Evaluation and Improvement of Freezing Tolerance in Cold Sensitive Grape Genotypes

Home , Arneis, Regent (grape), Rotberger

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Shouxin Li

Graduate Program in Horticulture and Crop Science

The Ohio State University

2014

Master's Examination Committee:

Dr. Imed Dami, Advisor

Dr. Michelle Jones

Dr. Joshua Blakeslee

Copyrighted by

Shouxin Li

2014

Abstract

Grape and wine industries in colder regions such as Ohio have been expanding rapidly and demand for premium wine grapes has also increased. However, several popular cultivars are sensitive to freezing temperatures below -20°C. The objectives of this research were to: 1) evaluate the freezing tolerance (FT) of field-grown winegrape cultivars new to Ohio, 2) evaluate the response of field-grown winegrape cultivars to exogenous ABA, and 3) characterize the changes of FT and water content in bud tissues of greenhouse-grown grapevines in response to exogenous ABA. Initially, FT (or LT50) of 23 cultivars were evaluated between September and April in two locations for three seasons. The purpose of this study was to characterize FT as influenced by genotype.

Specifically, the objective of this three-year study was to determine the FT of 23 winegrape cultivars. Three different methods including date-mode method, piecewise regression and mean LT50s were used to estimate FT. We were able to classify the 23 cultivars into three groups of FT: most cold sensitive including Gamay noir, Pinotage,

Rotberger, Regent, Chardonnay, and Cabernet franc; least cold sensitive including

Syrah, Lagrein, Tempranilllo, Barbera, and Durif and the intermediate group which included Malvasia, Dolcetto, Siegerrebe, Carménère, Cabernet Sauvignon, Sauvignon blanc, Malbec, Arneis, Teroldego, Sangiovese, Merlot, and Kerner. In the ABA study, we evaluated the effect of exogenous ABA on FT of two cold sensitive cultivars, Vitis vinifera ‘Chardonnay’ and ‘Pinot gris’. Grapevines were sprayed with foliar ABA at a ii concentration of 0 mg·L-1 (control), or 400 to 500 mg·L-1 at vine phenological stages corresponding to véraison, post-véraison, and post-harvest. Exogenous ABA application at the concentrations of 400 mg·L-1 and 500 mg·L-1 effectively improved the bud FT of

‘Chardonnay’ and ‘Pinot gris’ without affecting vine size, yield or fruit composition. The best time to spray ABA on ‘Pinot gris’ was between véraison and 20 days post-véraison or leaf age between 105 d and 120 d which led to the lowest LT50 and deepest dormancy.

Differences among ABA application timing of ‘Chardonnay’ were not obvious. Finally, the relationship between FT and ABA-induced desiccation was investigated in three temporal experiments. The purpose of this study was to confirm findings from previous greenhouse experiments. ‘Cabernet franc’ potted grapevines were used in three experiments conducted in the greenhouse in 2012 and 2013. The effects of ABA on FT and water content in bud and leaf tissues were determined. The results demonstrated that application of exogenous ABA increased the bud FT of greenhouse-grown ‘Cabernet franc’ grapevines and the effect was shown 1w after ABA application. ABA caused bud desiccation, which may have led to increased FT. Our study showed that bud dehydration may occur as early as 48h after ABA application which led to increased FT

(decreased LT50) one week later. Ultimately, the findings of this project are valuable to grape producers to provide another tool for freeze protection and to the scientific community to further our understanding of the mechanisms of FT.

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Dedicated to my dear parents, Meihua Wang and Maozhong Li

Acknowledgments

First of all, I wish to thank my advisor, Dr. Imed Dami, for sharing his viticultural knowledge and providing great research opportunity. I am especially thankful to his guidance and patience. I definitely could not finish my graduate study without his support and help.

I would like to thank Dr. Michelle Jones and Dr. Joshua Blakeslee. Dr. Jones gave me a lot of instructions on scientific writing. Dr. Blakeslee taught me a lot in biochemistry area. Both of my committee members gave me invaluable suggestions for my project.

I am very thankful for the support from all my previous and current lab mates, Dr. Yi

Zhang, Ms. Diane Kinney, Ms. Abigail Gerdes, Mr. Thomas Todaro, and Dr. Trudi

Grant. Thank you to Dr. Ann Chanon for sparing a lot of time to help me on sugar analysis. I am also very thankful for the help from Mr. Greg Jones, Ms. Yvonne

Woodworth, Ms. Lisa Robbins, and Mr. Bruce Williams on my field study. Thanks to

Mr. Mike Davault and Ms. Kesia Hartzler with environmental control of the greenhouses and growth chambers. Thank you to Mr. David Scurlock, Mr. Todd Steiner, and Mr.

Patrick Pierquet for always sharing their viticulture and enology knowledge and expertise. I am thankful to the hard work of all my undergraduate interns, Natalie Fry,

Steven Parker, Bailey Miller and Robert Tichinel.

My research is funded by the Dept. of Horticulture and Crop Science, USDA-NIFA, and

Ohio Grape Industry Program.

Vita

2007...... Laiwu No.17 High School

2012...... B.S. Landscape Gardening, South China

Agricultural University

2012 to present ...... Graduate Research Associate, Department

of Horticulture and Crop Science, The Ohio

State University

Fields of Study

Major Field: Horticulture and Crop Science

Specialization: Viticulture

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Table of Contents

Abstract ...... ii

Acknowledgments...... v

Vita ...... vii

List of Tables ...... x

List of Figures ...... xii

Chapter 1: Literature Review ...... 1

Chapter 2: Evaluation of the Freezing Tolerance of Twenty three Winegrape Cultivars

New to Ohio ...... 22

Chapter 3: Improving Freezing Tolerance of Cold-Sensitive Grape Cultivars Using

Exogenous Abscisic Acid ...... 53

Chapter 4: Effects of Exogenous Abscisic Acid on Bud Freezing Tolerance and Water content of Greenhouse-grown Vitis vinifera ‘Cabernet franc’ Grapevines ...... 92

Bibliography ...... 110

Appendix A: Freezing tolerance (LT50) profiles of 19 winegrape cultivars grown in the

Wooster research vineyard. The 3-year LT50s were fitted to parabolic trendlines, and an equation with R2 were computed for each cultivar (listed alphabetically)...... 122

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Appendix B: Environmental Conditions (Temperature, Relative Humidity, and PAR) during the Greenhouse Experiments ...... 128

Appendix C: Report of Phytoxicity of Greenhouse-grown Grapevines ...... 140

List of Tables

Table 2.1. Description of winegrape clutivars planted at the Wooster and Kingsville research vineyards ...... 41

Table 2.2. Growing degree days (GDD), frost-free days (FFD), and precipitation relative to the phenology of Vitis Vinifera grapevines grown in the research vineyard in Wooster,

OH ...... 42

Table 2.3. Estimated minimum LT50s using mode-date-method, mean of observations in piecewise regression, and annual mean LT50s by cultivar ...... 43

Table 2.4. Correlations coefficients between annual mean freezing tolerance, date-mode, and piecewise regression method for two seasons (2011, and 2012) ...... 44

Table 2.5. Bud and cane phloem mortality of 23 winegrape cultivars planted in Wooster research field after a freeze event (-24.1°C) on 7 Jan. 2014 ...... 45

Table 3.1. Abscisic acid (ABA) application dates and corresponding growing degree days (GDD) and days after budburst (DAB) relative to the phenology of ‘Pinot gris’ and

‘Chardonnay’ ...... 76

Table 3.2. Effect of abscisic acid (ABA) on yield components, fruit composition, and vine size in ‘Pinot gris’ grapevines grown in Kingsville, Ohio ...... 77

Table 3.3. Effect of abscisic acid (ABA) on yield components, fruit composition, and vine size in ‘Chardonnay’ grapevines grown in Geneva, Ohio (Harvest date: 30 Sept.

2013) ...... 78

Table 3.4. Bud and cane damage of ‘Pinot gris’ and ‘Chardonnay’ after sub-freezing event in Kingsville (-25.3 °C) and Geneva (-23.9 °C) on 7 Jan. 2014 (Samples were collected on 13 Jan. 2014) ...... 79

Table 3.5. Effect of abscisic acid (ABA) on budburst of ‘Pinot gris’ and ‘Chardonnay’ grapevines grown in Kingsville, OH and Geneva, OH in 2013...... 80

Table 4.1. Abscisic acid (ABA) application dates and corresponding leaf age relative to the phenology of greenhouse-grown ‘Cabernet franc’...... 105

List of Figures

Figure 1.1 Structure of Abscisic Acid (ABA) ...... 8

Figure 1.2 Structures of (S)-cis-ABA, (R)-cis-ABA and (S)-2-trans-ABA ...... 8

Figure 1.3 The ABA precursor IPP can be synthesized with plastids via the terpenoid pathway (B) ...... 10

Figure 1.4 Biosynthesis pathway of abscisic acid (ABA) ...... 11

Figure 2.1. Daily minimum and maximum temperatures and dates of fall frost (FF) recorded at Wooster research vineyard during: A) 2011-2012 season; B) 2012-2013 season and C) 2013-2014 season ...... 46

Figure 2.2. Combined LT50s of A) Barbera B) Dolcetto C) Gamay noir D) Regent in

Wooster research vineyard for the three years by day of year ...... 49

Figure 2.3. Estimated minimum LT50s of winegrape cultivars planted in Wooster research vineyard using date-mode method by year: A) 2011-2012 and B) 2012-2013 .. 50

Figure 2.4. Estimated minimum LT50s of winegrape cultivars planted in Wooster research vineyard using piecewise regression by yearA) 2011-2012 and B) 2012-2013 . 51

Figure 2.5. Annual mean LT50 of winegrape cultivars planted in Wooster research vineyard during A) 2011-2012; B) 2012-2013 and C) average of 2011-2012 and 2012-

2013 seasons ...... 52

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Figure 3.1. Effect of abscisic acid (ABA) on leaf senescence and abscission of ‘Pinot gris’ grapevines grown in Kingsville, OH ...... 81

Figure 3.2. Effect of abscisic acid (ABA) on leaf abscission of ‘Pinot gris’ grapevines grown in Kingsville in A) 2012 and B) 2013 ...... 82

Figure 3.3. Effect of abscisic acid (ABA) on chlorophyll content of ‘Pinot gris’ grapevines grown in Kingsville in 2013...... 83

Figure 3.4. Effect of abscisic acid (ABA) on leaf senescence and abscission of

‘Chardonnay’ grapevines grown in Geneva, OH ...... 84

Figure 3.5. Effect of abscisic acid (ABA) on bud dormancy (days to 50% budbrust) on

‘Pinot gris’ grown in Kingsville during A)2012-2013 and B)2013-2014 seasons ...... 85

Figure 3.6. Daily minimum and maximum temperatures and dates of fall frost (FF) and budburst (BB) recorded at ‘Pinot gris’ and ‘Chardonnay’ fields in: A) Kingsville, OH

(2012-2013); B) Kingsville, OH (2013-2014); C) Geneva, OH (2012-2013); and D)

Geneva, OH (2013-2014) ...... 86

Figure 3.7. Effect of ABA on freezing tolerance (LT50) in ‘Pinot gris’ grapevines grown in Kingsville during A) 2012-2013 and B) 2013-14 seasons ...... 90

Figure 3.8. Response of bud LT50 to ABA applied at véraison, post-véraison and post- harvest in Geneva, OH during A) 2012-2013 and B) 2013-14 seasons ...... 91

Figure 4.1. Sampling protocol for bud freezing test, leaf/bud water content and leaf/bud sugar concentration of greenhouse-grown ‘Cabernet franc’ ...... 106

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Figure 4.2. Effect of ABA on freezing tolerance (LT50) of greenhouse-grown ‘Cabernet franc’ grapevines: A) Experiment 1 conducted in July 2013; B) Experiment 2 conducted in November, 2013; C) Experiment 3 conducted in July, 2014...... 107

Figure 4.3. Effect of ABA on leaf water content of greenhouse-grown ‘Cabernet franc’ grapevines: A) Experiment 1 conducted in July 2013; B) Experiment 2 conducted in

November, 2013; C) Experiment 3 conducted in July, 2014 ...... 108

Figure 4.4. Effect of ABA on bud water content of greenhouse-grown ‘Cabernet franc’ grapevines: A) Experiment 1 conducted in July 2013; B) Experiment 2 conducted in

November, 2013; C) Experiment 3 conducted in July, 2014...... 109

Figure C.1. ‘Cabernet franc’ damage in tips and leaves (photos taken on 16 July, 2013)

...... 140

Figure C.2. ‘Chambourcin’ damage in leaves and tips (photos taken on 16 July, 2013)

...... 141

Figure C.3. ‘Cabernet franc’ —before spray (photos taken on 25 July, 2013) ...... 147

Figure C.4. ‘Cabernet franc’—24h after spray (photos taken on 26 July, 2013)-black leaf margins on shoot tips ...... 147

Figure C.5. ‘Cabernet franc’ — ‘Pylon + Avid + Capsil + Sovran’. Young leaves cupped upwards and wrinkled ...... 148

Figure C.6. ‘Chambourcin’--‘Pylon + Avid + Capsil + Sovran’ treatment’s before (A) and after (B-D) spray application ...... 149

Figure C.7. ‘Carbernet franc’— ‘Sanmite + Capsil’ before (A) and after (B-D) spray application ...... 150

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Figure C.8. ‘Chambourcin’— ‘Sanmite + Capsil’ before (A) and after (B-D) spray application ...... 151

Figure C.9. ‘Cabernet franc’ — ‘Judo + Capsil’ (A) before, and after spray application

(B-D) ...... 152

Figure C.10. ‘Chambourcin’— ‘Judo + Capsil’ (A) before, and (B-D) after spray application ...... 153

Figure C.11. ‘Cabernet franc’ — ‘Marathon + Capsil’ before (A) and after (B-D) spray application ...... 154

Figure C.12. ‘Chambourcin’— ‘Marathon + Capsil’ before (A) and after (B-D) spray application...... 155

Chapter 1: Literature Review

Grapes are fruit crops of great economic value, but exhibit a high level of temperature sensitivity and are easily threatened by winter injury due to their wide plant distribution.

Freezing injury can result in crop reduction, thus economic losses to the grape and wine industry. Therefore, it is critical to understand and improve the freezing tolerance (FT) of grapevines. The literature review will provide a description of FT, methods used to measure FT, factors affecting FT, and a summary of methods by which this damage may be prevented. Finally, the role of abscisic acid (ABA) in stress responses will be discussed with emphasis on the role of ABA to mediate FT.

1. Freezing tolerance and winter injury to grapevines

1.1 Freezing tolerance of grapevines

Definition of FT

In grapevine, FT is defined as the ability of dormant tissues to resist exposure to freezing temperatures during autumn and winter (Levitt, 1980; Sakai and Larcher, 1987; Zabadal et al. 2007). FT of buds is typically quantified by determining the temperature capable of killing 50% of the population, termed ‘lethal temperature 50’or LT50 (Wolf and Pool,

1987; Zabadal et al. 2007). FT of grapevines is dynamic during the dormant season and can be divided into three stages: cold acclimation (September to December), maximum hardiness (December to February) and deacclimation (February to April) (Zabadal et al.

2007). Grapevine FT is also influenced by environmental conditions, cultural practices, and grape genotypes (Zabadal et al., 2007).

Mechanism of freezing tolerance in grapes

Grapevine responds to freezing temperature differently from different vine tissues. There are two basic mechanisms: the canes and trunks tolerate ice formation extracellularly, which results in intracellular desiccation of the cytoplasm; in grape buds, however, FT is the result of cytoplasmic supercooling (Jones et al., 1999; Fennell, 2004; Zabadal et al.

2007). Supercooling occurs when the contents of a cell remain in a liquid state at temperatures below the freezing point of water (Barke et al. 1997; Zabadal et al. 2007). In addition to these two physiological mechanisms, grapevines have developed several adaptiations that increase FT. For example, physical barriers like bud axes resist ice formation by preventing water transfer from extracellular regions to cells, thereby maintain bud cells dehydrated and resistant to freezing (Jones et al. 2000).

FT measurement

Methods of freezing tolerance test: A combination of field analysis and controlled testing (laboratory methods) can effectively detect and quantify differences in FT between cultivars and appraise environmental condition, and management practices

(Fennell, 2004; Zabadal et al., 2007). Laboratory methods such as electrolyte leakage, tissue staining, chlorophyll fluorescence, oxidative browning and thermal analysis can provide information on the critical temperatures causing vine injury, the most susceptible tissues on vines, and the performances of different cultivars (Fennell, 2004; Zabadal et al., 2007). This project has made use of several of the field- and laboratorary-based

methods described above to assess FT in grapevines. Specific methods used are described in details below.

Thermal analysis: When the temperature decreases to a certain level, the supercooled water in grape buds nucleates to ice and releases heat. These exotherms can be readily detected by thermocouples (or thermoelectric modules) (Zabadal et al., 2007). A grape bud typically generates both a single high-temperature exotherm (HTE), caused by the crystallization of free water outside bud cells; as well as one or more low temperature exotherms (LTE), which are the results of the crystallization of intracellular supercooled water (Andrews et al., 1984; Pierquet and Stushnoff, 1980; Pierquet et al., 1977;

Quamme, 1986; Wolf and Pool, 1987; Fennell, 2004). The HTE often occurs at temperatures between -5 °C to -10 °C and does not cause any bud injury while the LTE often occurs at or lower than -10 °C and generally indicates that bud tissues are killed

(Stergios and Howell, 1973; Pierquet and Stushnoff, 1980; Zabadal et al., 2007). Thermal analysis is a useful measurement in obtaining accurate and consistent bud killing temperatures. Twenty cultivars from Vitis labruscana, Vitis vinifera and hybrid had been observed and the LT50 were within 1 °C of each other (Andrews et al., 1984; Fennell,

2004). However, correct methods and specialized equipment are required for accurate prediction. For example, in the early stages of dormancy, HTE is difficult to separate from LTEs since they occur close to each other (Fennell, 2004). Placing the buds on moistened filter paper after excision allows the separation between HTE and LTE (Wolf and Pool, 1987). Additionally, when setting the freezer temperature, a fast cooling rate

(40 °C/hour) produced inconsistent LTEs; 1.5 °C to 10 °C/hour can produce consistent

LTEs (Quamme, 1986). In addition to HTE/LTE analyses, FT of canes and trunks can

also be determined using controlled freezing tests by removing plant tissues at specific temperature intervals and detecting tissue browning visually.

