71(2):214-222.  Larson KC, Berry RE. 1984. Influence of peppermint phenolics and monoterpenes on two-spotted spider mite (Acari: Tetranychidae). Environmental Entomology 13(1):282-285.  Le Bourvellec C, Guyot S, Renard CMGC. 2004. Non-covalent interaction between procyanidins and apple cell wall material. Part I. Effect of some environmental parameters. Biochimica et Biophysica Acta 1672:192-202.  Leszczynski B, Wright LC, Bakowski T. 1989. Effect or secondary plant sunstances on winter wheat resistance to grain aphid. Entomologia Experimentalis et Applicata 52(2):135-139.  Lev-Yadun S, Gould KS, Winefield C, Davies K & Gould K. 2009. Role of anthocyanins in plant defence. Anthocyanins. Springer New York. p. 21-48.  Lima M, Ferreres F, Dias A. 2012. Response of Vitis vinifera cell cultures to Phaeomoniella chlamydospora: changes in phenolic production, oxidative state and expression of defence-related genes. European Journal of Plant Pathology 132(1):133-146.  Manach C, Scalbert A, Morand C, Remesy C, Jimenez L. 2004. Polyphenols: Food sources and bioavailability. American Journal of Clinical Nutrition 79:727-747.  Manetas Y, Petropoulou Y, Psaras GK, Drinia A. 2003. Exposed red (anthocyanic) leaves of Quercus coccifera display shade characteristics. Functional Plant Biology 30:265-270.  Mattivi F, Vrhovsek U, Masuero D, Trainotti D. 2009. Differences in the amount and structure of extractable skin and seed tannins amongst red grape varieties. Australian Journal of Grape and Wine Research 15:27-35.  Matus JT, Loyola R, Vega A, Pea-Neira A, Bordeu E, Arce-Johnson P, Alcalde JA. 2009. Post-veraison sunlight exposure induces MYB-mediated transcriptional regulation of anthocyanin and flavonol synthesis in berry skins of Vitis vinifera. Journal of Experimental Botany 60(3):853-867.  Mazza G, Francis FJ. 1995. Anthocyanins in grapes and grape products. Critical Reviews in Food Science and Nutrition 35(4):341-371.  Mazza G, Fukumoto L, Delaquis P, Girard B, Ewert B. 1999. Anthocyanins, phenolics, and color of Cabernet franc, Merlot, and Pinot noir wines from British Columbia. Journal of Agricultural and Food Chemistry 47(10):4009-4017.  101  McManus JP, Davis KG, Beart JE, Gaffney SH, Lilley TH. 1985. Polyphenol interactions. Part 1. Introduction; some observations on the reversible complexation of polyphenols with proteins and polysaccharides. Journal of the Chemical Society, Perkin Transaction II 1429-1438.  McRae JM, Schulkin A, Kassara S, Holt HE, Smith PA. 2013. Sensory properties of wine tannin fractions: Implications for in-mouth sensory properties. Journal of Agricultural and Food Chemistry 61(3):719-727.  McRae JM, Kennedy JA. 2011. Wine and grape tannin interaction with salivary proteins and their impact on astringency: A review of current research. Molecules 16:2348-2364.  McRae JM, Falconer RJ, Kennedy JA. 2010. Thermodynamics of grape and wine tannin interaction with polyproline: Implications for red wine astringency. Journal of Agricultural and Food Chemistry 58(23):12510-12518.  Mercurio MD, Dambergs RG, Cozzolino D, Herderich MJ, Smith PA. 2010. Relationship between red wine grades and phenolics. 1. Tannin and total phenolic concentrations. Journal of Agricultural and Food Chemistry 58:12313-12319.  Mercurio MD, Smith PA. 2008. Tannin quantification in red grapes and wine: Comparison of polysaccharide and protein-based tannin precipitation techniques and their ability to model wine astringency. Journal of Agricultural and Food Chemistry 56:5528-5537.  