Response of Grapes to 2,4-D, , and Simulated Drift

Thesis

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

By

Scott James Wolfe, B.A.

Graduate Program in and Science

The Ohio State University

2013

Thesis Committee:

Douglas Doohan, Advisor

Joshua Blakselee

Mark Loux

Copyright by

Scott James Wolfe

2013

Abstract

In the USA, are widely used as an integral tool for management. With

genetically modified such as Ready® (glyphosate-resistant) corn and ,

herbicides that normally would have killed a crop can be used for . Over years of

use, some weed species have developed resistance to glyphosate and require novel approaches to management. New technologies, including 2,4-D and dicamba resistant crops, are one approach for corn and soybean farmers to better manage ; however, vapor or particle drift of these herbicides can damage sensitive crops such as grapes, tomatoes, and peppers. Research over the last 30 or more years has shown some of the effects of these herbicides on sensitive crops. With the impending introduction of new resistance traits in agronomic crops, the use of 2,4-D and dicamba will likely increase both in number of applications and in total volume applied per year per given area. Therefore, the severity and frequency of damage observed on sensitive crops may also increase. Grapes are an important crop in Ohio as fresh fruit and for wine production. The

wine industry attracts millions of tourists each year with a measureable positive economic effect.

With the predicted increase in use of 2,4-D and dicamba, grape growers are concerned about the

potential for damage to their vineyards. This research was conducted to better understand the risk

associated with this increased use. Grapes were extremely sensitive to 2,4-D and dicamba, to rates as low as 0.0028 kg ae/ha. A greenhouse study with varieties of grapes likely to be planted in Ohio over the next 10 years indicated that V. vinifera varieties were slightly more sensitive

ii

than hybrid varieties, showing greater injury symptoms, including leaf cupping (dicamba),

(glyphosate) and parallel venation, and fan shaped leaves (2,4-D). In a field study, the

effects of timing (pre bloom, full bloom, and post bloom) and of rate (0.028, 0.0084, and 0.0028

kg ae/ha) of simulated 2,4-D and glyphosate drift were evaluated on ‘Riesling’ vinifera grape.

Fruit yield and quality were measured in 2011 and 2012. In 2011, 2,4-D + glyphosate at 0.0084

kg ae/ha + 0.028 kg ae/ha caused effects on shoot length and visually observable injury

symptoms, regardless of application timing. Symptoms of injury included parallel venation, fan

shaped leaves, and, in more severely injured vines, death of new shoot growth. However, only

2,4-D + glyphosate at 0.028 kg ae/ha + 0.028 kg ae/ha applied pre and post bloom and 0.0084 kg ae/ha + 0.0084 kg ae/ha applied post bloom affected yield. Post bloom application of 2,4-D + glyphosate at 0.028 kg ae/ha + 0.028 kg ae/ha and 0.0084 kg ae/ha + 0.0084 kg ae/ha also resulted in a loss of yield in the year following the treatments. One year after application, some vines had died that were treated with post bloom 2,4-D + glyphosate at 0.028 kg ae/ha + 0.028 kg ae/ha and 0.0084 kg ae/ha + 0.0084 kg ae/ha. The application of the pre and full bloom 0.028 kg ae/ha + 0.028 kg ae/ha in 2012 caused much greater injury (96-100% injury) and loss of yield (100%) than in 2011. In conclusion, 2,4-D and dicamba drift may result in severe injury to grapevines; and the rate and timing of the drift can affect the severity of damage observed. The damage caused by the combination of 2,4-D and glyphosate was almost always more severe than either herbicide applied alone in the field.

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Dedication

Dedicated to my wife, Danae.

iv

Acknowledgments

I would like to thank the members of the Weed Lab in Wooster who helped with research, ratings, potting, watering, etc., Linjian Jiang, Steven “Vinny” Font, AJ Kropp, Tim Koch, Roger

Downer, Jason Parker, Andy Glaser, Erick Mvati, Connie Echaíz, Andrea Sosa, Marlon AC

Pangan, Heather McDonough, Ben Morphew, and Ashley Kulhanek. Thanks to The Enology and

Viticulture program members including David Scurlock, Todd Steiner, and Patrick Pierquet for providing their vast knowledge on vineyard management and fruit quality. Thank you especially to Greg Johns and his crew at the Ashtabula Agricultural Research Station for managing the vineyard research plot (including pruning, hilling, harvesting assistance, applications, etc.). Thank you to Mike Davault and Kesia Hartzler and their crew for assisting in greenhouse maintenance and supplies in Wooster. Thank you to Bert Bishop for invaluable SAS lessons and programming assistance. And finally, thank you to Danae (my wife) and to my parents for their advice, help, and support throughout my career.

Funding was provided by The Ohio Agricultural Research and Development SEEDS Grant

Program, The Ohio Grapes Industries Committee, and Dow AgroSciences.

v

Vita

2002 Western Reserve Academy (HS)

2006 B.A. Biology, Hiram College

2010 to present Research Assistant, Department

of Horticulture and Crop Science,

The Ohio State University

Peer Reviewed Publications

N. Gray, K. Kainec, S. Madar, L. Tomko, and S. Wolfe. “Sink or Swim? Bone as a

Mechanism for Buoyancy Control in Early Cetaceans,” The Anatomical Record, Volume

290, Issue 6 (June 2007), Pages 638-653.

Conference Proceedings

S. Wolfe. Response of grapes to simulated 2,4-D, dicamba, and glyphosate drift. 2013 Weed

Science Society of America Annual Meeting.