Winter injury assessment: To identify differences among cultivars and evaluate the extent of the injury, visual damage assessments on buds, canes and trunks can be conducted following freezing events. During the dormant season, live tissues always show a light green color after excision, while damaged tissues are brown or black. This is because the membranes surrounding each cell are destroyed when freeze occurs (Zabadal et al. 2007). When the tissues thaw after freezing cell contents will leak into surrounding regions and oxidative enzymes will turn tissues to brown (Zabadal et al. 2007). When assessing buds, a razor blade is used to excise the tissue at half of the overall height of the bud, allowing visual inspection of a cross-section of the compound grape bud, including primary, secondary and tertiary buds. The primary bud (the largest of the three) centrally located, is responsible for flowering shoots (Zabadal et al. 2007). The secondary bud is smaller and less fruitful and usually remains dormant (Zabadal et al. 2004). Tertiary bud is the smallest and does not produce any fruit (Zabadal et al. 2007). Primary buds are more tender than secondary or tertiary, so when a freeze stress occurs, a large percentage of primary buds are damaged, and the survival of secondary and tertiary buds may still have the potential to produce crop and develop leaf area for long-term survival (Zabadal et al. 2007). To assess canes, cordons and trunks, the bark is removed to observe the phloem tissue just below the bark. Phloem is the most tender cane tissue in the vascular system. Even when phloem is severely injured, cambium and the xylem are often less injured or even not injured compared to phloem (Zabadal et al., 2007). Freezing injuries

in cordons and trunks are most severe in the phloem and progress from outside to the inside of the organs (Zabadal et al., 2007).

Freezing injury of grapevines and economic loss

Freezing injury is a serious problem which can limit production, damage vine parts, resulting in secondary diseases (crown gall), or even kill the whole vine (Fennell, 2004).

Differences in the FT of cultivars may be small, but will result in large differences in the field survival of these cultivars (Wolf and Cook, 1991; Fennell, 2004).

Winter injury will result in direct losses in grape production and will have further effect on wine production. Expansion of grape acreage, production sustainability, and the success of wine-related industries in production regions that experience winter cold are threatened by the frequent occurrence of cold weather events. Wine grape production regions in northern U.S.A. have experienced substantial economic loss of production caused by cold weather events in 2003, 2004, 2005, 2009, 2012, and 2014 (Zabadal et al., 2007; Dami et al. 2012; Dami et al. 2014). The state of Ohio has experienced consecutive years of freezing-related loss of grape production for the last five years with the greatest loss occurring in 2014 (Dami et al., 2014; Dami and Lewis, 2014). For Vitis vinifera, the total direct loss per year is $24 per vine; the total direct loss of hybrid per year is $16 per vine (Zabadal et al. 2007). The losses from wine production are higher with $33 per vine per year for Vitis vinifera and $ 29 for hybrid (Zabadal et al. 2007).

Losses in real production tend to be even higher, since the replacement of a vine will affect the production for the next four years.

Factors affecting freezing tolerance of grapes

Genotype: Vitis vinifera cultivars are most frequently grown in regions where winter temperatures stay above -22 °C (Wolf and Miller, 2001; Wolf and Warren, 2000, Fennell,

2004). Hybird cultivars with higher percentage of Vitis labruscana were more tolerant to freeze than cultivars with higher percentages of Vitis vinifera (Bourne et al., 1991;

Fennell, 2004). Some species that originate from North America and Asia are more freeze tolerant than Vitis vinifera and hybrid (Fennell, 2004). For example, FT of V. riparia, and V. amurensis have been reported at -30 °C to -40 °C (Alleweldt and

Possingham, 1988; Alleweldt et al., 1990; Pierquet and Stushnoff, 1980; Seyedbagheri and Fallahi, 1994; Fennell, 2004).

Environment: Environmental factors include ambient temperature and day length, which affect grapevine FT. Both bud and cane tissues begin to increase FT when exposed to low air temperatures in the fall, and deacclimate in the spring. Dormant buds also have the ability to reacclimate when exposed to low temperature following a brief warm period, but vines cannot reacclimate after budburst (Stergios and Howell, 1977b). Microclimates also cause temperature variation within the same planting location. Temperatures are the lowest near the ground, and increase with higher elevation (Fennell, 2004; Zabadal et al.,

2004). Low elevation sites are more prone to winter damage than higher elevation sites, thus growers should establish vineyards in higher elevation and train vines on a high trellis system (1.5 to 2 meters). High light levels promote FT in both early acclimation period and midwinter. This is most likely due to high level light promote cane maturation during early acclimation period and increase level of carbohydrate storage during winter (Wolpert and Howell, 1986a; Hamman et al., 1996; Jones et al., 1999;

Stergios and Howell, 1977a; Fennell, 2004). Some reports also showed that short

daylength can contribute to early acclimation in some cultivars (Ahmedullah, 1985;

Wolpert and Howell, 1986b).

Cultural practices: The first consideration to protect vines from winter injury is to select an optimal site and select cultivars that are suited to the climatic conditions of the region

(Fennell, 2004). Other cultural practices factors that impact freezing injury include: training system, rootstock, irrigation and fertilization practices (Fennell, 2004).

1.2 Protection methods against freezing injury

Active and passive protection methods have been developed to mitigate the threat of freezing stress on grapevines, with the purpose of either changing the meso-climate condition in the vineyard or improving the FT of the grapevines themselves. Active protection methods include wind machines, heaters, and over-vine sprinkling (Poling,

2008). Passive methods include site and variety selection (Zabadal et al., 2007) and the application of chemical protectants (Dami and Beam, 2004). Among the chemical protectants, foliar applications of the plant growth regulator abscisic acid (ABA) has been found to increase FT in various crops, including rye (Secale cereale L.) (Churchill et al.,

1998), apple (Malus domestica L.) (Guak and Fuchigami 2001), and grape (Vitis spp)

(Zhang and Dami, 2012a; 2012b). Exogenous application of ABA to potted grapevines was found to induce growth recession, leaf abscission and periderm formation; these changes were associated with induction of dormancy and cold acclimation (Zhang et al.,

2011).

2. Freezing protection using ABA

2.1 Structure of ABA

Abscisic acid (ABA) is a terpenoid-derived compound with molecular formula of

C15H20O4 Figure 1.1). ABA has cis and trans isomers. Cis ABA is the biological active form. After exposure to ultraviolet light, cis ABA can convert active into inactive trans form (Cutler et al., 2010) (Figure 1.2).There are S and R type enantiomers of cis ABA, which are differentiated by rotation of functional group around an asymmetric carbon atom at position 1' (Figure 1.2). S- ABA is related to both fast response such as stomatal closure and slow responses such as seed maturation (Taiz and Zeiger, 2010). R-ABA is only responsible in long-term response, like seed maturation (Taiz and Zeiger, 2010).

Figure 1.1 Structure of Abscisic Acid (ABA)

Figure 1.2 Structures of (S)-cis-ABA, (R)-cis-ABA and (S)-2-trans-ABA (Taiz and

Zeiger, 2010)

2.2 ABA Metabolism

Almost all the cells in plants are capable of ABA synthesis (Milborrows, 2001). The biosynthesis pathway of ABA is plastidal 2-C-methyl-D-erythritol-4-phosphate (MEP)

terpere synthesis pathway (Milborrows, 2001) (Figure 1.3 B). Both fungi and higher plants can synthesize ABA through the general pathway shown in Figure 1.4 (Zeevaart,

1988). The precursor of ABA is the isopentenyl diphosphate (IPP) generated by the MEP pathway (Shimizu et al., 1998). Three molecules of IPP are xombined seauentially to synthesize 15- carbon farnesyl diphosphate (FPP) which is precursor of ABA and related to brassinosteroid synthesis (Sagami et al., 1993; Busquets et al., 2008). FPP can be converted to geranylgeranyl diphosphate (GGAPP), which is the precursor of GA biosynthesis (Sagami et al., 1993). In plants, ABA synthesis occurs primarily through the carotenoid pathway, which is indirect compared to other pathways found in some bacteria species, IPP is converted to violaxanthin, which is catalyzed by zeaxanthin epoxidase (ZEP), the enzyme encoded by the ABA1 locus of Arabidopsis (Xiong and

Zhu, 2003). Violaxanthin is then converted first to 9'-cis-neoxanthin (40-carbon compound), and then into the 15-carbon xanthoxal, a critical ABA precursor by 9-cis- epoxycarotenoid carotenoid dioxygenase (NCED) (Hansen and Crossmann, 2000; Taiz and Zeiger, 2010). NCED is a critical enzyme in ABA synthesis, which is rapidly induced by water stress, which suggests that NCED and its products play a key role in regulating ABA biosynthesis (Luchi et al., 2001). The xanthoxal is moved out from plastids to cytosol, and is converted by a series of oxidative steps to ABA, a process in which ABA-aldehyde is an important intermediate (Taiz and Zeiger, 2010). The conversion from ABA-aldehyde to ABA is catalyzed by abscisic aldehyde oxidases (Seo et al., 2004).

Figure 1.3 The ABA precursor IPP can be synthesized with plastids via the terpenoid pathway (B). (Dubey et al. 2003)

Figure 1.4 Biosynthesis pathway of abscisic acid (ABA) (Taiz and Zeiger, 2002)

2.3 Physiological functions of ABA

Water relations

It has been reported that ABA caused rapid closure of the stomata and ABA was the signal in the stomata regulation of water loss (Zeevaart et al., 1988). When plants are under water stress, ABA regulates stomata closure to reduce water loss from transpiration. Under water stress, ABA in the leaves can increase 50 fold within 4 to 8 hours (Zabadal, 1974).

Seed and bud dormancy

Seed dormancy: There are three stages in seed development: division and differentiation of tissue stop cell division and accumulate storage compound and seed dehydration (Taiz and Zeiger, 2010). The concentration of ABA changes during the three stages: seeds

ABA concentration starts at low level and reaches peak value during seed dehydration, and then decreases to low level when seeds reach maturation (Taiz and Zeiger, 2010).

This suggests that ABA plays a role in seed maturation and dormancy. ABA also regulates seed maturation and dormancy through inducing raffinose family oligosaccharide (RFO) accumulation during seed development, which is associated with desiccation tolerance (Lahuta et al., 2004; Blochl et al., 2005).

Bud dormancy: ABA concentration increases when the plant enters dormancy and reaches maximum concentration during the plant’s deepest dormancy stage (Cvikrova et al., 1994; Nagar, 1995; Nagar, 1996). It is reported that ABA induces the expression of an inhibitor for cyclin-dependent kinases (CDKs) which plays an important role in cell division (Demetric et al., 1994). This results in an interruption of cell division and leads to dormancy (Wang et al., 1998).

Leaf abscission and senescence

ABA has its name since people believed it contributed to leaf abscission initially.

However, it was confirmed that this only happened in a small amount of plants. But ABA has been reported to play a role in promoting leaf senescence. In light-incubated barley leaves (Hordeum vulgare L.), chlorophyll and carotenoids were promoted to break down with higher concentration of ABA and the leaf senescence rate increase with higher ABA concentration (Dent and Cowan, 1994). In my own research which tested ABA’s effect on FT of Pinot gris grapevines, the field observation showed ABA-treated grapevines exhibited early leaf abscission and senescence (Chapter 3).

Adaptation to drought, cold and salt stress

ABA has been called a stress hormone since it has played a central role in plants’ response to abiotic stresses, such as drought, cold, and salt. ABA affects plant to adapt to drought stress via water control via affecting stomata closure. During cold hardening, plants showed a rapid increase in ABA concentration (Chen et al. 1983), which suggests that ABA may be an endogenous regulator of adaptation to cold stress. My research purpose was to evaluate the effect of exogenous ABA on grapevines FT.

Literature Citation

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Alleweldt, G. and J.V. Possingham. 1988. Progress in grapevine breeding. Theor. Appl.

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Barka, E. A. and J. C. Audran .1997. Response of champenoise grapevine to low temperatures: Changes of shoot and bud proline concentrations in response to low temperatures and correlations with freezing tolerance. Journal of Horticultural Science

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Chapter 2: Evaluation of the Freezing Tolerance of Twenty three Winegrape Cultivars New to Ohio

Abstract

Grape and wine industries in colder regions have been expanding rapidly in recent years.

Unfortunately, the continued expansion of the grape industry is limited by geographical constraints that impose environmental stresses, primarily seasonal freezing temperatures.

Currently more than 80% of grape expansion in Ohio has been planted with cold- sensitive Vitis vinifera cultivars. These newly introduced Vitis vinifera cultivars are more susceptible to winter injury than their native counterparts. However, information on the freezing tolerance (FT) of Vitis vinifera cultivars is not available. The objectives of this research are to evaluate the FT of field-grown winegrape cultivars new to Ohio. FT (or

LT50) of 23 cultivars were evaluated between September and April in two locations for two seasons. Three different methods including date-mode method, piecewise regression and mean LT50s were used to estimate FT. We were able to classify the 23 cultivars into three groups of FT: most cold sensitive including Gamay noir, Pinotage, Rotberger,

Regent, Chardonnay, and Cabernet franc; least cold sensitive including Syrah, Lagrein,

Tempranilllo, Barbera, and Durif and the intermediate group which included Malvasia,

Dolcetto, Siegerrebe, Carménère, Cabernet Sauvignon, Sauvignon blanc, Malbec, Arneis,

Teroldego, Sangiovese, Merlot, and Kerner. The availability of these cultivars’ LT50 information will not only be of value to the academic world, but will also aid the nursery

industry and most importantly grape growers in selecting the best cultivars for their vineyards.

Introduction

Grapes are economically important crops grown throughout the world. Grapes and grape products, including wines, impact the American economy mostly in grape and wine sales, and tourism, whose revenues were more than $20 billion in 2007 (MKF Research LLC.

2007). The U.S. grape bearing acreage increased by 8% between 2002 and 2005, while wine market similarly increased in volume by 14% between 2002 and 2007 and by more than 15% in terms of revenue (MKF Research LLC. 2007). In particular, the grape and wine industries in cold regions have been expanding rapidly in recent years, despite the chanllenges associated with growing grapes in these regions. In the developing U.S. grape and wine industries, the grape growing acreage in northern latitudes increased by nearly 40%, and the economic value of grape production in these regions increased 18% between 2002 and 2005 (MKF Research LLC. 2007). Unfortunately, the continued expansion of the grape industry is limited by geographical constraints that impose environmental stresses, primarily seasonal freezing temperatures. In fact, Ohio experienced several major consecutive freezing-related grape losses throughout the last five years (Dami et al., 2014). In 2014 in particular, the polar vortex damaged 97% of vinifera cultivars, resulting in an average loss of $13,176 per acre (Dami and Lewis,

2014). Native American species, while cold hardy, are decreasing in demand in the U.S. winegrape market due to a consumer preference of Vitis vinifera wines. In contrast, Vitis vinifera can produce premium wines of commercial quality, they are desired by both market and grape and wine producers. Unfortunately, however, Vitis vinifera cultivars are

very sensitive to temperature below -20 °C and, as a result, are more sensitive to winter injury (Miller et al. 1988). Currently more than 80% of grape expansion in Ohio has been planted with cold-sensitive Vitis vinifera cultivars (Dami, personal communication).

These newly introduced Vitis vinifera cultivars are even more susceptible to winter injury than their native counterparts, which have traditionally been grown in these regions

(Zabadal et al. 2007).

Cold hardiness in grapevines is generally expressed by the freezing tolerance (FT) of primary buds since it reflects winter survival and future production potential (Gu et al.,

2001). Dormant buds of grapevine avoid freezing by a process known as supercooling

(Andrews et al., 1984). Supercooling is the ability of plant cells to retain cellular water in a liquid phase at subfreezing temperatures (Sakai and Larcher, 1987). The FT of grape buds that supercool can be detected and quantified using thermal analysis (TA) (Wolf and

Cook 1992). Grapevine FT is a highly dynamic condition, influenced by environmental conditions, grape genotypes, and cultural practices (Zabadal et al., 2007). One goal of our research was to characterize the impact of genotype on FT. Specifically, the objective of the three-year study presented here was to determine the FT of 23 winegrape cultivars grown at two different locations in Ohio.

Materials and Methods

Plant material and experimental design: Twenty two Vitis vinifera cultivars and

‘Regent’ (‘Diana’ × ‘Chambourcin’) grafted on rootstock ‘101-14 Mgt’ (V. riparia × V. rupestris) and ‘3309 Couderc’ (V. riparia × V. rupestris) were planted in 2008 at two research vineyards: the Horticulture Research Unit 2, Ohio Agriculture Research and

Development Center (OARDC) in Wooster, OH (Coordinates: 40.8° N, 81.9° W;

elevation: 304 m above sea level; Soil series: Riddles silt loams) and the Agriculture

Research and Development Center (OARDC)-Ashtabula Agricultural Research Station

(AARS) in Kingsville, OH (Coordinates: 41.8° N, 80.7° W; elevation: 240 m above sea level; Soil series: Habor fine sandy loam). Grape cultivars grown at the Wooster and

Kingsville locations are listed in Table 2.1. Vines were established on a randomized complete block of six blocks, with four-vine plots in each block. Vines were spaced 1.8

×2.7 m (vine × row) apart, and trained to a bilateral low cordon training system with vertical shoot positioning, and spur-pruned to 30 buds per vine. Side bird nettings were installed at véraison to protect the fruit from bird predation. Cluster and shoot thinning were conducted at the pea-size berry stage of development (EL stage 31) (Eichhorn and

Lorenz, 1977). Shoot thinning consisted of removing weak shoots, and cluster thinning consisted of removing clusters to achieve balanced vines with an optimum crop load

(crop weight to pruning weight) of five to 10. Leaf thinning was also conducted by removing the five leaves of each shoot on the east side (cool side) of the canopy for better spray penetration, air flow and sunlight exposure.