Merzlyak MN, Chivkunova OB, Solovchenko AE, Naqvi KR. 2008. Light absorption by anthocyanins in juvenile stressed, and senescing leaves. Journal of Experimental Botany 59(14):3903-3911.  Mira L, Frenandez MT, Santos M, Rocha R, Florencio MH, Jennings KR. 2002. Interactions of flavonoids with iron and copper ions: A mechanism for their antioxidant activity. Free Radical Research 36(11):1199-1208.  Monagas M, Bartolome B, Gomez-Cordoves C. 2005. Updated knowledge about the presence of phenolic compounds in wine. Critical Reviews in Food Science and Nutrition 45:85-118.  Moran JF, Klucas RV, Grayer RJ, Abian J, Becana M. 1997. Complexes of iron with phenolic compounds from soybean nodules and other legume tissue: Prooxidant and antioxidant properties. Free Radical Biology and Medicine 22(5):861-870.  Morlat R, Bodin F. 2006. Characterization of viticultural terroirs using a simple field model based on soil depth ? II. Validation of the grape yield and berry quality in the Anjou vineyard (France). Plant and Soil 281(1):55-69.  Mullins MG, Bouquet A, Williams LE. 1992. Biology of the grapevine. Cambridge: Cambridge University Press.  102  Murray NJ, Williamson MP, Lilley TH, Haslam E. 1994. Study of the interaction between salivary rich proteins and a polyphenol by 1H-NMR spectroscopy. European Journal of Biochemistry 219(3):923-935.  Nijveldt RJ, van Nood E, van Hoorn D, Boelens PG, van Norren K, van Leeuwen P. 2001. Flavonoids: a review of probable mechanisms of action and potential applications. American Journal of Clinical Nutrition 74:418-425.  Nunan KJ, Davies C, Robinson Sp, Fincher GB. 2001. Expression patterns of cell wall-modifying enzymes during grape berry development. Planta 214(2):257-64.  Oh HI, Hoff JE, Armstrong GS, Haff LA. 1980. Hydrophobic interactions in tannin-protein complexes. Journal of Agricultural and Food Chemistry 28:394-398.   Ojeda H, Andary C, Kraeva E, Carbonneau A, Deloire A. 2002. Influence of pre- and post v?raison water deficit on synthesis and concentration of skin phenolic compounds during berry growth of Vitis vinifera cv. Shiraz. American Journal of Enology and Viticulture 53(4):261-267.  Olle D, Guiraud JL, Souquet JM, Terrier N, Ageorges A, Cheynier V, Verries C. 2011. Effect of pre- and post-veraison water deficit on proanthocyanidin and anthocyanin accumulation during Shiraz berry development. Australian Journal of Grape and Wine Research 17(1):90-100.  Ortega-Regules A, Ros-Garcia JM, Bautista-Ortin AB, L?pez-Roca JM, G?mez-Plaza E. 2008. Changes in skin cell wall composition during the maturation of four premium wine grape varieties. Journal of the Science of Food and Agriculture 88:420-428.   Parr AJ, Bolwell GP. 2000. Phenols in the plant and in man. The potential for possible nutritional enhancement of the diet by modifying the phenols content or profile. Journal of the Science of Food and Agriculture 80:985-1012.   Paya M, Halliwell B, Hoult JR. 1992. Interactions of a series of coumarins with reactive oxygen species. Scavenging of superoxide, hypochlorous acid and hydroxyl radicals. Biochemical and Pharmacology 44(2):205-214.  Peleg H, Gacon K, Schlich P, Noble AC. 1999. Bitterness and astringency of flavan-3-ol monomers, dimers and trimers. Journal of the Science of Food and Agriculture 79(8):1123-1128.  Pereira DM, Valentao P, Pereira JA, Andrade PB. 2009. Phenolics: From chemistry to biology. Molecules 14:2202-2211.  Pinelo M, Del Fabbro P, Manzocco L, Nunez MJ, Nicoli MC. 2005. Optimization of continuous phenol extraction from Vitis vinifera by-products. Food Chemistry 92:109-117.  