S. Wolfe. Response of grapes to simulated 2,4-D, dicamba, and glyphosate drift. 2013 Ohio

Grape and Wine Conference Proceedings.

Doohan, D., S. Weller, G. Kruger, S. Wolfe, L. Jiang, R. Downer, M. Gardner, R. Johnson, W.

Johnson. 2012. 2,4-D and dicamba tolerant crop systems threaten fruit and vegetable

production, and agroecosystem services. 6th International Weed Science Congress

Proceedings. P. 53.

vi

S. Wolfe. New Herbicides in 2012 for Grapes in Ohio. 2012 Ohio Grape and Wine Conference

Proceedings.

S. Wolfe. Response of grapes to simulated 2,4-D, dicamba, and glyphosate drift. 2012 Ohio

Grape and Wine Conference Proceedings.

S. Wolfe, L. Jiang, D. Scurlock, I. Dami, D. Doohan. 2011. Response of Grapes to Simulated 2,4-

D, dicamba, and glyphosate Drift. North Central Weed Science Society 2011

Proceedings.

G. Szulgit, N. Abraham, A. Brenneman, J. Collins, M. Crum, K. Davidson, G. Dottle, E. Khalil,

S. Latosky, J. Moore, K. Ottey, B. Shelton, K. Wardell, S. Wolfe. “Agents extracted from

the body wall of the sea cucumber, Cucumaria frondosa, affect mutability in the tissues

of other echinoderms as well,” 12th International Echinoderm Conference, August 2006.

Newsletters/Webpages

S. Wolfe. DriftWatch: An Overview. Ohio Produce Growers and Marketers Association TODAY.

Winter Issue 2012.

S. Wolfe. 2011. Introduction to MapMaker and Creating a Linkage Map. eXtension,

http://www.extension.org/article/32510 (last confirmed on 1/27/2012).

Fields of Study

Major Field: Horticulture and Crop Science

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Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgments...... v

Vita...... vi

List of Tables ...... ix

List of Figures ...... xii

Chapter 1: Introduction to Herbicides and Drift ...... 1

Chapter 2: Response of Five Wine Grape Varieties to 2,4-D, Dicamba, and Glyphosate Simulated

Drift ...... 21

Chapter 3: Response of ‘Riesling’ Grape to Simulated Drift of 2,4-D and Glyphosate ...... 58

References ...... 89

Appendix A: Weather Data for Ashtabula Agricultural Research Station, Kingsville, Ohio ...... 94

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List of Tables

Table 2.1: Herbicide treatments applied to five varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’

‘Vidal blanc,’ and ‘Traminette’) of vinifera and hybrid grapes grown in pots. Combination

treatments were applied to ‘Riesling’ only...... 46

Table 2.2: The effect of low doses of 2,4-D, dicamba, or glyphosate on the visual injury of five

grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). LSD, p

≤ 0.05...... 47

Table 2.3: The effect of 2,4-D, dicamba or glyphosate on the visual injury of five grape varieties

(‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). Hybrid and vinifera

results averaged across all treatments within the three hybrid and two vinifera varieties. LSD, p ≤

0.05...... 48

Table 2.4: The effect of low doses of 2,4-D, dicamba, or glyphosate on the average shoot length of five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’) to low doses of 2,4-D, dicamba, or glyphosate. LSD, p ≤ 0.05...... 49

Table 2.5: The effect of 2,4-D, dicamba, or glyphosate on the shoot length of five grape varieties

(‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). Hybrid and vinifera

results averaged across all treatments within the three hybrid and two vinifera varieties. LSD, p ≤

0.05...... 50

Table 2.6: The effect of 2,4-D, dicamba, or glyphosate on the internode length of five grape

varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). Hybrid and

ix vinifera results averaged across all treatments within the three hybrid and two vinifera varieties.

LSD, p ≤ 0.05...... 51

Table 2.7: The effect of low doses of 2,4-D, dicamba, or glyphosate on the average internode length of five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and

‘Traminette’). LSD, p ≤ 0.05...... 52

Table 2.8: The effect of 2,4-D, dicamba, with or without glyphosate treatments on ‘Riesling’ grape. LSD, p ≤ 0.05...... 53

Table 2.9: The effect of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ shoot length. LSD, p ≤ 0.05...... 54

Table 2.10: The effect of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ internode length. LSD, p ≤ 0.05...... 55

Table 2.11: The residual effects 357 and 371 DAT of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ grape vines in the greenhouse after cold storage period. LSD, p ≤ 0.05...... 56

Table 2.12: The residual effects 357 and 371 DAT of individual and combination 2,4-D, dicamba, and/or glyphosate applications on five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’

‘Vidal blanc,’ and ‘Traminette’) in the greenhouse after cold storage period. LSD, p ≤ 0.05...... 57

Table 3.1: 2,4-D and/or glyphosate tank mix treatments, rates, and application timings applied to

‘Riesling’ grapevines, Kingsville, Ohio in 2011 and 2012...... 83

x

Table 3.2: The effect of 2,4-D and glyphosate tank mixes on growth of ‘Riesling’ grapevines

following applications at pre bloom, full bloom, and post bloom growth stages in 2011. Means

separation tests are for means within a growth stage...... 84

Table 3.3: The effect of 2,4-D and glyphosate tank mixes on growth of ‘Riesling’ grapevines following applications at the pre bloom, full bloom, and post bloom growth stages in 2012.