Weather data: Weather data (temperature, growing degree days (GDD), frost-free days

(FFD) and precipitation) were collected from the OARDC weather system website at: www.oardc.ohio-state.edu/newweather/stationinfo.asp?id=1. A temperature logger

(Model# A110, Watchdog A-Series, Spectrum Technologies, IL) was also installed as a back-up system at the Wooster research vineyard to collect hourly temperature.

Temperature data were downloaded monthly to the computer, and both the fall frost date and total number of FFD were determined from the temperature logger data.

Determination of bud FT: FT of bud were evaluated bi-weekly at the two locations for three dormant seasons (2011-2012, 2012-2013, and 2013-2014). During 2011-2012 seasons, cane samples were collected from 30 Sept 2011 to 14 Mar 2012 in Wooster and from 11 Oct 2011 to 26 Mar 2012 in Kingsville. During 2012-2013 seasons, cane samples were collected from 31 Aug 2012 to 21 Mar 2013 in Wooster and from 29 Oct

2012 to 01 Apr 2013 in Kingsville. One-year-old canes with seven basal buds (node positions three to nine) were collected from each replicate. Wooster cane samples were placed in a cooler with ice and brought to the lab immediately after sampling. Kingsville cane samples were placed in a cooler with ice and shipped overnight to the lab in

Wooster. Canes were stored at 4°C refrigerator for no longer than 48 hours prior to freezing tests. FT was determined by thermal analysis. For each cultivar, five buds from each cane were excised and placed on thermoelectric modules (MELCOR, Trenton, NJ), which were placed in a Tenney environmental chamber (Thermal Products Solutions,

New Columbia, PA). The chamber temperature was set to decrease at the rate of 4°C·h-1 from -2°C to -50°C. The FT of buds was determined by identifying the median or mean low temperature exotherm (LTE), which corresponds to the lethal temperature that kills

50% of the population, or LT50 (Wolf and Pool, 1987).

Statistical analyses: FT or LT50 was used as the response variable and cultivar as the predictor variable. Three statistical methods were used to evaluate the FT (LT50) of the different cultivars. The first method estimated the FT using a date-mode approach. This approach included the following steps:

 Calculation of the average LT50 across the four replicates within a sample date (by

year and cultivar);

 Determination of the date with the minimum average LT50 for each cultivar within

each study year;

 Examination of the dates across all cultivars to select the date that appeared most

frequently across the cultivars within each study year (mode date);

 Selection of the LT50 data for the mode date and comparison of the mean LT50s

used for that date among cultivars. These comparisons were done by fitting an

ANOVA model based on the following equation and using Tukey multiple

comparisons to compare the cultivars within years.

퐿푇50푖푗푘푙 = 휇 + 푌푖 + 푉푗 + 푉푌푖푗 + 퐷(푌)푘(푖) + 휀푖푗푘푙,

th th where LT50ijkl is the observed LT50 for the l replicate on the k date within year i for cultivar j,  is the overall mean LT50 across all replicates, dates, years and cultivars, Yi is an effect due to year i, Vj is an effect due to cultivar j, VYij is an interaction effect for year

th i and cultivar j, D(Y)k(i) is an effect due to the k date within year i, andijkl is an error associated with the lth replicate on the kth date within year i for cultivar j.

The second method used to estimate FT was based on fitting a piecewise linear regression model to the acclimation-steady state-deacclimation process. This model includes three segments that represents (1) acclimation, (2) mid-winter steady-state, and (3) deacclimation. The minimum LT50 temperature by cultivar was estimated using all observations collected during the mid-winter dormant period. The piecewise regression analysis was applied to each cultivar during each of the first two study years (the third study year did not have data for either the mid-winter or deacclimation periods) to estimate the dates at which the cultivar changed from fall acclimation to mid-winter periods and from mid-winter to deacclimation periods. All LT50 measurements collected

during the estimated dormant period were entered into an ANOVA model that estimated and compared the average minimum LT50 temperature for each cultivar within each study year as follows:

   1t, t  c1  LD50     1c1   2 (t  c1 ), c1  t  c2    c   (c  c )   (t  c ), t  c ,  1 1 2 2 1 3 2 2

Where c1 and c2 are the change-points marking the end of acclimation and start of deacclimation, respectively; t is the measurement time (number of days past a reference time);  is the LT50 at the reference time; 1 is the acclimation rate; 2 is the steady-state rate of change; and 3 is the deacclimation rate. These change-point estimates were used to identify all measurements taken during the steady-state period. An ANOVA model identical to that for the date-mode method, along with Tukey multiple comparisons, was used to compare minimum LT50 values among cultivars within each year. Only the mid- winter steady-state results are presented in this chapter.

The third method consisted of calculating the annual FT (or annual mean LT50) across each study year for each cultivar using a multifactor analysis-of-variance model and comparing the cultivars, years and dates using Tukey multiple comparisons.

All of the analyses were performed using SAS® statistical software Versions 9.3 and 9.4.

ANOVA was performed using PROC GLM, estimates of the minimum LT50 for the mode-date method were obtained using PROC GLM, and the estimates based on the piecewise linear regression were calculated using SAS® PROC NLIN (to perform the piecewise regression) and PROC GLM. Pearson correlation coefficients were computed

for six LT50 values (overall mean for 2 years, 2 study years of date-mode values, and 2 study years of piecewise values) to compare FT estimated from each of the three methods. Significance levels were set at  = 0.05.

Results

Weather:

Daily minimum and maximum air temperatures from August to April in each season are summarized in Figure 2.1. During the 2011-2012 dormant season, the first fall frost date occurred on 28 Oct. 2011 and the lowest temperature recorded at the Wooster research vineyard was -17.3 °C on 20 Jan. 2012 (Figure 2.1A). During the 2012-2013 dormant season, the first fall frost occurred on 11 Oct. 2012 and the lowest temperature was -12.7

°C on 3 Jan. 2013 (Figure 2.1B). During the 2013-2014 dormant season, the first fall frost occurred on 24 Oct. 2013 (Figure 2.1C). During the following January and February in

2014, the Wooster research vineyard experienced successive low temperatures which dropped below the critical temperature of -20°C five times and reached -24.6 °C on 28

Jan. Each year’s cumulative growing degree days (GDD) (from 1 Apr. to 30 Oct. at base

10 °C) and number of frost-free days (FFD) (consecutive days above 0 °C) are reported in Table 2.2 to express the growing season heat and duration, respectively. Each year’s monthly precipitation during growing season, yearly precipitation and cumulative precipitation during the growing season (1 Apr. to 30 Oct.) are also reported in Table 2.2.

GDD were 1652, 1687 and 1616 in 2011, 2012 and 2013, respectively; all were above the

30-year (1982-2011) average GDD of 1558 (Table 2.2). FFD were 206, 182 and 164 in

2011, 2012 and 2013, respectively (Table 2.2). Cumulative precipitations during growing seasons were 746, 498, and 575 mm in 2011, 2012 and 2013, respectively while the 30-y

average was 573 mm (Table 2.2). Annual precipitation was 1148, 750, and 926 in 2011,

2012 and 2013, respectively; the 30-y average was 868 mm (Table 2.2). The year 2012, was dry especially during Apr. to Aug. while 2011 was a wet year (Table 2.2).

Freezing tolerance:

Seasonal changes of FT: The FT for the 2011 – 2012 and 2012 – 2013 dormant seasons included observations from September through April, while the data for the 2013 – 2014 season only included observations from September through December. Thus, the results may not be completely comparable across the three years. The results of the ANOVA examining differences in LT50 by year, date, and cultivar showed that there were statistically significant differences ( = 0.05) for year, for the date within year, and for the cultivar. The profiles of bud FT of each cultivar followed similar patterns and can be divided into three stages consisting of fall cold acclimation (September to December), followed by maximum hardiness in mid-winter (January to mid-February) when LT50 remained fairly steady, and deacclimation in late winter and early spring. Figure 2.2 shows the LT50s of four cultivars determined over three years. LT50s started to decrease in late September and usually reached maximum FT in early December (Figure 2.2). The minimum LT50s remained relatively steady until February and then started to increase in early spring (Figure 2.2). The onset, rate, and duration of each stage of acclimation varied among cultivars. For example, Barbera LT50s dropped from mid-September (252 DOY,

LT50= -10.8 °C) to early December (339 DOY, LT50= -19.9 °C) (Figure 2.1A). Then the

LT50 remained relatively steady until mid-February (46 DOY, LT50= - 20.1 °C), ranging from -19.4 °C to - 21.4 °C, and then increased in early spring (38 DOY, LT50= - 17.1 °C)

(Figure 2.1A). Dolcetto LT50 reached a lower minimum than Barbera by 18 Dec (352

DOY, LT50= -21.4 °C), and remained steady through 4 Mar (63 DOY, LT50= -22.8 °C) before increasing (82 DOY, LT50= - 9.6 °C) (Figure 2.1B). Gamay noir LT50 decreased to the lowest level among all cultivars until 9 Dec (343 DOY, LT50= - 22.6 °C), remaining steady to 4 Mar (63 DOY, LT50= - 22.3 °C) and then increased to -13.0 °C on 23 Mar (82

DOY) (Figure 2.1C). FT in Regent followed a similar pattern as in Gamay noir by decreasing to LT50= -21.6 °C on 7 Dec (341 DOY), remained steady through 15 Feb. (46

DOY, LT50= - 22.3 °C) then increased to -12.2 °C on 23 Mar. (82 DOY) (Figure 2.1D).

The seasonal changes of FT of the other 19 cultivars are included in Appendix A.

Determination of minimum LT50 using date-mode method: The mode date for the minimum LT50 temperatures in the 2011 – 2012 study year was January 31, 2012, and this date was January 3, 2013 for the 2012 - 2013 study year. Table 2.3 shows the estimated minimum LT50s using date-mode method and the results should be viewed with caution because for several cultivars, the actual minimum observed LT50 occurred on a date other than the mode date. In particular, in the first study year, nearly as many cultivars had their minimum LT50 on 22 Jan. 2012 (7 cutivars) as on 31 Jan. 2012 (8 cultivars). Figure 2.3 shows the date-mode estimates of the minimum LT50s by cultivar within each study year, along with 95% Tukey-adjusted confidence intervals. In the first season (2011-2012), the range of the minimum LT50s was between -24.8 °C (Gamay noir) and -18.3 °C (Tempranillo), with a 6.5 °C difference (Table 2.3, Figure 2.3A).

Generally, a 3 °C difference of LT50 between two cultivars indicates statistically significant difference (Figure 2.3A). In the second season (2012-2013), the range of the minimum LT50s was between -24.4 °C (Gamay noir) and -16.6 °C (Durif) with a 7.8 °C difference (Table 2.3, Figure 2.3B).

Determination of minimum LT50 using piecewise regression: Table 2.3 shows the estimated minimum LT50s by year and cultivar using the piecewise regression approach.

For several cultivars, it was not possible to obtain estimates due to the absence of observations during the estimated mid-winter period either because no samples were collected or because the piecewise linear regression produced poor estimates of the change points. For example, in the 2012 – 2013 period, the plots of the LT50 values for

Chardonnay and Cabernet Franc had more of a “V” shape than a “U” shape, so the dormant period could not be identified. Figure 2.4 shows the piecewise estimates of the minimum LT50s by cultivar within each year. Figure 2.4 also shows intervals that incorporate Tukey multiple comparison critical values in such a way that there is an overall 95% confidence that all pairs of cultivars and years whose error bars do not overlap do, in fact, have different minimum LT50s. In the first season (2011-2012), the range of the minimum LT50s was between -23.3 °C (Gamay noir) and -18.3 °C (Durif) with a 5 °C difference (Table 2.3, Figure 2.4A). In the second season (2012-2013), the range of the minimum LT50s was between -23.2 °C (Gamay noir) and -16.0 °C (Durif) with a 7.2 °C difference (Table 2.3, Figure 2.4B). Generally, the variability of LT50 values within each cultivar was much smaller than with the date-mode method. In other words, the piecewise regression provides a better separation of LT50 means among cultivars. In most cases, a difference of 2 °C on LT50s indicates significant difference between two cultivars.

Annual freezing tolerance (annual mean LT50 ): Table 2.3 and Figure 2.5 show the annual mean LT50s of the 23 winegrapes cultivars across the whole dormant season. In the first season (2011-2012), the range of the annual mean LT50s was between -18.9 °C

(Gamay noir) and -14.8 °C (Barbera) with a difference of 4 °C (Table 2.3, Figure 2.5A).

In the second season (2012-2013), the range of the annual mean LT50s was between -19.1

°C (Gamay noir) and -14.2 °C (Durif) with a 4.9 °C difference (Table 2.3, Figure 2.5B).

The annual mean FT of each cultivar was also computed for two seasons (Figure 2.5C).

Gamay noir had the lowest annual mean LT50 (-19.1 °C) and Durif had the highest LT50

(-14.2 °C). This method also had the least LT50 variability within cultivars and statistical differences are detected at the 1 °C level (Figure 2.5C). The 2013 – 2014 year was omitted from this analysis because the data collected in that year were not comparable to the other years. In addition, mean LT50s could not be estimated for several cultivars that were either not measured in 2011-2012 or where the vines (Chardonnay, Cabernet franc,

Kerner, and Malbec) were too young to produce reasonable results. The 2-year mean

LT50 showed Gamay noir as the most cold hardy (annual mean LT50 = -19.0 °C) and

Barbera as the most cold sensitive (annual mean LT50 = -14.6 °C) (Figure 2.5C).

Correlation analysis: The correlation analyses among the three methods used to estimate

LT50 showed that, in general, cultivars were ranked similarly across the methods. Gamay noir, Rotberger, Pinotage, Siegerrebe, Regent, and Carmenere were usually among the cultivars with the lowest LT50 values, while Tempranillo, Lagrein, Arneis, Syrah,

Teroldego, Barbera, and Durif were usually among the cultivars with the highest LT50 values. Table 2.4 shows Pearson coefficients which, in general, indicate strong correlations between LT50 estimates among the three methods. All correlation coefficients are significant (p < 0.01). Furthermore, when comparing Figures 2.3 and 2.4, the error bars in the former are generally wider than those in the latter. This is primarily due to the fact that there are more observations used in the regression method (four

replicates across several sampling days), while there are only four replicates within a single day per cultivar in the date-mode method. As a result, few cultivars can be clearly distinguished using the mode method.

Winter injury in 2014: During Jan. 2012 and Jan. 2013, the mean LT50s of all Vitis vinifera culitvars ranged from -21.3 °C to -22.6 °C, which were both lower than air temperature. However, during Jan. and Feb. 2014, the lowest air temperature dropped below -20 °C five times: -24.1 °C on 7 Jan, -24.6 °C on 28 Jan,-20.1 °C on 7 Feb, -24.3

°C on 12 Feb, and -20.8 °C on 17 Feb. (Figure 2.1C). To evaluate the extent of bud and cane damage, ten canes with ten buds (node position one to 10) per cultivar were collected after the first freeze event (-24.6 °C) on 7 Jan. between 13 Jan. and 16 Jan.

Except for Cabernet sauvignon (98% mortality) and Gamay noir (99% mortality), all other cultivars suffered 100% primary bud mortality (Table 2.5). Cultivars showed differences in percent of cane damage. There was no cane damage in Barbera, Cabernet franc, and Regent while the damage percent in Arneis, Dolcetto, Durif and Malbec were

93%, 93%, 97% and 97%, respectively (Table 2.5).

Discussion

In this study, all winegrape cultivars’ LT50s profiles exhibited the typical U-shaped pattern of FT during the dormant season, which is consistent with previous studies on vine seasonal FT changes (Hamman et al. 1999, Jones et al. 1999, Zabadal et al. 2007,

Zhang and Dami 2012a,b).

Significant variation in FT was observed among the 23 winegrape cultivars. We used mode-date method and mean of observations in piecewise regression to estimate the minimum LT50 of each cultivar. Minimum LT50 is the most commonly used index to

estimate cultivar FT. A previous report divided Vitis vinifera cultivars into three classes based on minimum LT50 in mid-winter; very tender (LT50= -15 to -20.6 °C), tender

(LT50= -17.7 to -22.2 °C), and moderately tender (LT50= -20.6 to -23.3 °C) (Zabadal et al.

2007). Additionally, FT based on minimum LT50 has also been reported for several Vitis vinifera cultivars grown in Washington state including Cabernet Sauvignon, Malbec,

Merlot, Sangiovese, and Syrah (Mills et al. 2006, Ferguson et al. 2014). The minimum

LT50s of these cultivars ranged between -24 °C and -25 °C except for Sangiovese and

Merlot, which both had minimum LT50s of -22 °C (Mills et al. 2006, Ferguson et al.