Pinelo M, Arnous A, Meyer AS. 2006. Upgrading of grape skins: Significance of plant cell-wall structural components and extraction techniques for phenol release. Trends in Food Science & Technology 17(11):579-590. 103   Pirie A, Mullins MG. 1977. Interrelationships of sugars, anthocyanins, total phenols and dry weight in the skin of grape berries during ripening. American Journal of Enology and Viticulture 28(4):204-209.  Porter ML, Krueger CG, Wiebe DA, Cunnungham DG, Reed JD. 2001. Cranberry proanthocyanidins associate with low-density lipoprotein and inhibit in vitro Cu2+ induced oxidation. Journal of the Science of Food and Agriculture 81(14):1306-1313.   Pratt C. 1971. Reproductive anatomy in cultivated grapes - A review. American Journal of Enology and Viticulture 22(2):92-109.  Revilla E, Carrasco D, Benito A, Arroyo-Garcia R. 2010. Anthocyanin composition of several wild grape accessions. American Journal of Enology and Viticulture 61(4):536-543.  Rib?reau-Gayon P, Dubourdieu D, Don?che B, Lonvaud A. 2006a. Handbook of Enology: The microbiology of wine and vinifications, Volume 1, 2nd Edition. John Wiley & Sons, Ltd.  Rib?reau-Gayon P, Glories Y, Maujean A, Dubourdieu D. 2006b. Phenolic Compounds. Handbook of Enology: Volume 2, 2nd Edition. John Wiley & Sons, Ltd. p. 141-203.  Roggero JP, Coen S, Ragonnet B. 1986. High performance liquid chromatography survey on changes in pigment content in ripening grapes of Syrah. An approach to anthocyanin metabolism. American Journal of Enology and Viticulture 37(1):77-83.  Sacchi KL, Bisson LF, Adams DO. 2005. A review of the effect of winemaking techniques on phenolic extraction in red wines. American Journal of Enology and Viticulture 56(3):197-206.  Sarneckis CJ, Dambergs RG, Jones P, Mercurio M, Herderich MJ, Smith PA. 2006. Quantification of condensed tannins by precipitation with methyl cellulose: Development and validation of an optimised tool for grape and wine analysis. Australian Journal of Grape and Wine Research 12(1):39-49.  Saucier C, Bourgeois G, Vitry C, Roux D, Glories Y. 1997. Characterization of (+)-catechin?acetaldehyde ?polymers:?? ?A ?model ?for ?colloidal ?state ?of ?wine ?polyphenols. ?Journal ?of ?Agricultural and Food Chemistry 45(4): 1045-1049.   Schaefer HM, Schaefer V, Levey DJ. 2004. How plant animal interactions signal new insights in communication. Trends in Ecology & Evolution (Personal edition) 19(11):577-584.  Seddon TJ, Downey MO. 2008. Comparison of analytical methods for the determination of condensed tannins in grape skin. Australian Journal of Grape and Wine Research 14:54-61.  Simon C, Barathieu K, Laguerre M, Schmitter J-M, Fouquet E, Pianet I, Dufourc EJ. 2003. Three-Dimensional ?Structure ?and ?Dynamics ?of ?Wine ?Tannin?Saliva ?Protein ?Complexes. ?A ?Multitechnique Approach. Biochemistry 42(35):10385-10395.  104   Soleas GJ, Diamandis EP, Goldberg DM. 1997. Wine as a biological fluid: History, production, and role in disease prevention. Journal of Clinical Laboratory Analysis 11(5):287-313.  Solovchenko A, Schmitz-Eiberger M. 2003. Significance of skin flavonoids for UV-B-protection in apple fruits. Journal of Experimental Botany 54(389):1977-1984.  Souquet J-M, Cheynier V, Brossaud F, Moutounet M. 1996. Polymeric proanthocyanidins from grape skins. Phytochemistry 43(2):509-512.  Sparvoli F, Martin C, Scienza A, Gavazzi G, Tonelli C. 1994. Cloning and molecular analysis of structural genes involved in flavonoid and stilbene biosynthesis in grape (Vitis vinifera L.). Plant Molecular Biology 24(5):743-755.  