Means separation tests are for means within a growth stage...... 85

Table 3.4: The effect of 2,4-D and glyphosate tank mixes on growth of ‘Riesling’ grapevines one

year after applications at the pre bloom, full bloom, and post bloom growth stages in 2011. Days

after treatment (DAT) are from pre bloom application in 2011...... 86

Table 3.5: Harvest measurements taken after individual treatment of ‘Riesling’ grapevines

sprayed with glyphosate and/or 2,4-D at various timings around bloom stage in 2011. *When no

berries present on a vine, value was recorded as zero...... 87

Table 3.6: Harvest measurements taken after individual treatment of ‘Riesling’ grapevines

sprayed with glyphosate and/or 2,4-D at various timings around bloom stage in 2012. *When no

berries present on a vine, value was recorded as zero...... 88

Table A.1: Weather Data for Ashtabula Agricultural Research Station, Kingsville, Ohio...... 95

xi

List of Figures

Figure 1.1: Chemical structure of 2,4-dichlorophenoxyacetic acid (2,4-D)...... 3

Figure 1.2: Chemical structure of 3,6-dichloro-2-methoxybenzoic acid (dicamba)...... 4

Figure 1.3: Chemical structure of N-(phosphonomethyl) (glyphosate)...... 5

Figure 2.1: Grapevines located in greenhouse the day of application with herbicide simulated drift

treatments...... 42

Figure 2.2: Effect of 0.0084 kg/ha 2,4-D on greenhouse grown ‘Chardonnay’ grapevine 21 DAT.

Note typical strapped (or parallel) veins (Panels 1,2,3, and 5), interveinal puckering (Panel 5), and

overall fan-shaped structure (Panels 1-5) of these younger leaves...... 43

Figure 2.3: Effect of dicamba on greenhouse grown grapevines at 21 DAT. Panels 1-2 are 0.0056

kg/ha on ‘Riesling;’ 3-4 are 0.019 kg/ha on ‘Riesling;’ 5-7 are 0.0056 kg/ha on ‘Traminette;’ 8-9 are 0.019 kg/ha on ‘Traminette.’ Note typical upward cupping (all Panels except 5) and occasional downward cupping (Panel 5)...... 44

Figure 2.4: Effect of glyphosate on greenhouse grown grapevines at 21 DAT. Panels 1-2 are

0.028 kg/ha on ‘Chardonel;’ 3-4 are 0.0084 kg/ha on ‘Vidal blanc.’ Note typical very slight interveinal chlorosis, puckering and occasional slight cupping, as in panel 2...... 45

xii

Chapter 1: Introduction to Herbicides and Drift

In 2007, the Environmental Protection Agency (EPA) estimated herbicide sales to be $15.5 billion worldwide and $5.9 billion in the USA. The most used herbicide in the is glyphosate, in large part due to the introduction of glyphosate resistant crops in the mid-1990s

(USGS 2012). The glyphosate resistance trait allows for the herbicide to be applied without damaging the crop and allows a farmer to control weeds while retaining a healthy crop.

Unfortunately, extensive use of specific herbicides, such as glyphosate, can lead and has led to herbicide resistance arising in weed species due to selection pressure (WSSA 2011). Once a weed has become resistant to a particular herbicide, the farmer is unable to control the weed using the same herbicide; and novel approaches to weed management are therefore required. One potential approach to overcome herbicide resistance is to create new herbicide resistant traits and

stack multiple herbicide resistances in a crop (Wright et al. 2010). This approach allows a farmer

to combine herbicides to control the different weed species and biotypes present in their fields.

Recently, such new traits have been generated for both 2,4-D (Wright et al. 2010) and dicamba

resistance (Behrens et al. 2007), and crops with these traits will likely be commercially launched

as early as 2014 (B. Olson, personal communications).

As new genetically modified (GM) crops expressing gene stacks conferring multiple

herbicide resistances (some incorporating 2,4-D resistance) enter the market, they raise new

concerns for specialty crop producers, specifically, grape growers. Presently, 2,4-D and dicamba

are applied primarily at times when grapevines are dormant (Volenberg 2009). With the new GM 1

crops, 2,4-D will be used during times of the year when grapes are blooming and are therefore the most sensitive to damage (White 2004) from herbicide drift. Drift is defined “as the movement of herbicide from the target area to areas where herbicide application was not intended” (Dexter

1993). Specialty crops can be extremely sensitive to 2,4-D or dicamba herbicide drift even at rates below 1% of those registered for use in row crops (Dexter 1993 and Jiang 2010). Grapes in particular have been previously demonstrated to be more sensitive to the combination of 2,4-D and glyphosate than to either herbicide alone (although glyphosate alone causes significantly less injury than 2,4-D) (Bhatti et al. 1997).

2,4-D is the common name for the chemical 2,4-dichlorophenoxyacetic acid (Gervais

2008). 2,4-D is a broadleaf herbicide, meaning that it generally kills dicots, but not typically monocots. 2,4-D is the most used herbicide in the world, but only the third most used in United

States (Anonymous 2012). 2,4-D is a synthetic that is absorbed through the leaf tissue and translocated in the auxin transport stream to both root and shoot meristems, resulting in unregulated growth and ultimately death if applied at a sufficient rate (Walker 2011). The herbicide was developed by the British during World War II in an attempt to increase yield in , , rice, and other cereal crops, and was first released commercially in 1946 by

Sherwin-Williams (Burnside 1996). In 2005, 2,4-D was re-registered in the United States by the

EPA (Gervais 2008). 2,4-D has several different formulations that include sodium, potassium, or salts; a new choline ; and a 2-ethylhexyl ester formulation (Gervais 2008). These formulations vary greatly in volatility with the ester being the most volatile and the new choline salt exhibiting the lowest volatility (Anonymous 2011). Longstroth, in 2008, and White, in 2004, 2

both described the effects of 2,4-D on grapes, detailed the effects of warm temperatures on

increasing 2,4-D volatility (and drift), and recommended use of the amine formula to reduce the

risk of volatility. 2,4-D is commonly applied at a labeled rate of 0.84 kilograms acid equivalent

per hectare (kg ae/ha) (Anonymous 2013c) a rate selected as the 1x rate for the experiments

reported in this thesis.