2014). Further, Pool et al. (1990) reported the minimum LT50s of Cabernet franc (-26.6

°C), Merlot (-22.9 °C), Sauvignon blanc (-22.6 °C), and Siegrrebe (-25.4 °C) grown in

New York State. Our results are consistent with those from Washington and New York except the absolute values of LT50 were not identical among each cultivar. For example,

LT50 of Sauvignon blanc was -20.6 °C in Ohio, but -22.6 °C in New York. LT50 of

Siegrrebe was -21.5 °C in Ohio, but -25.4 °C in New York. This may be explained by different environmental condition and cultural practices (Zabadal et al., 2007).

Furthermore, the minimum LT50s were relatively higher in 2013 than in 2012. Even with the same cultivar, the LT50s varies with season, environment and cultural practices

(Zabadal et al. 2007). In this case, different growing and dormant seasons’ temperatures,

GDD, FFD, and precipitation affected the LT50 values of the same cultivars in different years. For example, in 2012, grapevines enjoyed a favorable growing season with a dry year and high GDD. These conditions are conducive for optimum fall cold acclimation and maximum FT in the winter. In 2012 and 2013, both seasons were characterized by

wet falls and low GDD, which are not ideal conditions for optimum fall acclimation and maximum hardiness in mid-winter (Zabadal et la. 2007).

Based on the mode-date method, cultivars can be divided into three groups according to each year’s minimum LT50: least sensitive (LT50 ≤ -23 °C); moderate (-23 °C < LT50 < -

21 °C); and most sensitive (LT50 ≥ -21 °C). During 2011-2012, the least sensitive group included: Gamay noir, Pinotage, Cabernet Sauvignon, Rotberger and Carménère; the most sensitive cultivars included: Sangiovese, Regent, Teroldego, Sauvignon blanc,

Lagrein, Merlot, Malbec, Barbera, and Tempranillo. The intermediate group with moderate FT included the remaining cultivars (Table 2.3, Figure 2.3A). During 2012-

2013, the least sensitive group included: Gamay noir, Chardonnay, Malvasia, Rotberger and Pinotage; the most sensitive cultivars included: Carménère, Cabernet Sauvignon,

Syrah, Tempranillo, Merlot, Kerner, Lagrein and Durif. Similarly, the intermediate group with moderate FT included the remaining cultivars (Table 2.3, Figure 2.3A). Based on the 2-year LT50 results, there were several cultivars which could be estimated consistently using the mode-date method. In this study, the least freezing sensitive (or most cold tolerant), among the 23 cultivars, consisted of Gamay noir (2-year minimum LT50 = -24.6

°C), Rotberger (-23.9 °C) and Pinotage (-22.3 °C). The most cold sensitive (or very tender) cultivars consisted of Tempranilllo (-18.9 °C), Lagrein (-19.1 °C), Barbera (-18.3

°C) and Durif (-18.3 °C).

Based on the piecewise regression method, we also divided cultivars into three groups: least sensitive (LT50 ≤ -23 °C); moderate (-23 °C < LT50 < -21 °C); and most sensitive

(LT50 ≥ -21 °C). Similar to the previous method, there were several cultivars which could be estimated consistently by both criterions and years using regression method. The least

sensitive cultivars were Gamay noir (2-year minimum LT50 = -23.3 °C), Pinotage (-22.7

°C) and Rotberger (-22.5 °C). The most sensitive cultivars were Lagrein (-19.4 °C),

Merlot (-19.3 °C), Barbera (-19.1 °C), Tempranilllo (-18.2 °C), and Durif (-17.2 °C). The

LT50s of the remaining cultivars fall in the intermediate group. Therefore, the mode-date and piecewise regression methods showed consistent conclusions in estimating the minimum LT50s, with Gamay noir, Pinotage, and Rotberger having high FT and Durif,

Tempranillo, and Lagrein having low FT. In general, the date-mode method provided lower estimates of the minimum LT50s because the data were selected so that the maximum numbers of cultivars were at their minimum LT50. However, the date-mode method (large error estimates) did not allow us to distinguish differences among cultivars as the piecewise regression method (small error estimates). Therefore, the piecewise regression method is a superior method to estimate LT50 than the conventional method.

In this study, we have proposed a third method to estimate FT, using a criterion that takes into accounts multiple measurement of LT50 throughout the whole dormant season. The new method agrees with the previous two as shown by the significant correlations coefficients (Table 2.4). Gamay noir, Pinotage and Rotberger had the lowest annual mean LT50s and Durif , Tempranillo and Lagrein had the highest annual mean LT50s.

Figure 2.5C summarizes the 2-year annual mean LT50 of each cultivar with Gamay noir being the least cold sensitive (-19.0 °C) and Barbera, the most cold sensitive (-15.2 °C).

In conclusion, based on the three methods used to estimate FT and our field assessments, we can cluster the 23 cultivars into three groups from the least (1) to the most (23) cold sensitive. Least cold sensitive cultivars were (1) Gamay noir, (2) Pinotage, (3) Rotberger,

(4) Regent, (5) Chardonnay, and (6) Cabernet franc. Moderately cold sensitive cultivars

were (7) Malvasia, (8) Dolcetto, (9) Siegerrebe, (10) Carménère, (11) Cabernet

Sauvignon, (12) Sauvignon blanc (13) Malbec, (14) Arneis, (15) Teroldego, (16)

Sangiovese, (17) Merlot, and (18) Kerner; Most cold sensitive cultivars were (19) Syrah,

(20) Lagrein, (21) Tempranilllo, (22) Durif, and (23) Barbera. Prior to this report, the information on FT (LT50) of the cultivars used in this study was not available in the literature. The findings of this study will not only be of value to the academic world, but will also aid the nursery industry and most importantly grape growers in selecting the best cultivars for their vineyards.

Literature Ciatation

Andrews, P. K., C. R. Sandidge, and T. K. Toyama. 1984. Deep supercooling of dormant and deacclimating Vitis buds. Amer. J. Enol. Viticult. 35: 175-177.

Dami, I, and D. Lewis. 2014. 2014 Grape Winter Damage Survey Report. Department of

Horticulture and Crop Science Series #816. The Ohio State University.

Dami, I.E., D. Kinney, and S. Li. 2014. Polar vortex and its impact on grapes. Ohio

Grape-Wine Electronic Newsletter. 10 Jan 2014 (Special Issue):2-6.

Eichhorn, K.W. and D.H. Lorenz. 1977. Phenological development stages of the grapevine. Nachrichtenbl. Dt. Pflanzenschutzd 29:119-120.

Ferguson, J. C., M. M. Moyer, L. J. Mills, G. Hoogenboom and M. Keller. 2014.

Modeling Dormant Bud Cold Hardiness and Budbreak in Twenty-Three Vitis Genotypes

Reveals Variation by Region of Origin. American Journal of Enology and Viticulture

65(1): 59-71.

Gu, S. L., S. F. Dong, J. Q. Li, and S. Howard. 2001. Acclimation and deacclimation of primary bud cold hardiness in 'Norton', 'Vignoles' and 'St. Vincent' grapevines. J. Hort.

Sci. Biotech. 76:655-660.

Hamman, R. A. and I. E. Dami .1999. Evaluation of 35 wine grape cultivars and

Chardonnay on 4 rootstocks grown in western Colorado

Jones, K., J. Paroschy, B. McKersie, and S. Bowley. 1999. Carbohydrate composition and freezing tolerance of canes and buds in Vitis vinifera. J. Plant Physiol. 155:101-106.

Miller, D.P., G.S. Howell, and R.K. Striegler. 1988. Cane and bud hardiness of selected grapevine rootstocks. Amer. J. Enol. Viticult. 39:55-59.

Mills, L. J., J. C. Ferguson and M. Keller. 2006. Cold-hardiness evaluation of grapevine buds and cane tissues. American Journal of Enology and Viticulture 57(2): 194-200.

MKF Research LLC. 2007. The impact of wine, grapes, and grape production on the

American economy 2007: family businesses building value. Helena, CA: MKF Research,

LLC.

Pool, R., G. Howard, R. Dunst , J. Dyson, T. Henick-Kling and J. Freer. 1990. Growing

Vitis vinifera grapes in New York State. I-Performance of new and interesting varieties.

NYS Agricultural Experiment Station : New York Wine and Grape Foundation.

Sakai, A. and W. Larcher. 1987. Frost Survival of Plants: Responses and Adaptation to

Freezing Stress. Vol.62. Springer-Verlag Berlin Heidelberg.

Wolf, T.K. and M. Cook. 1992. Seasonal deacclimation patterns of 3 grape cultivars at constant warm temperature. Am. J. Enol. Vitic. 43:171-179.

Wolf, T.K. and R.M. Pool. 1987. Factors affecting exotherm detection in the differential thermal analysis of grapevine dormant buds. J. Am. Soc. Hort. Sci. 112:520-525.

Zabadal,T., I. Dami, M. Goffinet, T. Martinson and M. Chien. 2007. Winter injury to grapevine and methods of protection. Michigan State University Extension, East Lansing,

MI.

Zhang, Y. and I. Dami. 2012a. Foliar application of abscisic acid increases freezing tolerance of field-grown Vitis vinifera ‘Cabernet franc’ grapevines. Am. J. Enol.

Viticult.63:377-384.

Zhang, Y. and I. Dami. 2012b. Improving freezing tolerance of ‘Chambourcin’grapevines with exogenous abscisic acid. HortScience, 47: 1750-1757.

Table 2.1. Description of winegrape cultivars planted at the Wooster and Kingsville research vineyards.

Planting location Cultivar Origin Colorz Clone Rootstocky Wooster Kingsville (OARDC ) (AARS) FPS Albariño Spain White 101-14 × 01x Arneis Italy White FPS 01 101-14 × × Barbera Italy Red FPS 06 101-14 × Red FPS 01 101-14 × Cabernet franc France Red FPS 11 101-14 × Cabernet Sauvignon France Red FPS 08 101-14 × Carménère France Red FPS 03 101-14 × Chardonnay France White FPS 37 101-14 × × Dolcetto Italy Red FPS 01 101-14 × × Durif (Petite Sirah) France Red FPS 03 101-14 × × Gamay noir France Red FPS 05 101-14 × × Grüner Veltliner Austria White FPS 01 101-14 × Kerner Germany White FPS 01 101-14 × × Lagrein Italy Red FPS 03 101-14 × Malbec France Red FPS 09 101-14 × Malvasia bianca Italy White FPS 03 101-14 × Merlot France Red FPS 03 101-14 × Petit Manseng France White 101-14 × Pinot noir France Red FPS 13 101-14 × Pinotage South Africa Red FPS 01 101-14 × × Pinot noir précoce France Red 101-14 × Refosco Italy Red FPS 03 101-14 × Regent Germany Red 101-14 × × Rotberger Germany Red 101-14 × Red FPS 10 101-14 × Sangiovese Italy Red FPS 14 101-14 × Sauvignon blanc France White FPS 14 101-14 × × Sauvignon gris France White FPS 01 101-14 × Siegerrebe Germany White FPS 02 101-14 × × Syrah France Red FPS 07 101-14 × Tempranillo Spain Red FPS 06 101-14 × × Teroldego Italy Red FPS 02 101-14 × × Tocai Friulano Italy White FPS 01 C-3309 × zColor: Primary wine use. yRootstock: V. riparia × V. rupestris. xFPS: Foundation Plant Services, Davis, CA.

Table 2.2. Growing degree days (GDD), frost-free days (FFD), and precipitation relative to the phenology of Vitis Vinifera grapevines grown in the research vineyard in Wooster, OH.

Annual Monthly Precipitation (mm) Total precipitation during growing Year GDDz FFDy Precipitation season (Apr.-Oct.) (mm) Apr. May June July Aug. Sep. Oct. (mm) 2011 1652 206 116 185 79 75 93 104 94 746 1148 2012 1687 182 36 56 56 59 57 125 109 498 750 2013 1616 164 104 52 128 168 50 74 93 669 926 30-year Average 1558 164 77 97 91 92 83 71 64 575 868 (1982-2011) z GDD: cumulative daily mean temperatures with base 10 °C from 1 Apr. through 31 Oct. y FFD: successive days with minimum daily temperatures at or above 0 °C.

Table 2.3. Estimated minimum LT50 using mode-date-method, mean of observations in piecewise regression, and annual mean LT50 by cultivar. LT50s are listed from lowest to highest. z Mode-Date Method Piecewise Regression Method Annual Mean LT50 31 Jan. 2012 3 Jan. 2013 2011-2012 2012-2013 2011-2012 2012-2013

Cultivar LT50 Cultivar LT50 Cultivar LT50 Cultivar LT50 Cultivar LT50 Cultivar LT50 Gamay noir -24.8 Gamay noir -24.4 Gamay noir -23.3 Gamay noir -23.2 Gamay noir -18.9 Gamay noir -19.1 Pinotage -24.4 Chardonnay -24.3 Pinotage -23.1 Rotberger -23.0 Pinotage -18.5 Pinotage -18.5 Cab. Sauv. -23.5 Malvesia -24.2 Carménère -22.6 Dolcetto -22.6 Rotberger -18.4 Regent -18.3 Rotberger -23.3 Rotberger -24.5 Siegerrebe -22.1 Pinotage -22.3 Cab. Sauv. -17.8 Chardonnay -18.2 Carménère -23.2 Pinotage -23.0 Malvasia -22.0 Malbec -22.1 Carménère -17.7 Malvasia -18.2 Dolcetto -22.7 Dolcetto -22.9 Rotberger -22.0 Malvasia -21.2 Siegerrebe -17.6 Rotberger -18.1 Arneis -22.7 Cab. franc -22.9 Syrah -21.9 Carménère -20.5 Arneis -17.4 Sauv. blanc -18.0 Malvesia -22.3 Regent -22.6 Dolcetto -21.5 Siegerrebe -20.2 Malvasia -17.3 Siegerrebe -17.8

43 Syrah -22.2 Malbec -22.1 Regent -21.2 Cab. Sauv. -20.0 Regent -17.2 Carménère -16.9

Durif -21.6 Siegerrebe -22.1 Teroldego -20.6 Regent -19.6 Dolcetto -16.8 Cab Sauv -16.7 Siegerrebe -21.4 Sauv. B. -21.9 Cab. Sauv. -20.6 Syrah -19.5 Syrah -16.6 Cab. franc -16.7 Sangiovese -20.4 Arneis -21.6 Sangiovese -20.4 Barbera -19.3 Durif -16.5 Malbec -16.7 Regent -20.3 Barbera -21.5 Sauv B. -20.0 Merlot -19.3 Sauv. blanc -16.3 Kerner -16.4 Teroldego -19.8 Teroldego -21.2 Lagrein -19.9 Lagrein -18.8 Merlot -16.3 Merlot -16.4 Sauv. B. -19.8 Sangiovese -21.1 Merlot -19.3 Kerner -18.8 Tempranillo -16.2 Teroldego -16.3 Lagrein -19.6 Carménère -20.7 Tempranillo -19.3 Teroldego -17.9 Teroldego -16.2 Dolcetto -16.2 Merlot -18.8 Cab. Sauv. -20.2 Barbera -18.8 Tempranillo -17.1 Sangiovese -16.2 Sangiovese -16.1 Barbera -18.5 Syrah -19.7 Durif -18.3 Arneis -16.7 Lagrein -15.9 Arneis -15.8 Tempranillo -18.3 Tempranillo -19.5 Durif -16.0 Barbera -14.8 Syrah -15.6

Merlot -19.5 Lagrein -15.5

Kerner -19.1 Barbera -15.4

Lagrein -18.6 Tempranillo -15.3

Durif -16.6 Durif -14.2

Table 2.4. Correlations coefficients between annual mean freezing tolerance, date-mode, and piecewise regression method for two seasons (2011, and 2012).

Annual Annual mean Date-Mode Date-Mode Piecewise 2011 Piecewise 2012 mean 2011 2012 2011 2012 Annual mean 2011 1 0.695** 0.820** 0.526** 0.473** 0.579** Annual mean 2012 1 0.731** 0.709** 0.805** 0.740**

Date-Mode 2011 1 0.680** 0.658** 0.634**

Date-Mode 2012 1 0.641** 0.795**

Piecewise 2011 1 0.685**

Piecewise 2012 1 ** indicates significance at the 0.01 level.

Table 2.5. Bud and cane phloem mortality of 23 winegrape cultivars planted in Wooster research field after a freeze event (- 24.6°C) on 7 Jan. 2014. Bud damage (%) Cultivar Primary bud Secondary bud Tertiary bud Cane phloem damage (%) Arneis 100 100 98 93 Barbera 100 100 99 0 Cabernet Franc 100 100 100 0 Cabernet Sauvignon 98 96 96 47 Carménère 100 100 100 60 Chardonnay 100 99 99 23 Dolcetto 100 100 100 93 Durif 100 100 100 97 Gamay noir 99 96 94 10 Kerner 100 100 100 17

45 Lagrein 100 100 100 23

Malbec 100 100 100 97 Malvasia bianca 100 100 100 80 Merlot 100 100 100 83 Pinotage 100 98 97 3 Regent 100 99 93 0 Rotberger 100 100 99 53 Sangiovese 100 100 99 80 Sauvignon blanc 100 100 100 57 Siegerrebe 100 100 99 3 Syrah 100 100 99 60

Max air temp(°C) A 30 Min air temp(°C)

C) ° 10

0 Temperature ( Temperature

46 -10

FF (28-Oct-11): -0.8°C

-20

-30

Date

Continued

Figure 2.1. Daily minimum and maximum temperatures and dates of fall frost (FF) recorded at Wooster research vineyard during: A) 2011-2012; B) 2012-2013 and C) 2013-2014.