Spayd SE, Wample RL, Evans RG, Stevens RG, Seymour BJ, Nagel CW. 1994. Nitrogen fertilization of white Riesling grapes in Washington. Must and Wine Composition. American Journal of Enology and Viticulture 45(1):34-42.  Srinivasan C, Mullins MG. 1981. Physiology of flowering in the grapevine -- a review. American Journal of Enology and Viticulture 32(1):47-63.  Steyn WJ, Wand SJE, Holcroft DM, Jacobs G. 2002. Anthocyanins in vegetative tissues: a proposed unified function in photoprotection. New Phytologist 155(3):349-361.  Sun BS, Pinto T, Leandro MC, Ricardo-Da-Silva JM, Spranger MI. 1999. Transfer of catechins and proanthocyanidins from solid parts of the grape cluster into wine. American Journal of Enology and Viticulture 50(2):179-184.  Treutter D. 2006. Significance of flavonoids in plant resistance: A review. Environmental Chemistry Letters 4:147-157.  Valentao P, Fernands E, Carvalho F, Andrade PB, Seabra RM, Bastos ML. 2002. Antioxidative properties of cardoon (Cynara cardunculus L.) infusion against superoxide radical, hydroxyl radical, and hypochlorous acid. Journal of Agricultural and Food Chemistry 50(17):4989-4993.  Van Leeuwen C, Friant P, Chone X, Tregoat O, Koundouras S, Dubourdieu D. 2004. Influence of climate, soil, and cultivar on terroir. American Journal of Enology and Viticulture 55(3):207-217.  Van Leeuwn C, Seguin G. 2006. The concept of terroir in viticulture. Journal of wine research 17(1):1-10.  Van Zyl J. 1987. Diurnal variation in grapevine water stress as a function of changing soil water status and meteorological conditions. South African Journal of Enology and Viticulture 8(2):7.  105  Verries C, Guiraud J-L, Souquet J-M, Vialet S, Terrier N, Olle D. 2008. Validation of an extraction method on whole pericarp of grape berry (Vitis vinifera L. cv. Shiraz) to study biochemical and molecular aspects of flavan-3-ol synthesis during berry development. Journal of Agricultural and Food Chemistry 56(14):5896-5904.  Vicens A, Fournand D, Williams P, Sidhoum L, Moutounet M, Doco T. 2009. Changes in polysaccharide and protein composition of cell walls in grape berry skin (Cv. Shiraz) during ripening and over-ripening. Journal of Agricultural and Food Chemistry 57(7):2955-60.  Vidal S, Francis L, Noble A, Kwiatkowski M, Cheynier V, Waters E. 2004a. Taste and mouth-feel properties of different types of tannin-like polyphenolic compounds and anthocyanins in wine. Analytica Chimica Acta 513(1):57-65.  Vidal S, Meudec E, Cheynier V, Skouroumounis G, Hayasaka Y. 2004b. Mass Spectrometric Evidence for the Existence of Oligomeric Anthocyanins in Grape Skins. Journal of Agricultural and Food Chemistry 52(23):7144-7151.  Vidal S, Francis L, Guyot S, Marnet N, Kwiatkowski M, Gawel R, Cheynire V, Waters EJ. 2003. The mouth-feel properties of grape and apple proanthocyanidins in a wine-like medium. Journal of the Science of Food and Agriculture 83(6):564-573.  Waite JG, Daeschel MA. 2007. Contribution of wine components to inactivation of food-borne pathogens. Journal of Food Science 72(7):M286-M291.  Wang H, Cao G, Prior RL. 1997. Oxygen radical absorbing capacity of anthocyanins. Journal of Agricultural and Food Chemistry 45:304-309.  Weiss MR. 1995. Floral color change: A widespread functional convergence. American Journal of Botany 82(2):167-185.  Winkel-Shirley B. 2001. Flavonoid Biosynthesis. A colorful model for genetics, biochemistry, cell biology, and biotechnology. Plant Physiology 126(2):485-493.  Winkel T, Rambal S. 1993. Influence of water stress on grapevines growing in the field: From leaf to whole-plant response. Functional Plant Biology 20(2):143-157.  