Figure 1.1: Chemical structure of 2,4-dichlorophenoxyacetic acid (2,4-D).

Dicamba is the common name for the chemical 3,6-dichloro-2-methoxybenzoic acid

(Bunch et al. 2012). Dicamba is an organochloride derivative of benzoic acid, and functions as an herbicide typically used to control broadleaf perennials and improve control of annual weeds in grain crops (Appleby et al. 2002). Dicamba causes unregulated growth, and when applied at a sufficiently high rate, results in plant death (Bunch et al. 2012). Dicamba was first registered in the United States in 1967 with the Environmental Protection Agency (EPA). As described above

with glyphosate, some weed species have developed resistance to dicamba (Cranston et al. 2001).

3

Dicamba is commonly applied at a labeled rate of 0.561 kilograms acid equivalent per hectare

(Anonymous 2013d), a rate set as the 1x for these experiments.

Figure 1.2: Chemical structure of 3,6-dichloro-2-methoxybenzoic acid (dicamba).

Glyphosate is the common name for N-(phosphonomethyl)glycine. Glyphosate is a systemic herbicide, which means that it is translocated throughout the plant (Miller 2010).

Glyphosate inhibits 5-enolpyruvylshikimate-3- (EPSP) enzyme involved in the synthesis of the amino acids , , and (Miller 2010). Due to this mode of action, glyphosate is only effective on actively growing plant tissues (Miller 2010).

Glyphosate was originally registered in 1974 and reregistered in 1993 by under the trade name Roundup®, with the expiring in 2000 (Miller 2010). ® crops, carrying the glyphosate resistance trait, were first introduced in 1996 (Miller 2010). Glyphosate is currently the most widely used herbicide in the United States (EPA). Due to the heavy use of

4 glyphosate in GM crops, there are now over 20 states reporting weed species that have developed resistance to glyphosate and now require new management practices (Anonymous, 2011c).

Glyphosate is commonly applied at an EPA registered rate of 0.84 kilograms acid equivalent per hectare, which was selected as the 1x rate for these experiments.

Figure 1.3: Chemical structure of N-(phosphonomethyl)glycine (glyphosate).

The current generation of 2,4-D resistance crops were generated via the insertion of a bacterial aryloxyalkanoate dioxygenase gene (isolated by Dow AgroSciences) into maize,

Arabidopsis, and soybean (Wright et al. 2010). Arabidopsis plants generated using these methods were resistant to 2,4-D as well as the herbicides and (Wright et al. 2010).

According to Dow AgroSciences, 2,4-D resistance will be paired (or stacked) with genes providing resistance to other herbicides, such as glyphosate and ; and, potentially, with other currently available traits (Anonymous 2011). Stacking of traits will allow transgenic plants to exhibit resistance to multiple herbicides. 2,4-D resistance will likely be available in corn in 5

2014 followed by soybean and in a few years (B. Olson, personal communication). In

addition to herbicide resistant transgenic crop lines, Dow AgroSciences will also be releasing a

new formulation of 2,4-D. In this new formula, 2,4-D is present as a choline salt reputed to have reduced volatility (Anonymous 2011).

Similarly to the strategy employed by Dow AgroSciences, Monsanto engineered dicamba resistance through the insertion of a gene from the bacterium Pseudomonas

maltophilia (strain DI-6), which had been demonstrated to metabolize dicamba (Behrens et al.

2007). The dicamba resistance gene will be stacked with other herbicide resistance genes, in a

manner similar to the 2,4-D resistance trait described above (Anonymous 2013e). Crops that have been engineered to include the dicamba resistance gene include soybean, corn, cotton, and canola

(Anonymous 2013e). Monsanto has not announced a release date at this time, but it will most likely be within a few years in order to remain competitive with Dow AgroScience’s 2,4-D resistant Enlist crops (Anonymous 2011).

In this study, sensitive crops are defined as any crop that does not exhibit resistance to a specific herbicide that is either directly applied or drifts onto the crop. Some crops exhibit varying levels of herbicide sensitivity based on their developmental stage (White 2004). Grapes, for example, are not sensitive to 2,4-D while dormant during the winter, but can be extremely sensitive at bloom stage (White 2004). Almost all broadleaf crops as well as garden and ornamental plants are sensitive to 2,4-D and dicamba (Anonymous 2013). 2,4-D and dicamba

sensitive crops grown in Ohio include grapes, tomatoes, peppers, and cabbage (Jiang 2010). 6

In 2008, the Ohio Grape Industry commissioned a report to better understand the

economic and agronomic impact of the grape industry in Ohio. The report was developed by

MFK Research and several of the key statistics include that there were 124 Ohio wineries (a 65%

increase since 1999), 769 hectares of vineyards producing 4,292,660 L of wine annually. The

economic impact to Ohio was calculated to be $582.8 million per year, drawing 2.2 million

tourists to Ohio wineries in 2008. There were approximately 4,100 employees related to the wine

industry (including wineries, tour companies, restaurants, lodging, etc.). Ohio is the eleventh

largest wine producing state by liters bottled and the ninth largest by area in grape production.