Figure 2.1. continued 40 B Max air temp(°C) 30 Min air temp(°C)

C) ° 10

0 Temperature ( Temperature

-10 FF (11-Oct-12): -0.8°C

-20

-30

Date

continued

Figure 2.1. continued 40.0

Max air temp(°C) C 30.0 Min air temp(°C)

20.0

C) ° 10.0

0.0 Temperature ( Temperature

-10.0

-20.0

-30.0

Date

A B

0 2 0 y = 0.0218x - 1.0098x - 6.0793 y = 0.0274x2 - 1.3637x - 3.0773 R² = 0.6446 A R² = 0.7761 B

-5 C -5

-10 -10

(

50 LT LT -15 -15

-20 -20

-25 -25 252 284 301 327 352 31 73 252 284 301 327 352 31 73 Day of year (DOY) Day of year (DOY)

-5 2 0 y = 0.0308x - 1.3796x - 6.6151 y = 0.0335x2 - 1.3945x - 6.1663 R² = 0.7785 C R² = 0.7209 D -10 -5

-15

C) -10

(

50 LT

-20 LT -15

-25 -20

-30 -25 252 284 301 327 352 31 73 252 284 301 327 352 31 73 Day of year (DOY) Day of year (DOY)

Figure 2.2. Combined LT50s of A) Barbera B) Dolcetto C) Gamay noir and D) Regent in Wooster research vineyard for the three years by day of year. ● represent the LT50s collected in 2011-2012 season; ○ represent the LT50s collected in 2012-2013 season; represent the LT50s collected in 2013-2014 season. Lines are order two polynomial trendlines.

-10 -12 A -14

-16

° (

-18 50

-20

-22

MinimumLT -24

-26

-28

-30

Cultivars

-10 -12 B -14

-16

° (

-18 50

-20

-22

MinimumLT -24

-26

-28

-30

Cultivars Figure 2.3. Estimated minimum LT50s of winegrape cultivars planted in Wooster research vineyard using date-mode method by year: A) 2011-2012 (estimated date: 31 Jan. 2012) and B) 2012-2013 (estimated date: 3 Jan. 2013).

-10 -12 A -14

-16

° (

-18 50

-20

-22

MinimumLT -24

-26

-28

-30

Cultivars

-10 -12 B

-14

C) -16

(

50 -18

-20

-22

-24 MinimumLT

-26

-28

-30

Cultivars

Figure 2.4. Estimated minimum LT50s of winegrape cultivars planted in Wooster research vineyard using piecewise regression by year: A) 2011-2012 and B) 2012-2013.

-13

-14 A C)

° -15 -16 -17 -18 Mean LT50 MeanLT50 ( -19 -20

Cultivars

-13 B

-14 C) ° -15 -16 -17 -18

Mean LT50 MeanLT50 ( -19 -20

Cultivars

-13

-14 C

C) -15 ° -16

-17

-18 Mean LT50 MeanLT50 ( -19

-20

Cultivars

Figure 2.5. Annual mean LT50 of winegrape cultivars planted in Wooster research vineyard during A) 2011-2012; B) 2012-2013 and C) average of 2011-2012 and 2012- 2013 seasons.

Chapter 3: Improving Freezing Tolerance of Cold-Sensitive Grape Cultivars Using Exogenous Abscisic Acid

Abstract

Economic losses due to cold weather events are a major constraint to the expansion of premium but cold sensitive winegrape cultivars in colder regions, such as Ohio. The purpose of this study was to determine whether a foliar application of abscisic acid

(ABA) could increase the freezing tolerance (FT) of field-grown, ‘Chardonnay’ and

‘Pinot gris’ grapevines (Vitis vinifera), and whether the effectiveness of ABA treatments can be influenced by the phenological timing of the application. Mature, ‘Chardonnay’ and ‘Pinot gris’ grapevines were treated with a foliar application of ABA at a concentration of 0 mg·L-1 (control), or 400 mg·L-1 at vine phenological stages corresponding to véraison, post-véraison, and post-harvest. ABA application did not affect yield components or fruit composition, but caused early leaf senescence, leaf abscission, and advanced dormancy that led to increased FT of ‘Pinot gris’ and

‘Chardonnay’ during the dormant season. The phenological timing of application influenced ABA effectiveness. In both cultivars, spray applications made at véraison and post-véraison were the most effective. We conclude that a foliar application of ABA increased bud FT during the dormant season and thus ABA is a potential cultural practice for mitigating economic losses from cold injury in production regions with damaging cold events.

Introduction

Winegrape production regions in the northern U.S.A. have experienced substantial economic losses in production due to cold weather events in 2003, 2004, 2005, 2009,

2012, and 2014 (Zabadal et al., 2007; Dami et al. 2012; Dami et al. 2014). The state of

Ohio has experienced consecutive years of freezing-related loss of grape production for the last five years, with the greatest loss occurring in 2014 (Dami et al., 2014; Dami and

Lewis, 2014). Expansion of grape acreage, production sustainability, and the success of wine-related industries in production regions that experience winter cold are threatened by the frequent occurrence of cold weather events. In order to mitigate the threat of cold damage in grapes, active and passive protection methods have been developed, with the purpose of either changing the meso-climate condition in the vineyard or improving the

FT of grapevines. Active protection methods include wind machines, heaters, and over- vine sprinkling (Poling, 2008). Passive methods include site and variety selection

(Zabadal et al., 2007) and the application of chemical protectants (Dami and Beam,

2004). Among the chemical protectants, foliar applications of the plant growth regulator

ABA have been found to increase FT in various crops including rye (Secale cereale L.)

(Churchill et al., 1998), apple (Malus domestica L.) (Guak and Fuchigami 2001), and grape (Vitis spp) (Zhang and Dami, 2012a; 2012b). Exogenous application of ABA to potted grapevines was found to induce growth recession, leaf abscission and periderm formation, changes associated with induction of dormancy and cold acclimation (Zhang et al., 2011). The cultivars ‘Chardonnay’ and ‘Pinot gris’ are moderately cold sensitive

cultivars of V. vinifera that are widely planted in winegrape production regions where winter weather events commonly cause cold injury. The purpose of this study was to investigate whether a foliar application of ABA and the phenological timing of this application could enhance the FT of ‘Chardonnay’ and ‘Pinot gris’ without adversely affecting yield or berry composition. We hypothesized that the effectiveness of foliar

ABA to increase FT would be influenced by the phenological stage of the vine at the time of the foliar application and that exogenous ABA would not adversely influence yield or berry composition. We investigated these hypotheses by applying exogenous ABA to the canopy of field-grown ‘Chardonnay’ and ‘Pinot gris’ grapevines at three stages of berry development in field trial sites located in Ohio.

Materials and Methods

Plant material, experimental design, and treatments:

The field study was conducted at two locations in northeast Ohio: Ashtabula Agricultural

Research Station (AARS), in Kingsville, and at Meineke Cellars Vineyard in Geneva,

Ohio. Vitis vinifera ‘Pinot gris’ were planted at AARS and vines were spaced 1.5 ×2.4 m (vine × row). Vitis vinifera ‘Chardonnay’ were spaced 0.9 ×2.7 m (vine × row). Both cultivars were trained to a bilateral low cordon training system with upward shoot positioning, and spur-pruned to 15 buds/m of cordon. Treatments were applied on vines using a randomized complete block with five blocks and four treatments each consisting of 10-vine plots. In each block, all treatments were bordered by untreated vines. The four treatments consisted of the following: 1) control (no ABA), 2) ABA at véraison (50% berry color change and softening), 3) ABA at post-véraison (two to three weeks after véraison), and 4) ABA at post-harvest (six to eight weeks after véraison). ABA and

control (no ABA) foliar spray solutions were prepared using deionized water and the surfactant Latron B-1956 ® at 0.05% (v/v). The ABA solutions, containing 400 mg∙L-1

(‘Pinot gris’ and ‘Chardonnay’ in year 1) and 500 mg·L-1 (‘Chardonnay’ in year 2), were prepared using Protone® SG (Valent BioSciences Corporation, Libertyville, IL) which contains 20.0% (w/w) s-ABA as the active ingredient. The sprays were applied on both sides of the vine canopy (leaves and clusters) to runoff using a backpack sprayer that averaged a spray volume of 0.5 L per vine. The experiments were repeated for two growing seasons (2012 and 2013) in both vineyard sites.

Leaf senescence and abscission:

In 2012, leaf senescence was visually observed and photos were taken of all treatments.

Leaf abscission was determined by counting leaves per shoot pre- and post-ABA application and calculating the percentage of leaf abscission. In 2013, leaf senescence was monitored by measuring chlorophyll using SPAD-520 chlorophyll meter (Spectrum

Technologies, Inc. East - Plainfield, IL). One to four shoots were randomly tagged per treatment-replicate and chlorophyll measurements were recorded bi-weekly on the upper surface of the basal four leaves (node position 4, 5, 6, 7). Leaf abscission was also recorded at the same time and on the same shoots as described above.

Yield components, fruit composition, and pruning weight:

Yield components consisted of crop weight per vine, cluster number per vine, and cluster weight. A 100-berry weight was measured and the berry number per cluster was calculated based on cluster weight divided by 100-berry weight and then multiplied by

100. In both 2012 and 2013, a 100-berry sample was collected at harvest for fruit composition analysis. This analysis included the determination of total soluble solids

(TSS), titratable acidity (TA), and pH. Berries were weighed using an electronic scale

(Denver Instrument, Bohemia, NY), and then the berry samples were juiced at room temperature. The juice was then transferred to a 50 mL centrifuge tube and centrifuged at

8500 rpm for 5 min (accuSpin 400, Fisher Scientific, Pittsburgh, PA). A 10-mL supernatant was transferred to the titration work station (PH/EP Titration Workstation

Model 350/352) with SAC80 Sample change, (Denver Instrument, Bihemia, NY) to measure pH and TA. TA was determined by titrating a 10-mL aliquot of juice sample to a pH 8.2 with 0.1 N NaOH solutions. Total soluble solids were measured with a digital refractometer (MISCO, Cleveland, OH) and expressed in degree Brix (Zhang et al. 2011).

In March, 2013, ‘Pinot gris’ and ‘Chardonnay’ vines were spur-pruned to retain 15 buds/m of cordon. All one-year-old canes were weighed for each vine after pruning. In

March, 2014, canes of ‘Pinot gris’ vines were pruned back to the cordons due to the extensive winter damage that occurred in January, 2014. Pruning weight estimates vine size and is a measure of vine growth.

Bud dormancy:

Dormancy assays were only conducted in ‘Pinot gris’. Bud samples were collected monthly from 31Aug, 2012 to 21 Mar, 2013 in the 2012-2013 season and from 06 Sep,

2013 to 21 Nov, 2013 in the 2013-2014 season. All dormancy assays were conducted on the same day of sample collection and followed the method reported by Zhang and Dami

(2011). Three canes with 8 basal buds per replicate (node position three to10), 18 node cuttings were used for each replicate. Canes with visible periderm formation were excised into one-node cuttings ~5 cm long, then inserted into 2.5 cm×2.5 cm foam medium (Smithers-Oasis, Kent, OH) and placed in 55 cm× 25 cm×7 cm plastic trays

(T.O. Plastics, Clearwater, MN) filled with deinonized water. Trays were then placed in a growth chamber (Conviron, Pembina, ND) with the following settings: 12-h photoperiod with 300 µmol·m-2·s -1, 22°C, and 88% relative humidity (Zhang and Dami,

2012a). Budburst was recorded three times a week as EL stage 5 (Eichhorn and Lorenz,

1977). Dormancy results were estimated as the number of days to 50% budburst

(D50BB), with higher values of D50BB indicating more dormant buds (Wake and

Fennell, 2000).

Water content:

Water contents in buds and leaves were measured in ‘Pinot gris’ grown in Kingsville. In the 2012-2013 season, one representative cane was collected from each treatment- replicate from 31 Aug, 2012 to 21 Mar, 2013. Leaf samples were collected from 31 Aug,

2012 to 11 Nov, 2012. In the 2013-2014 season, leaf samples were not collected due to extensive chemical damage experienced by the vines, and bud samples were collected monthly from 06 Sep, 2013 to 21 Nov, 2013. The selection criteria were the same as for bud dormancy assay. Leaf samples were weighed immediately after collection. Buds on node positions three to seven of each shoot were excised and weighed immediately after collection. Leaf and bud samples were placed in an oven at 70°C for a week, and then measured the dry weights of leaf and bud samples. Water content was expressed as percent of fresh weight.

Freezing tolerance:

One-year-old canes with seven basal buds (node positions three to nine) were collected from each replicate. The canes were placed in coolers with ice and shipped overnight to the laboratory in Wooster. Canes were stored in 4°C refrigerator for no longer than 48

hours prior to conducting freezing test. FT was determined by thermal analysis. Briefly, buds were excised and placed on thermoelectric modules (MELCOR, Trenton, NJ), which were placed in a Tenney environmental chamber (Thermal Products Solutions,

New Columbia, PA). The chamber temperature was lowered from -2°C to -50°C at the rate of 4°C·h-1. The FT of buds was determined by identifying the median or mean low temperature exotherm (LTE), which corresponds to the lethal temperature that kills 50% of the population, or LT50 (Wolf and Pool, 1987). ‘Pinot gris’cane was collected at the same times as samples used to determine bud dormancy and water content from 31 Aug,

2012 to 21 Mar, 2013 in the 2012-2013 season and from 06 Sep, 2013 to 21 Nov, 2013 in the 2013-2014 season. ’Chardonnay’ cane samples were collected from 31 Aug, 2012 to

21 Mar, 2013 in the 2012-2013 season and from 04 Oct, 2013 to 21 Nov, 2013 in the

2013-2014 season.

On 7 Jan. 2014, both Kingsville and Geneva experienced sub-freezing events when air temperature dropped to -25.3 °C and -23.9 °C, respectively. Theses temperatures were lower than the LT50s of ‘Pinot gris’ (-21.3 °C) and ‘Chardonnay’ (-19.3 °C) measured on 25 Nov. 2013. On 13 Jan. 2014, ten canes with ten buds (node position one to 10) per cane were collected from each field and stored for 24h at room temperature. Buds were excised using razor blades to visually assess the viability of primary, secondary, and tertiary buds and cane phloem tissue. If the tissues were green, they were alive while brown ones were injured (Dami et al., 2012). Winter injury was expressed as a percentage by dividing the number of damaged buds or canes with dead tissue by the sample size and multiplying by 100.

Field budburst:

After pruning in 2013, the total number of buds per vine were counted and recorded.

Budburst measurements were made by counting buds at the E-L (Eichhorn and Lorenz,

1977) stage five and monitoring three times a week until 80% or more of buds burst.

Weather data:

Temperature data in the ‘Pinot gris’ vineyard was collected by the weather station at the

AARS in Kingsville (www.oardc.ohio state.edu/newweather/stationinfo.asp?id=4). A temperature logger (Model# A110, Watchdog A-Series, Spectrum Technologies, IL) with a shield was installed in the commercial ‘Chardonnay’ vineyard. The hourly temperature data were downloaded monthly to a laptop and presented as daily minimum and maximum temperatures.

Statistical analysis:

All data were subjected to analysis of variance using SAS statistical software (version

9.3; SAS Institute, Cary, NC). When treatments were significantly different, an LSD test was used for mean comparisons at p ≤0.05, ≤0.01, ≤0.001.

Results

ABA application dates and corresponding weather and phenology:

ABA application dates and their corresponding growing degree days (GDD) and vine phenological stages are summarized in Table 3.1. Days after budburst (DAB) were also computed to evaluate their association with vine phenological stages (Table 3.1).

Cumulative growing degree days, computed from 1 Apr. to 31 Oct. at base 10 °C indicates the growing season heat. Frost-free days (consecutive days above 0 °C) were recorded to indicate the growing season duration. ‘Pinot gris’ grapes were harvested on

19 Sept. 2012 and 24 Sept. 2013 (Table 3.1). ‘Chardonnay’ grapes were harvested on 24

Sept. 2012 and 30 Sept. 2013 (Table 3.1).

Leaf senescence and abscission:

‘Pinot gris’: In 2012, ABA-treated ‘Pinot gris’ grapevines grown in Kingsville began to exhibit changes in leaf color one week after each ABA application and application time showed different level of color change and leaf abscission. On 9 Oct, ABA-treated grapevines changed their color from green to yellow with increased intensity from véraison to post-harvest (Figure 3.1A). After eight days, control leaves were still green while post-harvest leaves were completly abscised (Figure 3.1B). In 2012, post-harvest treated-vines exhibited earlyier defoliation and an increased percentage of abscised leaves compared to other three treatments (Figure 3.2A). In 2013, ABA application at véraison on 21 Aug. 2013 increased leaf abscission from 6% to 33% within 16 days as compared to control (15%) (Figure 3.2B). ABA application at post-véraison on 17 Sept. 2013 increased leaf abscission from 17% to 90% within 18 days while control remained at 15%

(Figure 3.2B). Post-harvest ABA application on 17 Oct. 2013 increased leaf abscission from 32% to100% within one month, while control was at 39% (Figure 3.2B). In 2013, leaf senescence of ‘Pinot gris’was also monitored based on chlorophyll content which continuously declined from September to October in both control and ABA-treated leaves from 35.9 to 18.2 and 31.1 to17.1, respectively. Between 18 Sept. 2013 and 11

Oct. 2013, the chlorophyll content of ABA-treated vines dropped more rapidly than in control vines (Figure 3.3). At the end of October, both control and ABA-treated leaves reached a similar low level of about 18.

‘Chardonnay’: In 2012, leaf color of post-harvest treated ‘Chardonnay’ grapevines changed from green to yellow within one week after ABA application (Figure 3.4).

Véraison and post-véraison changed to light yellow and the later ABA application the more color change was observed (Figure 3.4). Control leaves remained green at the same time (Figure 3.4). Defoliation of post-harvest ABA-treated grapevines occured two weeks earlier than control and showed the earliest leaf abscission among all treatments (Figure

3.4).Leaf abscission percent within three days (from 20 Oct. 2013 to 23 Oct. 2013) among control, véraison, post-véraison and post-harvest were 10%, 12%, 16% and 58%, respectively and the leaf abscission percentage of post-harvest showed significant difference compared to the other three (data not shown).