Xie D-Y, Sharma SB, Paiva NL, Ferreira D, Dixon RA. 2003. Role of anthocyanidin reductase, encoded by BANYULS in plant flavonoid biosynthesis. Science 299(5605):396-399.  Yokotsuka K, Nagao A, Nakazawa K, Sato M. 1999. Changes in anthocyanins in berry skins of Merlot and Cabernet Sauvignon grapes grown in two soils modified with limestone or oyster shell versus a native soil over two years. American Journal of Enology and Viticulture 50(1):1-12.  Zhang Q, Su LJ, Chen JW, Zeng XQ, Sun BY, Peng CL. 2012. The antioxidative role of anthocyanins in Arabidopsis under high-irradiance. Biologia Plantarum 56(1):97-104. 106   Zhao J, Pang Y, Dixon RA. 2010. The mysteries of proanthocyanidin transport and polymerization. Plant Physiology 153:437?443.  Zucker WV. 1983. Tannins: Does structure determine function? An ecological perspective. The American Naturalist 121(3): 335-365.                       107  Appendices  Appendix A: Calibration Curves for Subunits   Figure A.1: Calibration curve for catechin and epicatechin with or without phloroglucinol. Showing standard deviation error bars; N= 3.   Figure A.2: Calibration curve for epigallocatechin (EGC) with phloroglucinol attached. Showing standard deviation error bars; N= 3.  y = 9.7921x - 3.8106 R? = 1 02004006008001000120014001600180020000 20 40 60 80 100 120 140 160 180 200DAD Integration C/EC (with or without phloro) Concentration (mg/L) y = 30.6x - 11.908 R? = 1 01000200030004000500060000 20 40 60 80 100 120 140 160 180 200DAD Intensity EGC-P Concentration (mg/L) 108   Figure A.3: Calibration curve for epicatechin gallate (ECG) without phloroglucinol attached. Showing standard deviation error bars; N= 3.   Figure A.4: Calibration curve for epicatechin gallate (ECG) with phloroglucinol attached. Showing standard deviation error bars; N= 3.  y = 4.7305x - 1.8408 R? = 1 010020030040050060070080090010000 20 40 60 80 100 120 140 160 180 200DAD Intensity ECG Concentration (mg/L) y = 4.0131x - 1.5617 R? = 1 01002003004005006007008000 20 40 60 80 100 120 140 160 180 200DAD Intensity ECG-P Concentration (mg/L) 109  Appendix B: Calibration Curves for mDP  Figure B.1: Calibration curve for catechin (C) and epicatechin (EC) without phloroglucinol, concentration expressed in mmol/L to be used in calculation of mean degree of polymerization. Showing standard deviation error bars; N= 3.   Figure B.2: Calibration curve for catechin and epicatechin with phloroglucinol attached, concentration expressed in mmol/L to be used in calculation of mean degree of polymerization. Showing standard deviation error bars; N= 3.  y = 33.735x - 3.8106 R? = 1 02004006008001000120014001600180020000 10 20 30 40 50 60DAD Integration C/EC (without phloro) Concentration (mmol/L) y = 23.632x - 3.8106 R? = 1 02004006008001000120014001600180020000 10 20 30 40 50 60 70 80DAD Integration C/EC + Phloro Concentration (mmol/L) 110   Figure B.3: Calibration curve for epigallocatechin (EGC) with phloroglucinol attached, concentration expressed in mmol/L to be used in calculation of mean degree of polymerization. Showing standard deviation error bars; N= 3.   Figure B.4: Calibration curve for epicatechin gallate (ECG) without phloroglucinol, concentration expressed in mmol/L to be used in calculation of mean degree of polymerization. Showing standard deviation error bars; N= 3.  