In 2011 in Ohio, there were 1,497,340 hectares of corn (of which 71% was genetically

modified (GM) including glyphosate resistance) and 1,780,620 hectares of (of which

86% was GM, again including glyphosate resistance) planted (Anonymous 2011b). The 769

hectares of vineyard described above equal about 0.002% of the corn and soybean hectares and

many are located in areas of extensive corn and soybean productions. The high use of glyphosate

GM crops can serve as an indication of how many farmers will adopt the new 2,4-D and dicamba

resistant crops discussed above. This indication can be made since the farmers currently using

GM crops will be more likely to continue using new GM crops whereas farmers opposed to GM

crops currently, will be less likely to switch to GM crops in the future.

Due to the large areas in Ohio currently farmed with GM crops, vineyards are likely to be located near areas where new 2,4-D and dicamba resistant crops will be planted and will therefore 7

be at risk of experiencing 2,4-D or dicamba drift. Since the timing of 2,4-D herbicide

applications will change with the introduction of the new generation of transgenic crops that will

tolerate the herbicide, vineyards will very likely be exposed to herbicide drift at novel times

throughout the growing season, including times when the grapevines are at sensitive growth

stages. Where previously 2,4-D application has been largely limited in corn and soybean to a burn

down early in the growing season when grapevines are dormant, it will likely now be used at

multiple times throughout the growing season (in order to optimize weed control and since the

crop will tolerate the applications), including times when the vines are more susceptible (such as bloom stage) (White 2004). For example, soybean seeding is often not completed until June and these new application timings would come after seeding - the time of the year when grape vines are in their most sensitive growth stage, bloom (White 2004). Although previous studies have investigated the effects of 2,4-D and dicamba on grapes (Stewart et al. 1947 and 1952; Ogg et al.

1991; Comes et al. 1984; Bhatti et al. 1996 and 1997; Dami et al. 2002; White 2004; Volenberg

2009; Jiang et al. 2010; Bondada 2011; Hellman et al. 1999; Castro et al. 2005; Al-Khatib et al.

1993; Longstroth 2008), the anticipated increase in 2,4-D and dicamba use (both quantities and applications), makes it imperative to more precisely define the effects of these herbicides on grape physiology throughout the plant life-cycle. The objective of Chapter Two (Response of

Five Wine Grape Varieties to 2,4-D, Dicamba, and Glyphosate Simulated Drift) was to investigate the sensitivity of grape cultivars to 2,4-D, dicamba and glyphosate. The objective of

Chapter Three (Response of ‘Riesling’ Grapes in the Vineyard to Various Timings and Rates of

Simulated Drift of 2,4-D and Glyphosate) was to quantify the sensitivity of established grapevines to various rates and timings of simulated drift. The knowledge gained from these 8

experiments, will hopefully allow better varietal recommendations to grape growers planting

vineyards near potential drift sources. Recommendations could also potentially be made to row crop herbicide applicators to avoid spraying 2,4-D or dicamba at specific times, in order to reduce the chance of drift damage to the vineyards during particularly sensitive stages of the grape life- cycle.

Linjian Jiang (2010) performed initial experiments in the greenhouse to test the response of three representative vinifera, hybrid, and American varieties to 2,4-D and dicamba. The

vinifera chosen was ‘Cabernet Franc’, the hybrid was ‘Chambourcin’, and the American was

‘Concord’. Preliminary data indicated that the combination of 2,4-D or dicamba with glyphosate

caused more severe injury to the vines than individual herbicide treatments at similar rates (Jiang

2010). Damage symptoms were visible on vines treated with 2,4-D at as low a rate as 0.0028 kg

ae/ha of the rate labeled for row crops.

Shortly after the introduction of 2,4-D in the United States in 1946, Stewart et al. (1947

and 1952) investigated its potential use for the control of wild grapevines in remote areas of

California. They observed that the ester formulation of 2,4-D in a 27% solution was effective at

killing all grapevines less than 3 meters tall and even killed some vines that were as tall as 9 meters (Stewart et al. 1947 and 1952).

Research on the effects of 2,4-D in the vineyard continued throughout the 1980s up to the present, and has greatly increased the state-of-knowledge in the field (Ogg et al. 1991; Comes et 9

al. 1984; Bhatti et al. 1996 and 1997; Dami et al. 2002; White 2004; Volenberg 2009; Jiang et al.

2010; Bondada 2011; Hellman et al. 1999; Castro et al. 2005; Al-Khatib et al. 1993; Longstroth

2008). Dami et al. (2002) published an extension bulletin describing 2,4-D damage symptoms in

grapes. Typical damage appears within two days of 2,4-D deposition and includes “fan-shaped leaves with sharp points at leaf margins, epinasty (downward bending of leaves), leaf strapping

(parallel venation) with deep sinuses, puckered leaf surfaces with constricted veins that may be slightly chlorotic” (Dami 2002). Dicamba typically causes leaf cupping and a marginal band of restricted growth on the leaf (Dami 2002). Glyphosate damage is different from both 2,4-D and dicamba damage in that it first appears as chlorosis of the tissue near the shoot meristem which can lead to necrosis and loss of the shoot apical meristem. The bulletin also details the sensitivity

(with symptoms ranging from “no injury” to “severe”) of 27 grape varieties to 2,4-D, including the ‘Chardonel,’ ‘Traminette,’ and ‘Vidal blanc’ varieties used in this research (Dami 2002).

Similar results were reported by Iowa State University in 2003 (Anonymous 2003).