Yield components and fruit composition:

‘Pinot gris’: In both years, ABA did not affect yield components or the basic fruit chemical composition of ‘Pinot gris’ grapevines. In 2012, the cluster number per vine was maintained between 30 and 33 (Table 3.2). The ranges of cluster weight, berries per cluster, berry weight, yield per vine and Ravaz index were 91 to 100 g, 55 to 63, 1.55 to

1.66 g, 2.70 to 3.13 kg, and 4.2 to 5.9 respectively (Table 3.2). There were also no differences in TSS (ranged from 23.2 to 23.5 °Brix), pH (ranged from 3.50 to 3.59), or titratable acidity (TA) (ranged from 6.5 to 6.6 g·L-1) among treatments (Table 3.2). In

2013, the cluster number per vine remained between 24 and 27 (Table 3.2). The ranges of cluster weight, berries per cluster, berry weight, yield per vine, and Ravaz index were 109 to 122 g, 72 to 80, 1.47 to 1.58 g, 2.62 to 3.17 kg, and 5.0 to 6.4 respectively (Table 3.2).

There were also no differences of TSS (ranged from 19.4 to 19.8 °Brix), pH (ranged from

3.39 to 3.51), or TA (ranged from 5.9 to 6.6 g·L -1) among treatments (Table 3.2).

‘Chardonnay’: In the Geneva field, we only measured the yield components and fruit composition of ‘Chardonnay’ were measured in 2013 but not in 2012, due to inadvertent harvest of the experimental plots by the cooperating grower. The cluster number per vine was maintained between 36 and 40 (Table 3.3). The ranges of cluster weight, berries per cluster,berry weight, and yield per vine were 95 to 109 g, 61 to 74, 1.47 to 1.58 g and

3.63 to 3.86 kg, respectively (Table 3.3).There were no differences among treatments in any yield component and there were no differences of TSS (ranged from 17.2 to 18.1

°Brix), pH (ranged from 3.45 to 3.58), or TA (ranged from 8.1 to 9.3 g·L-1) among treatments (Table 3.3).

Vegetative growth and phytotoxicity:

‘Pinot gris’: In 2013, there were no ABA treatment effects on vine pruning weight as an indicator of vegetative growth in ‘Pinot gris’. The mean pruning weight of control was

0.53 kg (Table 3.2). The means of three ABA-treated grapevines were 0.65 kg, 0.62 kg,

0.62 kg, respectively (Table 3.2). The Ravaz index of four treatments ranged from 4.2 to

5.9 without significant difference (Table 3.2). In 2014, no difference of pruning weight and vine size among treatments was observed and measured in the ‘Pinot gris’ grown in

Kingsville. Prunings were conducted on 27 Mar. 2014 and the means of pruning weight of control, véraison, post-véraison and post-harvest were 0.59 kg, 0.64 kg, 0.50 kg and

0.50 kg, respectively without significant difference (Table 3.2). The Ravaz index of four treatments was ranged from 5.0 to 6.4 without significant difference (Table 3.2).

‘Chardonnay’: In 2013, there were no ABA treatment effects on vine pruning weight in

‘Chardonnay’. The means of pruning weight of controls was 0.35 kg (Table 3.3). The

means of the three ABA-treated grapevines were 0.26 kg, 0.31 kg, 0.33 kg, respectively

(Table 3.3).

No symptoms of phytotoxicity were observed on leaves after ABA treatments were applied in both locations, indicating that the concentrations of 400 and 500 mg·L-1 ABA applied in a solution with the surfactant Latron B-1956® were not phytotoxic for ‘Pinot gris’ and ‘Chardonnay’ (data not shown).

Bud dormancy:

‘Pinot gris’: During 2012-2013 season, buds from the ‘Pinot gris’ cuttings took 19 days to budburst on 31 Aug. and took 38 days to budburst on 5 Oct., indicating that the cultivar entered dormancy on 5 Oct, 2012 (Figure 3.5A). On 17 Oct, 2012, D50BB was the highest indicating maximum dormancy. Post-véraison ABA-treatment delayed budburst by about 15 days compared to control (Figure 3.5A). Post-véraison treated vines showed delayed budburst in subsequent months in November, December and January

(Figure 3.5A). Among all ABA treatments, these performed post-véraison induced the deepest dormancy. During 2013-2014 season, D50BB increased from early September to

October and peaked on 30 Oct., indicating the deepest dormancy (Figure 3.5B). Véraison treatment induced the deepest dormancy compared to the other treatments since only véraison showed significant increases of D50BB by 10, 10, six, and four days on 6 Sept.,

4 Oct., 30 Oct. and 21 Nov., respectively. In both seasons, grape buds reached the deepest dormancy status in mid-to-late October (Figure 3.5B).

Leaf and bud water content:

‘Pinot gris’: Results from the 2012 ‘Pinot gris’ experiment indicate that there were no differences in water content in bud and leaf tissues among all treatments. In 2013, there

were no differences in leaf water content; however, the bud water content of control was

51% while véraison, post-véraison and post-harvest ABA treatments were 42%, 42% and

47%, respectively on 6 Sep. 2013. On 4 Oct. and 30 Oct., the bud water contents of all treatments were approximately 45%. On 21 Nov., the bud water contents of control, véraison, post-véraison and post-harvest ABA treatments were 47%, 40%, 44% and 47%, respectively. Even though there were no significant difference among the treatments, véraison and post-véraison showed a trend of low water content values compared to control and post-harvest.

Freezing tolerance:

‘Pinot gris’: During the 2012-2013 dormant season, the first fall frost occurred on 12

Oct. 2012 (Figure 3.6A). The lowest temperature occurred during late-January to late-

February in Kingsville (-16.3 °C) (Figure 3.6A). Throughout the dormancy season, the minimum air temperatures were warmer than mid-winter LT50. Exogenous ABA increased bud FT of ‘Pinot gris’ through the dormant season, except 17 Oct. and 9 Jan., indicating that ABA effects on improving FT was shown during cold acclimation (late-

August to early-October), maximum cold hardiness (mid-November to mid-December) and deacclimation (late-February to mid-March) stages of ‘Pinot gris’ in 2012-2013

(Figure 3.7A). Véraison improved FT by ~4 °C during winter and ~2°C during early spring (Figure 3.7A). Post-véraison improved FT by ~2 °C during winter and early spring

(Figure 3.7A). Post-harvest only improved FT by 1.2 °C on 28 Feb. (Figure 3.7A).

During 2013-2014 season, the first fall frost occurred on 29 Nov. 2013 (Figure 3.6B).

During the coming January, February, and March, successive low temperature which dropped below -20°C occurred nine times (ranging from -21.0 °C to -25.9 °C) which

were colder than mid-winter LT50 (Figure 3.6B). Thus, freezing tests were only conducted during the cold acclimation (early-September to late-November) stages during the year. ABA improved the FT of ‘Pinot gris’ by 2.6°C, 2.2°C, 2.7°C and 2.2°C from

September to November with véraison and post-véraison having the most significant effect on improving FT(Figure 3.7B).

‘Chardonnay’: During 2012-2013 growing season, the first fall frost occurred on 6 Nov.

2012 (Figure 3.6C). The lowest temperature occurred during late-January to late-

February in Geneva (-12.8 °C) (Figure 3.6C). Throughout the dormancy season in 2012-

2013, the minimum air temperatures were warmer than mid-winter LT50. Application of exogenous ABA increased bud FT by 1.1 °C to 1.9 °C during mid-winter in 2012, but had no effect on FT during cold deacclimation (Figure 3.8A). Application at véraison, post-véraison and post-harvest all significantly improved FT during mid-winter (Figure

3.8A). During the 2013-2014 season, the first fall frost occurred on 29 Oct. 2013 (Figrue

3.6D). During the coming January, February and March, and similar to Kingsville, successive low temperature dropped below -20°C eight times (ranging from -20.3 °C to -

26.8 °C) in Geneva which were colder than mid-winter LT50 (Figure 3.6D). Thus, freezing tests were only conducted during the cold acclimation (early-October to late-

November) stages. ABA applied at véraison increase bud FT by ~2.4 °C on 4 Oct. and 25

Nov. (Figure 3.8B). On 25 Nov, véraison, post-véraison and post-harvest all showed siginificant improved FT by 2.7°C, 2.9°C and 2°C, respectively (Figure 3.8B).

Bud and cane injury:

‘Pinot gris’: In the Kingsville research vineyard, temperatures dropped below -20 °C eight times and ranged between -20.0 °C and -25.3 °C: -22.8 °C on 22 Jan, -21.2 °C on

24 Jan, -23.4 °C on 28 Jan, -21.0 °C on 8 Feb, -25.9 °C on 12 Feb, -25.9 °C on 17 Feb, -

25.5 °C on 28 Feb, and -23.2 °C on 3 Mar. Primary, secondary and tertiary buds of ‘Pinot gris’ suffered almost 100% damage in all treatments (Table 3.4). However, the percentages of damaged canes phloem were significantly different among treatments with

30%, 5%, 10% and 0% of control, véraison, post-véraison and post-harvest, respectively

(Table 3.4).

‘Chardonnay’: On 07 Jan. 2014, the lowest air temperature in Geneva was -23.9 °C and temperature dropped below -20 °C seven times and ranged between -20.0 °C and -24.0

°C: -20.3 °C on 26 Jan, -21.6 °C on 28 Jan, -20.9 °C on 6 Feb, -26.8 °C on 12 Feb, -26.3

°C on 17 Feb, -22.2 °C on 28 Feb, and -22.1 °C on 4 Mar. Primary, secondary and tertiary buds of ‘Chardonnay’ suffered 100% damage in all treatments and the percentage of cane damage was almost 100% in all the treatments (Table 3.4).

Field budburst:

‘Pinot gris’: Budburst in ‘Pinot gris’ occured on 6 May, 2013, with the following percentages: 56%, 43%, 30% and 28% in control, véraison, post-véraison and post- harvest, respectively (Table 3.5). All ABA-treated grapevines showed significantly delayed budburst percentage compared to control (Table 3.5). Post-véraison and post- harvest showed more obvious delayed budburst among the four treatments (Table 3.5).

But this was not significant after 6 May.

‘Chardonnay’: On 3 May, 2013 in Geneva, the budburst percents of control, véraison, post-véraison and post-harvest were 28%, 23%, 13%, and 17%, respectively; and on 7

May, budburst was 88%, 83%, 85%, and 84%, respectively (Table 3.5). However, budburst percent values were not statistically different among treatments.

Discussion

Effect of ABA on grapevine physiology during the growing and dormant season:

Application of exogenous ABA caused early leaf senescence and abscission in both

‘Pinot gris’ and ‘Chardonnay’. ABA’s effects on leaf color change and abscission increased when applied on vines with older leaves. These findings support previous studies on greenhouse-grown Vitis ‘Cabernet franc’ and ‘Chambourcin’ (Zhang et al.,

2011). The observed reduction of chlorophyll concentrations following ABA treatment is indicative of the slowdown of photosynthesis and initiation of leaf senescence process

(Zhang and Dami, 2012a). The chlorophyll concentration continuously decreased in both control and ABA-treated ‘Pinot gris’ vines, but in ABA-treated vines’ chlorophyll content rapidly dropped from the end of September to mid-October. In previous reports, similar results were observed in field-grown Vitis vinifera ‘Cabernet franc’, where the chlorophyll content of all treatments steadily decreased by ~30% from September to mid-

October and ABA consistently reduced the chlorophyll content during this period (Zhang and Dami, 2012a).

Four hundred and 500 mg·L-1 ABA did not elicit phytotoxic response or affect yield components or fruit composition in ‘Pinot gris’ and ‘Chardonnay’. These findings are consistent with previous research on both table grapes in California (Lurie et al., 2009;

Peppi et al., 2007) and Vitis ‘Cabernet franc’ and ‘Chambourcin’ in Ohio (Zhang and

Dami, 2012a, 2012b). ABA application did not affect the vegetative growth of either

‘Pinot gris’ or ‘Chardonnay’, which is consistent with previous reports with ‘Cabernet franc’ and ‘Chambourcin’ (Zhang and Dami, 2012a, 2012b).

ABA is traditionally regarded as a positive regulator of dormancy induction (Kucera et at., 2005). In ‘Pinot gris’, ABA application at 15 days after véraison (2012) and véraison

(2013) had the most effect on dormancy: the budburst of vines treated 15 days after véraison (2012) treated vines was delayed by an average of six days from mid-October to early-January; and the budburst of vines treated at the time of véraison (2013) treated vines was delayed by an average of 7.5 days from early-September to late-November.

The application of 400 and 600 mg· L-1ABA at véraison and 20 days after véraison effectively enhanced dormancy by four days from November to February in field-grown

‘Carbernet franc’(Zhang and Dami, 2012a). The application of 400 mg· L-1ABA at véraison and 20 days after véraison also effectively enhanced dormancy by six days from

November to February in field-grown ‘Chambourcin’(Zhang and Dami, 2012b).

ABA has been shown to increase the FT of several woody plants, such as Arabidopsis thaliana (L.) Heynh. (Mantyla et al., 1995), Betula pendula Roth. (Li et al., 2003),

Hordeum vulgare L. (Bravo et al., 1998), Secale cereale L. (Churchill et al., 1998),

Triticum aestivum L. (Dallaire et al., 1994), Cicer arietinum L (Kumar et al., 2008),

Solanum Tuberosum L. (Mora-Herrera and Lopez-Delgaelo, 2007), Acer saccharum

Marsh. (Bertrand et al., 1997), and Malus domestica (L.) Borkh. (Guak and Fuchigami,

2001). In grapes, ABA has been reported to increase the FT of two Vitis cultivars:

“Cabernet franc” and “Chambourcin” (Zhang et al., 2012a, 2012b). The results in this study confirm the role of ABA in improving the FT of ‘Pinot gris’ and ‘Chardonnay’.

In ‘Pinot gris’, véraison and post-véraison ABA treatements had the lowest LT50s in both years, indicating that ABA applications was the most effective from véraison to 27 days after véraison. We also hypothesized that ABA improves FT of buds by inducing bud

tissue dehydration, hence leading to less freezable water. According to the results of

‘Pinot gris’ grapevine bud and leaf water content, there was no difference among treatments. However, véraison and post-véraison treatments showed decreased bud water content trend compared to control and post-harvest and this result paralleled the results in freezing test. ABA improved FT of ‘Chardonnay’ but not to the same level as in ‘Pinot gris’ and the differences among the three different application timings were not obvious.

As for the death of all ‘Pinot gris’ and ‘Chardonnay’ primary buds during the polar vertex in January 2014, ABA might have improved the FT up to a temperature threshold, but air temperature was too low (-25.3 °C in Kingsville and -23.9 °C in Geneva) and lasted for hours. Previous experiments on ‘Cabernet franc’ confirmed ABA’s effect on improving

FT via field observations of bud injury assessment following a natural freezing event

(Zhang and Dami, 2012a). However the temperature was warmer and the freezing duration was much shorter in the 2011 winter event than in 2014.

ABA effectiveness in relation to application timing:

In this study, application of 400 mg·L-1 ABA during véraison to four weeks post-véraison in both years had the best effect on improving FT of ‘Pinot gris’ while post-véraison (two weeks after véraison) application in 2012 and véraison application in 2013 were most effective on inducing deepest dormancy. Four hundred mg·L-1 and 500 mg·L-1 ABA application improved FT of ‘Chardonnay’ but differences among application timing were not obvious. Our findings showed some similarities when compared to previous results.

A pervious study reported that 400 mg·L-1 or 600 mg·L-1 ABA application at three to four weeks post-véraison was effective on improving FT and inducing deeper dormancy of field-grown Vitis vinifera ‘Cabernet franc’(Zhang and Dami, 2012a). Another study also

reported 400 mg·L-1 ABA application at three to four weeks post-véraison was effective on improving FT and inducing deep dormancy of field-grown Vitis vinifera

‘Chambourcin’(Zhang and Dami, 2012b).

The inconsistent response of ABA effectiveness and application timing may be attributed to differences in phenological stages, growing degree days (GDD) and leaf age. First, there was inconsistency of ABA application timing and phenology. With ‘Pinot gris’, the post-véraison application of ABA was sprayed 15 days after véraison in 2012 and 27 days after véraison in 2013 due to weather (Table 3.1). With ‘Chardonnay’, post-véraison application was sprayed 15 days after véraison in 2012 and 22 days after véraison in

2013. Second, even though vines were at similar phenological stages of berry development, calendar date and GDD may be different. In Kingsville, GDD ranged between 943 and 1138 (19% variability) at véraison, 1225 and 1464 (18% variability) at harvest. The GDD of two years’ best spray timing were 1296 (2012) and 943 (2013), respectively, with 32% variability (Table 3.1). In Geneva, ABA application timing was consistent in relation to GDD. GDD ranged between 1156 and 1159 (0.3% variability) at véraison, 1312 and 1373 (4.5% variability) at harvest (Table 3.1). Third, the leaf age expressed as days after budburst (DAB), varied between the two years at similar phenological stages of berry development (Table 3.1). In the ‘Pinot gris’ study, the most effective ABA application varied between leaf age of 107 (2013 ABA véraison application) and 120 (2012 ABA post-véraison application). These results support previous findings in greenhouse-grown (Zhang et al. 2011) and field-grown (Zhang and

Dami, 2012a) Vitis vinifera ‘Cabernet franc’ that ABA was most effective on inducing dormancy and improving FT when applied at leaf age between 110 and 137 leaf ages.