y = 71.103x - 11.908 R? = 1 01000200030004000500060000 10 20 30 40 50 60 70 80 90DAD Integration EGC-P Concentration (mmol/L) y = 10.693x - 1.8408 R? = 1 010020030040050060070080090010000 10 20 30 40 50 60 70 80 90DAD Intensity ECG Concentration (mmol/L) 111   Figure B.5: Calibration curve for epicatechin gallate with phloroglucinol attached, concentration expressed in mmol/L to be used in calculation of mean degree of polymerization. Showing standard deviation error bars; N= 3.       y = 6.4055x - 1.5617 R? = 1 01002003004005006007008000 20 40 60 80 100 120DAD Intensity ECG-P Concentration (mmol/L) 112  Appendix C: Correlation Between total tannins measured by MCP and Total Tannins Measured by UHPLC of mDP  Figure C.1: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Oliver extracted with 12% ethanol measured throughout berry development.   Figure C.2: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Oliver extracted with 12% ethanol measured throughout berry development.   y = -0.0114x + 1.0484 R? = 0.0004 00.20.40.60.811.21.40 0.2 0.4 0.6 0.8 1 1.2Tannin by UHPLC (mg/berry) Tannin by MCP (mg/berry) y = 10.373x + 11.028 R? = 0.3746 0510152025300 0.2 0.4 0.6 0.8 1 1.2Mean Degree of Polymerization Tannin by MCP (mg/berry) 113   Figure C.3: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Naramata extracted with 70% acetone measured throughout berry development.    Figure C.4: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Naramata extracted with 70% acetone measured throughout berry development.   y = 1.481x + 0.8928 R? = 0.4788 01234560 0.5 1 1.5 2 2.5 3 3.5Tannin by UHPLC (mg/berry) Tannin by MCP (mg/berry) y = 5.5347x + 14.756 R? = 0.3215 051015202530350 0.5 1 1.5 2 2.5 3 3.5Mean Degree of Polymerization Tannin by MCP (mg/berry) 114   Figure C.5: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Naramata extracted with 12% ethanol measured throughout berry development.    Figure C.6: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Naramata extracted with 12% ethanol measured throughout berry development.   y = 0.8067x + 1.0198 R? = 0.5167 00.511.522.50 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6Tannin by UHPLC (mg/berry) Tannin by MCP (mg/berry) y = 3.7474x + 12.014 R? = 0.313 024681012141618200 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6Mean Degree of Polymerization Tannin by MCP (mg/berry) 115   Figure C.7: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Osoyoos extracted with 70% acetone measured throughout berry development.    Figure C.8: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Osoyoos extracted with 70% acetone measured throughout berry development.   y = 0.7139x + 2.8467 R? = 0.1853 012345670 0.5 1 1.5 2 2.5 3 3.5Tannin by UHPLC (mg/berry) Tannin by MCP (mg/berry) y = 0.4977x + 21.707 R? = 0.0118 051015202530350 0.5 1 1.5 2 2.5 3 3.5Mean Degree of Polymerization Tannin by MCP (mg/berry) 116   Figure C.9: Correlation between total tannins measured by MCP and by UHPLC expressed in epicatechin equivalence. Samples are of grape skin extract from Osoyoos extracted with 12% ethanol measured throughout berry development.    Figure C.10: Correlation between total tannin precipitated by MCP expressed in epicatechin equivalence and mDP calculated through analysis by UHPLC. Samples are of grape skin extract from Osoyoos extracted with 12% ethanol measured throughout berry development.  y = 0.2527x + 1.4832 R? = 0.0642 00.511.522.50 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Tannin by UHPLC (mg/berry) Tannin by MCP (mg/berry) y = 0.7919x + 12.176 R? = 0.0201 024681012141618200 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Mean Degree of Polymerization Tannin by MCP (mg/berry) 

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