In 1984, Comes et al., showed that ‘Concord’ grapes sprayed with 1 part per million

(ppm) of 2,4-D developed moderate symptoms; but the injury had no effect on growth rate, yield, or fruit quality. This study also assayed leaf tissue for 2,4-D residue however no 2,4-D was detected above the limit of detection of 0.05 ppm. Ogg, et al., (1991), studied the long term effects of 2,4-D exposure by applying 2,4-D annually to the same vines for four years which resulted in as much as an 85% reduction in yield, as well as reduced berries per cluster. After three years of 2,4-D treatment, a slightly higher pH was detected along with higher soluble solids in fruit from the vines that showed moderate to severe damage symptoms (Ogg et al. 1991). The 10

symptoms and effects noted in this study did not persist for more than a year after the treatments

ceased, and the authors concluded that vines with only slight damage from 2,4-D would not experience yield reduction. Again, residual 2,4-D was not detected in plant tissues at levels above the limit of detection of 0.05 ppm. Since the completion of initial studies of 2,4-D damage in grapes, application of current generation analytical techniques has allowed the detection of 2,4-D residues on leaf surfaces for up to 72 hours post deposition (personal communication, A. Murphy and J. Blakeslee). As plant damage is rarely observed in this time frame, however, these data indicate that improved sampling/detection methods are needed in order to capture and preserve herbicide residues allowing the determination of the source of crop damage.

In an interview published on the website www.reignofterroir.com (2011), Dr. Susan

Kegley describes the ongoing legal issues surrounding herbicide drift on vineyards and the

difficulties of proving in court the source of damaging drift events. Volenberg (2009) contends the source of 2,4-D drift may not be just applications in agricultural fields, but could also include treatments of lawns, right of ways, golf courses, etc. Volenberg recommends that vineyard operators become aware of the cropping systems and other potential problem areas within 1.6 km of their vineyard so that they can adjust their practices and communicate with their neighbors to prevent possible drift events.

At Washington State University, Al-Khatib et al., (1993) and Bhatti et al., (1996 and

1997) tested numerous application rates and measured several variables (including injury, cane weights, shoot growth, leaf area, and/or internode length) on the effects of 2,4-D, as well as other 11 herbicides (varied between each study) on ‘Lemberger’ grapes (vinifera variety). The authors determined that newly planted vines were much more sensitive to 2,4-D than established vines.

Of the herbicides tested, the most severe response was caused by 2,4-D. Bhatti, et al., (1996) evaluated the effect of repeated applications of 2,4-D, chlorsulfuron, tribenuron, and thifensulfuron (at weekly intervals, up to three treatments per vine) and concluded that 2,4-D at

11.20 grams per hectare (1/100 the labeled rate) caused the most severe injury of the treatments tested. In this study, the 2,4-D damage observed lasted the entire season and resulted in reduced pruning weights (Bhatti et al. 1996). Further, the greater the number of times the vines were exposed to 11.20 g/ha of 2,4-D, the more adversely the growth was affected, including greater injury and reduced pruning weights (Bhatti et al. 1996). In 1997, Bhatti et al., reported that 2,4-D plus glyphosate caused more damage than 2,4-D alone, and that glyphosate alone caused little damage compared to other treatments (which included chlorsulfuron, thifensulfuron, 2,4-D, glyphosate, , and 2,4-D + glyphosate at 1/100, 1/33, 1/10, and 1/3 of established maximum rates recommended for use in wheat or fallow). As the severity of symptoms observed increased, shoot growth, leaf area, internode length, and dry cane weights all decreased (Bhatti et al. 1997). The authors also concluded that 2,4-D or 2,4-D + glyphosate exposure “during the fall can adversely affect growth of grapevines the following spring” (Bhatti et al. 1997). Hellman et al. (1999) reported that grapes at the flowering (bloom) stage were particularly sensitive to damage and that drift at this time would result in reduced fruit set and/or delayed fruit ripening. White (2004) also described that grapevines experienced the greatest damage at bloom stage and early fruit set stages (roughly late May and June in Iowa) which correspond with the time farmers spray corn, fence lines, and pastures with dicamba products 12

(White 2004). The author recommended a 0.8 kilometer radius buffer or no spray area around sensitive crops for 2,4-D applications and a 1.6 km radius for dicamba (White 2004).

Jiang et al. (2010) discussed the introduction of the new generation of 2,4-D and dicamba resistance traits in corn and soybean and concluded that these new technologies will potentially cause an increase in drift opportunities as well as new timings of drift. To potentially alleviate damage to grapes from 2,4-D or dicamba drift, it has been proposed that transgenic grapes resistant to these herbicides be developed, as discussed in a Food Engineering and Ingredients article (2008) describing “Improved Chancellor” herbicide resistant grapes. These new transgenic grapes are currently undergoing testing to determine their safety for consumption in products such as juice and wine.

The main pitfall of all simulated drift experiments is that they cannot replicate all of the variables of a real drift incident. There is some level of debate as to whether or not a simulated drift experiment accurately represents or is useful in helping to predict the effects of real drift events. In the case of grapes, numerous papers have been published that discuss rates used to test the effects of 2,4-D (Bhatti et al. 1997 and 1996; Volenberg 2009) and concluding that these simulated rates match real drift in terms of the levels of damage observed. Several of the rates selected for this study match those tested in the past and can therefore be approximately compared.

13

It is currently not feasible to test all of the variables that may greatly affect the severity of damage a grower might experience from drift. These other variables include, but not limited to: landscape/topography, distance from source of drift, meteorological conditions, wind breaks around vineyards, etc. These variables can all potentially change the amount of drift that occurs and change the severity of the symptoms observed in a vineyard.