Therefore, ABA application at certain leaf age showed the least variability to measure

ABA effectiveness and leaf age might be a better indicator of spray timing than phonological stage.

In conclusion, exogenous ABA application at concentrations of 400 mg·L-1 and 500 mg·L-1 effectively improved the bud FT of ‘Pinot gris’ and ‘Chardonnay’ without adversely affecting vine size, yield or fruit composition. The best time to spray ABA on

‘Pinot gris’ was between véraison and 20 days post-véraison or leaf age between 105 and

120 which led to the lowest LT50 and deepest dormancy. Differences among ABA application timing of ‘Chardonnay’ were not obvious. The finding of this study confirmed that exogenous ABA application has the potential to protect Vitis vinifera vines from cold injury.

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Kumar, S., G. Kaur, and H. Nayyar. 2008. Exogenous application of abscisic acid improves cold tolerance in chickpea (Cicer arietinum L.). J. Agron. Crop Sci. 194:449-

456.

Li, C., O. Junttila, P. Heino, and T. E. Palva. 2003. Different responses of northern and southern ecotypes of Betula pendula to exogenous ABA application. Tree physiol. 23:

481-487.

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Weksler, and A. Lichter. 2009. Abscisic acid improves colour development in 'Crimson

Seedless' grapes in the vineyard and on detached berries. J. Hort. Sci. Biotechnol. 84:639-

644.

Mantyla, E., V. Lang, and E.T. Palva. 1995. Role of abscisic-acid in drought-induced freezing tolerance, cold-acclimation, and accumulation of Lt178 and Rab18 proteins in

Arabidopsis-Thaliana. Plant Physiol. 107:141-148.

Mora-Herrera, M.E. and H.A. Lopez-Delgado. 2007. Freezing tolerance and antioxidant activity in potato microplants induced by abscisic acid treatment. Am. J. Potato Res.

84:467-475.

Peppi, M.C., M.W. Fidelibus, and N.K. Dokoozlian. 2007. Application timing and concentration of abscisic acid affect the quality of 'Redglobe' grapes. J. Hort. Sci.

Biotechnol. 82:304-310.

Poling E.B. 2008. Spring cold injury to winegrapes and protection strategies and methods. HortScience 43:1652-1662.

Wake, C. and A. Fennell. 2000. Morphological, physiological and dormancy responses of three Vitis genotypes to short photoperiod. Physiol. Plant. 109:203-210.

Wolf, T.K. and R.M. Pool. 1987. Factors affecting exotherm detection in the differential thermal analysis of grapevine dormant buds. J. Am. Soc. Hort. Sci. 112:520-525.

Zabadal,T., I. Dami, M. Goffinet, T. Martinson and M. Chien. 2007. Winter injury to grapevine and methods of protection. Michigan State University Extension, East Lansing,

MI.

Zhang, Y., T. Mechlin, and I. Dami. 2011. Foliar application of abscisic acid induces dormancy responses in greenhouse-grown grapevines. HortScience 46:1271-1277.

Zhang, Y. and I. Dami. 2012a. Foliar application of abscisic acid increases freezing tolerance of field-grown Vitis vinifera ‘Cabernet franc’ grapevines. Am. J. Enol.

Viticult.63:377-384.

Zhang, Y. and I. Dami. 2012b. Improving freezing tolerance of ‘Chambourcin’grapevines with exogenous abscisic acid. HortScience, 47: 1750-1757.

Table 3.1. Abscisic acid (ABA) application dates and corresponding growing degree days (GDD) and days after budburst (DAB) relative to the phenology of ‘Pinot gris’ and ‘Chardonnay’.

Budburst Véraison Post-véraison Harvest Post-harvest Cultivar/Site GDDx FFDw Date Date GDDz DABy Date GDD DAB Date GDD DAB Date GDD DAB

3-May, 2012 16-Aug 1138 105 31-Aug 1296 120 19-Sep 1464 139 28-Sep 1493 148 1637 191 ‘Pinot gris’ (AARS, Kingsville) 6-May, 2013 21-Aug 943 107 17-Sep 1292 134 24-Sep 1225 141 11-Oct 1307 158 1438 199

13-May, 2012 16-Aug 1156 95 31-Aug 1312 110 25-Sep 1503 135 28-Sep 1516 138 1615 191

‘Chardonnay’ (Geneva) 5-May, 2013 26-Aug 1159 113 17-Sep 1373 135 30-Sep 1445 148 21-Oct 1559 169 1567 199

z 76 GDD: cumulative daily mean temperatures with base 10 °C from 1 Apr. through date of corresponding stage of development.

y DAB: days after budburst. x GDD: cumulative daily mean temperatures with base 10 °C from 1 Apr. through 31 Oct. w FFD: successive days with minimum daily temperatures at or above 0 °C.

Table 3.2. Effect of abscisic acid (ABA) on yield components, fruit composition, and vine size in ‘Pinot gris’ grapevines grown in Kingsville, Ohio.

Clusters Ravaz Titratable Yield Cluster wt Berries per Berry wt Pruning TSSx Treatmentz per vine index pH acidity (kg·vine-1) (g) cluster (g) ( kg·vine-1) (°Brix) y (g·L-1) Harvest: 19 Sept. 2012 Control 3.11 31 100 63 1.60 0.53 5.9 23.4 3.53 6.5 Véraison 2.70 30 91 55 1.66 0.65 4.2 23.5 3.54 6.5 Post-véraison 3.13 33 95 61 1.55 0.62 5.1 23.2 3.59 6.5 Post-harvest 2.91 31 95 58 1.64 0.58 5.0 23.5 3.50 6.6 Significancew NS NS NS NS NS NS NS NS NS NS 77

Harvest: 24 Sept. 2013 Control 2.94 26 113 72 1.58 0.59 5.0 19.8 3.39 6.5 Véraison 3.17 26 122 80 1.53 0.64 5.0 19.6 3.50 6.4 Post-véraison 3.19 27 118 75 1.57 0.50 6.4 19.7 3.51 5.9 Post-harvest 2.62 24 109 74 1.47 0.50 5.2 19.4 3.43 6.3 Significance NS NS NS NS NS NS NS NS NS NS z Véraison, post-véraison, post-harvest: ABA sprayed at 50% véraison, 20 and 50 days after 50% véraison, respectively. y Ravaz index: was calculated by dividing total yield per vine by the pruning weight recorded during the winter following each season. x TSS: Total soluble solid. wNS, *, **, and *** Not significant, significant at p ≤ 0.05, 0.01, and 0.001, respectively.

Table 3.3. Effect of abscisic acid (ABA) on yield components, fruit composition, and vine size in ‘Chardonnay’ grapevines grown in Geneva, Ohio (Harvest date: 30 Sept. 2013).

Berries Titratable Yield Clusters per Cluster wt Berry wt Pruningy TSS Treatmentz per pH acidity (kg·vine-1) vine (g) (g) ( kg·vine-1) (°Brix) cluster (g·L-1) Control 3.63 40 95 60 1.58 0.35 17.5 3.58 9.3 Véraison 3.86 39 100 65 1.53 0.26 17.2 3.49 8.5 Post-véraison 3.63 38 95 61 1.57 0.31 17.2 3.53 8.1 Post-harvest 3.86 36 109 74 1.47 0.33 18.1 3.45 8.4 Significancex NS NS NS NS NS NS NS NS NS z Véraison, post-véraison, post-harvest: ABA sprayed at 50% véraison, 20 and 50 days after 50% véraison, respectively. y 78 Due to technical difficulties at the commercial vineyard, harvest was only conducted in 2013 and pruning weight in 2012. For that reason Ravaz index was not computed. x NS, *, **, and *** Not significant, significant at p ≤ 0.05, 0.01, and 0.001, respectively.

Table 3.4. Bud and cane phloem damage of ‘Pinot gris’ and ‘Chardonnay’ after sub-freezing events in Kingsville (-25.3 °C) and Geneva (-23.9 °C) on 7 Jan. 2014 (Samples were collected on 13 Jan. 2014).

‘Pinot gris’ (Kingsville) ‘Chardonnay’ (Geneva) Bud damage (%) Bud damage (%) Cane Cane Treatmentz phloem phloem Primary bud Secondary bud Tertiary bud damage Primary bud Secondary bud Tertiary bud damage (%) (%) Control 100 100 100 30a 100 100 100 100 Véraison 99 99 97 5b 100 100 100 100 Post-véraison 100 100 100 10b 100 100 100 100 Post-harvest 100 100 99 0c 100 100 100 99 Significancey NS NS NS * NS NS NS NS 79 z

Véraison, post-véraison, post-harvest: ABA sprayed at 50% véraison, 20 and 50 days after 50% véraison, respectively. y NS, *, **, and *** Not significant, significant at p ≤ 0.05, 0.01, and 0.001, respectively.

Table 3.5. Effect of abscisic acid (ABA) on budburst of ‘Pinot gris’ and ‘Chardonnay’ grapevines grown in Kingsville, OH and Geneva, OH in 2013.

Budburst (%)

Treatmentz 'Pinot gris' (Kingsville) 'Chardonnay' (Geneva) 3 May 6 May 2013 8 May 2013 10 May 2013 13 May 2013 16 May 2013 7 May 2013 10 May 2013 14 May 2013 2013 Control 56a 88 91 93 94 28 88 90 90 Véraison 43b 87 92 94 96 23 83 88 88 Post-véraison 30bc 80 86 89 91 13 85 89 91 Post-harvest 28bc 81 89 90 92 17 84 88 89 Significancey * NS NS NS NS NS NS NS NS z Véraison, post-véraison, post-harvest: ABA sprayed at 50% véraison, 20 and 50 days after 50% véraison, respectively. y NS, *, **, and *** Not significant, significant at p ≤ 0.05, 0.01, and 0.001, respectively.

Control Véraison Post-véraison Post-harvest

Figure 3.1. Effect of abscisic acid (ABA) on leaf senescence and abscission of ‘Pinot gris’ grapevines grown in Kingsville, OH. Photos were taken on A) 09 Oct. 2012 and B) 17 Oct. 2012. Grapevines were sprayed with 0 mg·L-1 (control) and 400 mg·L-1 ABA at 50% véraison on 16 Aug. 2012, post-véraison on 31 Aug. 2012, and post-harvest on 28 Sept. 2012. Note: increased yellowing of leaves as ABA was applied later in the season from véraison to post-harvest, which had the most abscised leaves.

A ▪ 100 ▪ 90 Control 80 ▪ Véraison 70 60 Post-véraison 50 40 Post-harvest 30

Abscised leaves (%) 20 10 0 17-Oct-12 22-Oct-12 25-Oct-12 Observation Date

 B * ▪ 100 

80 Control 70 Véraison 60 50 Post-véraison 40 Post-harvest 30 *

Abscised leaves (%) 20 10 0 21-Aug-13 6-Sep-13 24-Sep-13 21-Oct-13 Observation date

Figure 3.2. Effect of abscisic acid (ABA) on leaf abscission of ‘Pinot gris’ grapevines grown in Kingsville in A) 2012 and B) 2013. Significance of ABA treatment effects are indicated by * (p≤0.05) for véraison;  (p≤0.05) for post-véraison; and ▪ (p≤0.05) for post-harvest.

Control 35

ABA

(SPAD (SPAD units) 25 Chlorophyllcontent

15 6-Sep-13 18-Sep-13 11-Oct-13 25-Oct-13 Collection Date

Figure 3.3. Effect of abscisic acid (ABA) on chlorophyll content of ‘Pinot gris’ grapevines grown in Kingsville in 2013. For clarity, only one ABA plot was presented which was the average of véraison (ABA sprayed on 21 Aug. 2013), post-véraison (ABA sprayed on 17 Sept. 2013) and post-harvest (ABA sprayed on 11 Oct. 2013). * indicates significance at p ≤0.05.

Control Véraison Post-véraison Post-harvest

Figure 3.4. Effect of abscisic acid (ABA) on leaf senescence and abscission of ‘Chardonnay’ grapevines grown in Geneva, OH. Photos were taken on A) 09 Oct. 2012 and B) 17 Oct. 2012. Grapevines were sprayed with 0 mg·L-1 (control) and 400 mg·L-1 ABA at 50% véraison on 16 Aug. 2012, post-véraison on 31 Aug. 2012, and post-harvest on 28 Sept. 2012. Note: increased yellowing of leaves as ABA was applied later in the season from véraison to post-harvest, which had the most abscised leaves.

A 50  Control 45 ABA(Post-véraison)

35  30   25

Days Days to50% budbrust 20

10 31-Aug 5-Oct 17-Oct 14-Nov 12-Dec 9-Jan 28-Feb 21-Mar Collection Date

50 B Control 45

* ABA(véraison) 40 35 ** 30 * ** 25

20 Days Days to50% budburst 15 10 6-Sep 4-Oct 30-Oct 21-Nov Collection Date

Figure 3.5. Effect of abscisic acid (ABA) on bud dormancy (days to 50% budbrust) on ‘Pinot gris’ grown in Kingsville during A)2012-2013 and B)2013-2014 seasons. Significance of ABA treatment effects are indicated by * (p ≤ 0.05) and ** (p ≤ 0.01) for the véraison application;  (p ≤ 0.05) and  (p ≤ 0.01) for the post-véraison application. For clarity, only control and significantly different ABA treatments are presented.

50 A 40 Max Air Temp(°C) Min Air Temp(°C) BB (6-May-13)

° 20

0 Temperature ( Temperature

-10

86 -20

FF (12-Oct-12) -30

Date Continued

Figure 3.6. Daily minimum and maximum temperatures and dates of fall frost (FF) and budburst (BB) recorded at ‘Pinot gris’ and ‘Chardonnay’ fields in: A) Kingsville, OH (2012-2013); B) Kingsville, OH (2013-2014); C) Geneva, OH (2012-2013); and D) Geneva, OH (2013-2014).

Figure 3.6. continued 50

Max Air Temp(°C) B 40 Min Air Temp(°C)

C) C) 20 °

87 Temperature ( Temperature

-10 FF (29-Nov-13)

-20

-30

Date

Continued

Figure 3.6. continued

50 Max Air Temp(°C) C 40 Min Air Temp(°C) BB (5-May-13)

° 20

88 Temperature ( Temperature

-10 FF (6-Nov-12) -20

-30

Date

continued

Figure 3.6. continued

Max Air Temp(°C) D 40 Min Air Temp(°C)

° 20

0 Temperature ( Temperature

-10 FF (29-Oct-13) -20

-30

Date

Control

-5 *

Véraison



* Post-véraison * -10

Post-harvest



C) °

▪ * ( -15

50 * 



-20 *

-25

9-Jan-13

5-Oct-12

17-Oct-12

28-Feb-13

12-Dec-12

31-Aug-12

14-Nov-12 21-Mar-13 Collection Date

-5 B * Control Véraison *  -10 Post-véraison

* Post-harvest

C) 

° ( -15 *

50  LT

-20 ▪

-25

4-Oct-13

6-Sep-13 30-Oct-13 Collection Date 25-Nov-13

Figure 3.7. Effect of ABA on freezing tolerance (LT50) in ‘Pinot gris’ grapevines grown in Kingsville during A) 2012-2013 and B) 2013-14 seasons. Control,véraison, post- véraison, and post-harvest correspond to ABA application at 50% véraison, 20, and 50 days after 50% véraison stage. Significance of ABA treatment effects are indicated by * (p ≤0.05) for véraison;  (p ≤0.05) for post-véraison; and ▪ (p ≤0.05) for post-harvest application.

-5 * A -10

 *

°  ( -15 ▪ 50  Control

LT ▪ ▪ Véraison -20 Post-véraison Post-harvest

-25

5-Oct-12

17-Oct-12

28-Feb-13

12-Dec-12

31-Aug-12

14-Nov-12 21-Mar-13 Collection Date

-5 * B -10 *



° ( -15 ▪

50 Control LT Véraison -20 Post-véraison

-25 Post-harvest

4-Oct-13

30-Oct-13 25-Nov-13 Collection Date

Figure 3.8. Response of bud LT50 to ABA applied at véraison, post-véraison and post- harvest in Geneva, OH during A) 2012-2013 and B) 2013-14 seasons. Control,véraison, post-véraison, and post-harvest correspond to ABA application at 50% véraison, 20, and 50 days after 50% véraison stage. Significance of ABA treatment effects are indicated by * (p ≤0.05) for véraison;  (p ≤0.05) for post-véraison; and ▪ (p ≤0.05) for post-harvest application.

Chapter 4: Effects of Exogenous Abscisic Acid on Bud Freezing Tolerance and Water Content of Greenhouse-grown Vitis vinifera ‘Cabernet franc’ Grapevines

Abstract

Grapes are fruit crops of great economic value, but exihibit a high level of temperature sensitivity and are threatened by freezing stress. ABA has been reported to increase the

FT of several woody plants and several grape cultivars. The purpose of this study was to confirm findings from previous greenhouse experiments. The specific objectives of this research were to: 1) evaluate the response of greenhouse-grown ‘Cabernet franc’ to exogenous ABA, 2) characterize the temporal changes of freezing tolerance and water content in bud tissues. ‘Cabernet franc’ potted grapevines were used in three experiments conducted in the greenhouse in 2012 and 2013. The effects of ABA on FT, and water content in bud and leaf tissues were determined. The results demonstrated that application of exogenous ABA increased the bud FT of greenhouse-grown ‘Cabernet franc’ grapevines and the effect was shown 1w after ABA application. ABA caused bud desiccation, which may have led to increased FT. Our study showed that bud dehydration may occur as early as 48h after ABA application which led to increased FT

(decreased LT50) one week later. The findings of this project are valuable to grape producers to provide another tool for freeze protection and to the scientific community for better understanding of the mechanisms of freezing tolerance.

Introduction

Currently available protection methods for preventing cold injury are active methods which directly counteract the frost and freeze threat and are implemented just prior to or during the cold event and passive methods, which focus on the site, cultivar selection and cultural practices (Poling, 2008). The main active approaches include wind machine, heater, over-vine sprinkling, fogger and vineyard insulation with other materials (Poling,

2008). Wind machines are used to protect vineyards from frost damage under radiation frost condition by mixing the warmer upper air layers with the colder air layers on the vineyard floor (Poling, 2008). It was reported that the wind machines installed in South

River Vineyard in Ohio have helped raise the temperature 4°C on average, which avoided crop loss of $24,000 (Zabadal et al., 2007). However, wind machines are not practical for most small vineyards in Ohio because of the cost. Heater, fogger and over-vine sprinkler system may be available for smaller vineyards. However, the disadvantages include high installation cost, high water usage, and potential of overwatering and increased disease pressures.

Moreover, to avoid low temperature in the vineyard, growers can choose to insulate grapevines with other materials, such as snow, mulch, and soil. Snow can successfully counteract the radiation freeze. However, the disadvantage of snow insulation is the unpredictable snow occurrence. Growers have also adopted soil instead of snow to avoid low temperature. Although soil is a good insulation material, it requires specialized equipment to remove the hilled soil in the spring and the process usually brings risks of damaging vines and soil erosion.

Additional methods to protect grapevines from cold winter include chemical applications.

Some chemicals have been tested on grapevines mainly for delaying budburst to avoid spring frost. The present research aimed to improve FT of sensitive grape cultivars using absicsic acid (ABA). Exogenous ABA application advanced FT of some sensitive grape cultivars, such as ‘Cabernet franc’ and ’Chambourcin’ (Zhang et al. 2012a, 2012b). ABA did not affect yield or fruit composition, but caused early leaf abscission, advanced bud dormancy, decreased bud water content and eventually increased FT (Zhang et al. 2012a,

2012b). In this study, additional cultivars ‘Pinot girs’ and ‘Chardonnay’ were evaluated to confirm previous results. Field results showed that ABA effectively improved the bud

FT of ‘Pinot gris’ and ‘Chardonnay’ without affecting vine size, yield or fruit composition (Chapter 3). The purpose of this study was to confirm findings from previous greenhouse experiments. Furthermore, we aimed to determine physiological

(tissue water content) changes in ABA-treated vines. ‘Cabernet franc’ potted grapevines were used in three experiments conducted in the greenhouse in 2012 and 2013. The effects of ABA on FT and water content in bud and leaf tissues were determined.

Materials and Methods

Plant material and treatment:

Vitis vinifera ‘Cabernet franc’ grafted on Vitis riparia × Vitis rupestris ‘Couderc 3309’ were pruned to two spurs with two nodes and held at 4°C in a cooler to satisfy their chilling requirement before transfering to the greenhouse. Potted vines were moved to the greenhouse on 19 Mar. 2013, 1 Aug. 2013 and 10 Mar. 2014. The settings of the greenhouse were as follows: relative humidity was maintained around 50% day and night. The photoperiod was maintained 12 hours a day and the light intensity was

maintained at 300 μmol∙m-2∙s-1 using 1000-watt metal halide and 1000-watt high pressure sodium lights (Sunlight Supply, Woodland, WA) (Appendix B). The grapevines were watered every day with approximate 600ml water and fertilized three times a week with

11 g·L-1 20-20-20 fertilizer (150 mg·L-1 nitrogen). Prior to ABA application, shoots were trimmed occasionally to keep the average leaf number and shoot length to 15 and 150 cm, respectively.

Potted vines with uniform growth and size were selected for the greenhouse experiment.

Table 4.1 shows vines’ leaf age, ABA application and sample collection timing for each experiment. ABA was applied at leaf age between 84 and 95. Leaf age was determined based on Eichorn-Lorenz (EL) scale for stages of shoot development (Eichorn and

Lorenz, 1977) with one-day leaf age corresponding to the first leaf separated from the shoot tip (EL stage 7). Also, shoots were required to have periderm formation (color change from green to brown) prior to ABA application. Treatments were applied using a completely randomized design of three replications with two-vine plots and consisted of the following: control (0 mg·L-1ABA, sprayed deionized water with 0.05% tween-20 surfactant) and ABA (400 mg·L-1 ABA sprayed with 0.05% tween-20 surfactant).

Protone® SG (Valent BioSciences Corporation, Libertyville, IL) which contains 20.0%

(w/w) S-ABA as a.i. was used.

Sample collection for FT and water content:

In the first experiment, ABA was applied on 03 July, 2013 (84 days after budburst).

Samples were collected 24h, 48h, 2w, and 4w after ABA applications (Table 4.1). In the second experiment, ABA was applied on 28 Nov. 2013 (95 days after budburst) and samples were collected 24h, 48h, 1w and 2w after ABA application (Table 4.1). The third

experiment was a repeat of the second experiment, and ABA was applied on 02 July,

2014 corresponding to 92 days after budburst and samples were collected 24h, 48h, 1w and 2w after ABA application. Data collection included measuring bud FT, bud and leaf water contents, and leaf and bud sugar concentrations. At each sample collection time, buds and leaves from node positions two to five on the first shoot were used for the water content measurement. Buds from node positions two to six on the other shoot were used for the freezing test. Buds and leaves from node positions six to eight of the first shoot and seven to eight of the second shoot were used for sugar analysis (Figure 4.1). In the first greenhouse experiment conducted in July 2013, leaf samples were not collected since the leaves suffered phytotoxicity originating from applications of Avid, Pylon, and

Judo (Appendix C).

Freezing tolerance:

After sample collection, canes were placed in the cooler with ice. Canes were stored at

4°C for no longer than 48 hours prior to freezing test. FTs were determined by thermal analysis. Buds were excised and placed on the thermoelectric modules (MELCOR,

Trenton, NJ), which were placed in a Tenney environmental chamber (Thermal Products

Solutions, New Columbia, PA). The chamber temperature was lowered from -2°C to -

50°C at the rate of 4 °C·h-1. The FT of buds was determined by identifying the median or mean low temperature exotherm (LTE), which corresponds to lethal temperature that kills

50% of the population, or LT50 (Wolf and Pool, 1987).

Water content:

Leaf and bud samples were weighed immediately after collection to determine fresh weights. Leaf and bud samples were placed in an oven at 70°C for more than a week, and

then weighed to determine dry weights. Water content was determined as the difference between dry and fresh weight and expressed in percentage of fresh weight (Zhang et al.,

2011).

Statistical analysis:

All data were subjected to analysis of variance using SAS statistical software (version

9.3; SAS Institute, Cary, NC). When treatments were significantly different, an LSD test was used for mean comparisons at p ≤0.05, ≤0.01, ≤0.001.

Results

Determination of freezing tolerance (FT):

Experiment 1: In the first experiment conducted in July, 2013, ABA did not affect FT

24h and 48h after ABA application, but started to affect FT 2w and 4w after ABA application (Figure 4.2A). Between 24h and 48h after ABA application, LT50 of all

‘Cabernet franc’ grape buds ranged between -9.2 °C and -10.0 °C and showed no significant differences between control and ABA treatment (Figure 4.2A). Two weeks after ABA application, ABA improved the FT by 2.4 °C. At this point, LT50 of control and ABA-treated buds were -7.9 °C and -10.3 °C, respectively (Figure 4.2A). ABA also improved FT 4w after ABA application by 1.4 °C. At this point, LT50 of control and

ABA-treated buds were -5.2 °C and -6.6 °C, respectively (Figure 4.2A).

Experiment 2: Similar results were observed in the repeat experiment conducted in Nov.

2013. ABA application did not affect FT 24h and 48h after ABA application. The LT50s of control and ABA-treated grapevines ranged between -9.5 °C and -11.8 °C, but were not statistically different (Figure 4.2B). At 1w and 2w after ABA application, ABA

decreased the LT50 by 3.2 °C and 4.9 °C, respectively as compared to control (Figure

4.2B).

Experiment 3: In the third experiment, ABA did not affect FT 24h and 48h after application, but began to affect FT 1w and 2w after application (Figure 4.2C). After 2w,

LT50 of control and ABA-treated vines were -5.9 °C and -7.5 °C, respectively (Figure

4.2C). After 4w, ABA improved LT50 by 2.1 °C (Figure 4.2C).

Leaf and bud water content:

Results indicate no differences of water content in leaf tissues after ABA application in all experiments (Figure 4.3). Leaf water content ranged from 68% to 73%, 71% to 77%, and 67% to 72% in each experiment, respectively (Figure 4.3). However, ABA treatments affected bud water content (Figure 4.4). Results from all three experiments showed no significant differences of bud water content (range: 41%-61%) 24h and 48h after ABA application (Figure 4.4). In the first experiment, water content was lower in treated (47.9%) leaves than that in control (55.4%) 2w after ABA application (Figure

4.4A). In other words, ABA decreased water content or caused bud desiccation in treated buds. In the second experiment, water content was significantly different 1w and 2w after

ABA application (Figure 4.4B). ABA-treated buds had 22% (1w) and 8% (2w) less water content than in control (Figure 4.4B). At the end of the second experiment after 2w,

ABA-treated and control buds averaged 40% and 48%, respectively. In the third experiment, even though the water content of ABA-treated vines showed a decreased trend compared to control 48h, 1w and 2w after ABA application, there were no significant differences (Figure 4.4C). At the end of the third experiment after 2w, ABA treated and control buds averaged 48% and 53%, respectively (Figure 4.4C).

Discussion

ABA has been shown to increase the FT of several woody plants, such as Arabidopsis thaliana (L.) Heynh. (Mantyla et al., 1995), Betula pendula Roth. (Li et al., 2003),

Hordeum vulgare L. (Bravo et al., 1998), Secale cereale L. (Churchill et al., 1998),

Triticum aestivum L. (Dallaire et al., 1994), Cicer arietinum L (Kumar et al., 2008),

Solanum tuberosum L. (Mora-Herrera and Lopez-Delgaelo, 2007), Acer saccharum

Marsh. (Bertrand et al., 1997), and Malus domestica (L.) Borkh. (Guak and Fuchigami,

2001). ABA was also reported to increase FT of two Vitis cultivars, ‘Cabernet franc’ and

‘Chambourcin’ in both the field (Zhang et al., 2012a, 2012b) and greenhouse (Zhang,

2012). In this study, ABA treated buds showed increased FT 1w after application. Our results are consistent with previous greenhouse FT experiments on ‘Cabernet franc’ and

‘Chambourcin’ (Zhang, 2012). In previous experiments, ABA increased FT 2w, 4w, and

6w after application in greenhouse-grown ‘Cabernet franc’; and 4w, and 6w in greenhouse-grown ‘Chambourcin’(Zhang, 2012). This study confirmed the previous greenhouse findings that ABA increased FT of ’Cabernet franc’ 2w and beyond after

ABA application. We also demonstrated that ABA affects LT50 as quickly as 1w after application.

It has been reported that ABA causes rapid closure of the stomata and serves as a primary signal in stomata regulation of water loss (Zeevaart et al., 1988). Jones and Mansfield’s report (1970) also stated exogenous ABA application can cause stomata closure and help plants maintain water within tissues. However, in this study, no significant difference was shown in water content of grape leaves after ABA application. This result was consistent with Zhang’s previous greenhouse experiments on ‘Cabernet franc’ and ‘Chambourcin’

(Zhang, 2012). Similar result also showed that exogenous ABA application did not affect leaf water content under cool and wet climate (Balint and Reynolds, 2012). This may be explained as greenhouse-grown vines were well watered, which can affect both stomatal aperture sensitivity to ABA (Tardieu and Davies, 1992). Between 1w and 2w after ABA application, the water content of ABA-treated ‘Cabernet franc’ buds showed a decreasing trend and the difference were significant in two out of three experiments. Previous experiments on ‘Cabernet franc’ also showed significant changes in bud water content 2w after ABA application (Zhang, 2012). We also noticed that every time ABA treatments lowered water content below 48%, LT50 decreased as well. This result indicates that when bud water content reaches a certain level (48%), it started to affect bud FT.

Previous experiments on ‘Cabernet franc’ also showed an increase of FT, with 45% bud water content 2w after ABA application (Zhang, 2012). This observation needs further investigation.

In a previous field study, bud dehydration occurred simultaneously with increasing FT in

‘Carbernet franc’ and ‘Chambourcin’, which suggests a strong correlation between bud water content and bud FT (Zhang, 2012). However, in our field experiments on ‘Pinot gris’, bud water content was not affected by ABA application (Chapter 3). In this greenhouse experiment, at 1w and 2w after ABA application, improved FT showed correlating with decreasing bud water content, but the results was not consistent in each experiment. Similar results were also observed in previous greenhouse-grown ‘Cabernet franc’ (Zhang, 2012).

In the first experiment, bud LT50 values ranged between -5.2 °C and -10 °C. In the second experiment, bud LT50 values ranged between -9.5 °C and -16.3 °C. In the third

100

experiment, LT50 values ranged between -5.6 °C and -8.0 °C, similar to values in the first experiment, but not the second experiment. Bud LT50s of the second experiment were much lower than those in the other two experiments. Also, in experiment 2, buds had less water content after 48h than in the other two experiments. This may be explained by the fact that the experiments were conducted at different times of year. The first and third experiments were conducted in July 2013 and 2014, respectively with longer photoperiod while the second experiment was conducted in November, 2014 with shorter photoperiod. According to the previous greenhouse experiment conducted on the same cultivar ‘Cabernet franc’, the bud LT50 ranged from -9 °C to -12 °C when conducted in the summer of 2012 (Zhang, 2012). The leaf age may also be a factor, since leaf age was not the same in each experiment. The leaf age of each experiment was 84, 95 and 92 days, respectively and previous leaf ages of previous experiments were 80 days (Zhang,

2012). This suggested bud FT was affected by several cumulative factors; ABA, leaf age, and photoperiod were among those factors. The LT50 profile of the first experiment did not show similarity with LT50 profiles of the second, the third and previous similar experiments (Zhang, 2012). The reason may be from the phytoxicity to grapevines sustained in early July, 2013 (Appendix C). This suggests that phytoxicity may have also affected bud FT.

In summary, this study has demonstrated that application of exogenous ABA could improve the bud FT of greenhouse-grown ‘Cabernet franc’ grapevines and the effect was shown after 1w after ABA application. ABA caused desiccation, which may have led to increased FT. Our study shows that bud dehydration may occur as early as 48h after

ABA application which led to increased FT (decreased LT50) 1 week later. The

101

relationship between sugar metabolism and ABA-induced desiccation will be investigated to detect whether ABA induces sugar accumulation and if so when. In this case, we will characterize the relationship between bud desiccation, soluble sugars, and

FT of buds.

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Table 4.1. Abscisic acid (ABA) application dates and corresponding leaf age relative to the phenology of greenhouse-grown ‘Cabernet franc’.

y Date pots were z Sample collection dates Budburst ABA Spray Leaf age moved to date date (DAB) greenhouse 24h 48h 1w 2w 4w Experiment 1 19-Mar. 2013 1-Apr 3-Jul 84 4-Jul 5-Jul 17-Jul 31-Jul

Experiment 2 1-Aug. 2013 25-Aug 28-Nov 95 29-Nov 30-Nov 5-Dec 12-Dec

Experiment 3 10-Mar. 2013 1-Apr 2-Jul 92 3-Jul 4-Jul 9-Jul 16-Jul

z DAB: days after budburst. y Samples were collected 24h, 48h, 2w and 42 after ABA applications for the first experiment; samples were collected 24h, 48h, 1w and 2w after ABA application for the second and third experiments.

105

Figure 4.1. Sampling protocol for bud freezing test, leaf/bud water content and leaf/bud sugar concentration of greenhouse-grown ‘Cabernet franc’.

106

A -4 * -6

-8 *

° -10 ( Control 50 -12 * LT ABA -14 * -16 -18 24h 48h 2w 4w Time after ABA application -4 -6 B

-8 **

C) °

( -10 * 50 -12 Control LT -14 ABA -16 -18 24h 48h 1w 2w Time after ABA application * -4 C -6 *

-8

C) °

( -10

50 -12 Control LT -14 ABA -16 -18 24h 48h 1w 2w Time after ABA application

107

78 A 76 74 72 70 Control 68 ABA 66

Watercontent FW) (% 24h 48h 2w 4w Time after ABA application

78 76 B 74 72 Control 70 68 ABA

66 Watercontent FW) (% 24h 48h 1w 2w Time after ABA application

78 C 76 74 72 Control 70 68 ABA

Watercontent FW) (% 66 24h 48h 1w 2w Time after ABA application

Figure 4.3. Effect of ABA on leaf water content of greenhouse-grown ‘Cabernet franc’ grapevines: A) Experiment 1 conducted in July 2013; B) Experiment 2 conducted in November, 2013; C) Experiment 3 conducted in July, 2014. *, **, and *** indicate significance at p ≤ 0.05, p ≤0.01, and p ≤0.001, respectively.

108

65 A 60 55 * 50 B Control 45 ** ABA

40 Watercontent FW) (% 35 24h 48h 2w 4w Time after ABA application * 70 B 65 ** 60 55 50 * Control 45 ABA

40 Watercontent FW) (% 35 24h 48h 1w 2w Time after ABA application

70 65 C 60 55 50 Control 45 ABA 40 Watercontent FW) (% 35 24h 48h 1w 2w Time after ABA application

Figure 4.4. Effect of ABA on bud water content of greenhouse-grown ‘Cabernet franc’ grapevines: A) Experiment 1 conducted in July 2013; B) Experiment 2 conducted in November, 2013; C) Experiment 3 conducted in July, 2014. *, **, and *** indicate significance at p ≤ 0.05, p ≤0.01, and p ≤0.001, respectively.

109

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