The other main limitation to this study is the limited number of varieties of grapes tested.

Although this study evaluated the sensitivity of five varieties in the greenhouse and one variety in the field, but included no American varieties (out of a possible 158 varieties offered for sale by

Double A Vineyards, a major supplier of nursery stock to Ohio vineyards). The five varieties of

grape selected for the greenhouse are highly recommended for planting, but do not completely

represent all varieties or types of grapes that can be grown successfully in Ohio.

The research reported in this thesis will help provide a better understanding of the effects

of 2,4-D on certain varieties of grapes and how application timing plays a role in the effects,

aiding in identification of potential damage that could occur in growers’ fields. The results

presented will also help extension specialists recommend varieties to plant in or near possible

drift sites in contrast to varieties more suited to planting in isolated areas.

Grape growers are currently concerned that anticipated increases in both quantities and

timings of 2,4-D, dicamba, and glyphosate application, will result in increased risk of drift. These

growers, therefore want to know the potential effects of drift on the quality and yield of damaged 14

vines. The field experiment reported in this thesis (Chapter 3) helps address the relationship

between 2,4-D injury symptoms, yield, and quality. This study re-evaluates previous observations that damaged vines recover completely the year following damage. Ultimately, for growers, this work will help them identify varieties advantageous to plant in locations where risk of 2,4-D or dicamba drift is high, understand the significance of and be able to identify damage caused by 2,4-D and dicamba drift, and understand possible impacts on their final product

(grapes, juice, or wine). For researchers and extension specialists, the findings allow for a better understanding of the sensitivity of grapevines at various growth stages and variation in varietal resistances to herbicides. These data may also help researchers and extension specialists develop recommendations for management practices when drift has occurred; and guide interactions with herbicide companies, allied industries, and grain farmers to better communicate issues that the new herbicide technologies will bring, increasing the understanding of all parties associated.

15

Literature Cited

Anonymous. 2003. 2003 Wine Grape Cultivar Trial. Iowa State University. Online.

http://viticulture.hort.iastate.edu/research/pdf/03grapewine04report.pdf Accessed June 2,

2013.

Anonymous. 2011. Enlist Weed Control System. Dow AgroSciences. M09-137-006 (02/11) BR

010-42158 DAAGDHTA0076

Anonymous. 2011b. National Agricultural Statistics Service. United States Department of

Agriculture. Online. http://www.nass.usda.gov Accessed June 2, 2013.

Anonymous. 2011c. Resistance. Weed Science Society of America (WSSA). Online.

http://www.wssa.net/Weeds/Resistance/index.htm Accessed June 2, 2013.

Anonymous. 2012. Industry Task Force II on 2,4-D Research Data. Online. http://www.24d.org

Accessed June 2, 2013.

Anonymous. 2013a. Glyphosate-resistant weed problem extends to more species, more farms.

Farm Industry News. Online. http://farmindustrynews.com/herbicides/glyphosate-resistant-

weed-problem-extends-more-species-more-farms Accessed June 2, 2013.

Anonymous. 2013b. Ontario Ministry of , Food, and Rural Affairs. Online. 2,4-D.

Excerpt from Guide to Weed Control. Online.

http://www.omafra.gov.on.ca/english/crops/facts/notes/24d.htm Accessed June 2, 2013.

Anonymous. 2013c. Weedar 64 Herbicide Label. Nufarm Inc.

Anonymous. 2013d. Banvel Herbicide Label. Arysta LifeScience North America, LLC.

16

Anonymous 2013e. Roundup Ready 2 Xtend Soybeans. Monsanto Company. Online.

http://www.monsanto.com/products/Pages/roundup-ready-2-xtend-soybeans.aspx Accessed

June 2, 2013.

Al-Khatib, K., Parker, R., Fuerst, E.P. 1993. Wine Grape (Vitis vinifera L.) Response to

Simulated Herbicide Drift. Weed Technology, Vol. 7, No. 1, pp. 97-102.

Appleby, A.P., Müller, F., Carpy, S. 2002. Weed Control. Ullmann's Encyclopedia of Industrial

Chemistry, Wiley-VCH, Weinheim.

Behrens, M.R., Mutlu, N., Chakraborty, S., Dumitru, R., Jiang, W.Z., LaVallee, B.J., Herman,

P.L., Clemente, T.E., Weeks, D.P. 2007. Dicamba Resistance: Enlarging and Preserving

Biotechnology-Based Weed Management Strategies. Science, 316: 1185-1188.

Bhatti, M., Al-Khatib, K., Parker, R. 1997. Wine grape (Vitis vinifera) response to fall exposure

of simulated drift from selected herbicides. Weed Technology, Volume 11:532-536.

Bhatti, M.A., Al-Khatib, K., Parker, R. 1996. Wine Grape (Vitis vinifera) Response to Repeated

Exposure of Selected Sulfonylurea Herbicides and 2,4-D. Weed Technology, Vol. 10, No. 4,

pp. 951-956.

Bondada, B.R. 2011. Micromorpho-Anatomical Examination of 2,4-D Phytotoxicity in Grapevine

(Vitis vinifera L.) Leaves. Journal of Plant Growth Regulation. 30:185-198.

Bunch, T.R., Gervais, J. A., Buhl, K., Stone, D. 2012. Dicamba Technical Fact Sheet; National

Pesticide Information Center, Oregon State University Extension Services. Online.

http://npic.orst.edu/factsheets/dicambaTech.pdf Accessed June 2, 2013.

Burnside, O.C. 1996. The History of 2,4-D and Its Impact on Development of the Discipline of

Weed Science in the United States. United States Department of Agriculture. No. 1-PA-96. 17

Castro, A.J., Carapito, C., Zorn, N., Magne, C., Leize, E., Van Dorsselaer, A., Clement, C. 2005.

Proteomis analysis of grapevine (Vitis vinifera L.) tissues subjected to herbicide stress.

Journal of Experimental Botany. Vol. 56, No. 421, pages 2783-2795.

Comes, R.D., Marquis, L.Y., Kelley, A.D. 1984. Response of Concord Grapes (Vitis labrusca) to

2,4-D in Irrigation Water. Weed Science, Vol. 32, No. 4, pp. 455-459.

Cranston, H.J., Kern, A.J., Hackett, J.L., Miller, E.K., Maxwell, B.D., Dyer, W.E. 2001. Dicamba

resistance in kochia. Weed Science, 49:164-170.

Dami, I., Masiunas, J., Bordelon, B. 2002. Herbicide Drift and Injury to Grapes. Southern Illinois

University, Bulletin C1382.

Dexter, A.G. 1993. Herbicide Spray Drift. A-657. North Dakota State University and the

University of Minnesota. Online. http://www.ag.ndsu.edu/pubs/plantsci/weeds/a657w.htm

Accessed June 2, 2013.

Food Engineering and Ingredients. 2008. Herbicide-resistant grape could revitalize Midwest

America’s wine industry. Food Engineering and Ingredients. Volume 33, Issue 4, page 44.

Gervais, J. A., Luukinen, B., Buhl, K., Stone, D. 2008. 2,4-D Technical Fact Sheet; National

Pesticide Information Center, Oregon State University Extension Services.

http://npic.orst.edu/factsheets/2,4-DTech.pdf Accessed June 2, 2013.

Hellman, E., Fults, J. 1999. Preventing Phenoxy Herbicide Damage to Grape Vineyards. Oregon

State University Extension Service, EM8737.

Jiang, L., Scurlock, D., Dami, I., Doohan, D. 2010. Manage Herbicide Drift Damage to

Grapevines. The Ohio State University Extension Bulletin.

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Kegley, S. 2011. Dr. Susan Kegley on Herbicide Drift. March 27, 2011 (interview). Online.

www.reignofterroir.com Accessed June 2, 2013.

Longstroth, M. 2008. Think Twice Before Using 2,4-D. Michigan State University Extension

Van Buren County.

MFK Research. 2008. The Economic Impact of Wine and Wine Grapes on the State of Ohio.

Commissioned by the OGIC. http://www.tasteohiowines.com/downloads/pdfs/ Accessed June

2, 2013.

Miller, A., Gervais, J. A., Luukinen, B., Buhl, K., Stone, D. 2010. Glyphosate Technical Fact

Sheet. National Pesticide Information Center, Oregon State University Extension Services.

http://npic.orst.edu/factsheets/glyphotech.pdf. Accessed June 2, 2013.

Mortensen, D.A., Egan, F., Maxwell, B.D., Ryan, M.R., Smith, R.G. 2012. Navigating a Critical

Juncture for Sustainable Weed Management. BioScience, Vol. 62 No. 1, pp. 75-84.

Ogg, Jr., A.G., Ahmedullah, M.A., Wright, G.M. 1991. Influence of Repeated Applications of

2,4-D on Yield and Juice Quality of Concord Grapes (Vitis labruscana) Weed Science, Vol.

39, No. 2, pp. 284-295.

OMAFRA Staff. 2002. Growth Stages of Grapevines. Ontario Ministry of Agriculture and Food.

Online. http://www.omafra.gov.on.ca/english/crops/facts/grapestages.htm Accessed June 2,

2013.

Roberson, R. Online. Glyphosate resistant weeds a reality for cotton growers.

http://southeastfarmpress.com/glyphosate-resistant-weeds-reality-cotton-growers Accessed

June 2, 2013.

19

Stewart, W.S., Gammon, C. 1947. Fog Application of 2,4-D to Wild Grape and Other Plants.

American Journal of Botany, Vol. 34, No. 9, pp. 492-496.

Stewart, W.S., Gammon, C., Hield, H.Z. 1952. Deposit of 2,4-D and Kill of Wild Grape Vines by

Helicopter Spray Application. American Journal of Botany, Vol. 39, No. 1, pp. 1-5.

United States Geological Survey (USGS). 2012. Glyphosate Herbicide Found in Many

Midwestern Streams, Antibiotics Not Common. Online.

http://toxics.usgs.gov/highlights/glyphosate02.html Accessed June 2, 2013.

Volenberg, D. 2009. Vineyard IPM Scouting Report for week of June 15, 2009. University of

Wisconsin-Extension Door County and Peninsular Agricultural Research Station. Sturgeon

Bay, WI.

Walker, T. 2011. Avoiding 2,4-D Injury to Grapevines. Colorado State University Extension.

White, M.L. 2004. Iowa: Viticulture (Grapes) 101. Iowa State Extension. Integrated Crop

Management Conference.

Wright, T., Shan, G., Walsh, T., Lira, J., Cui, C., Song, P., Zhang, M., Arnold, N., Lin, G., Yau,

K., Russell, S., Cicchillo, R., Peterson, M., Simpson, D., Zhou, N., Ponsamuel, J., Zhang, Z.

2010. Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate

dioxygenase . PNAS 107: 20240-20245.

20

Chapter 2: Response of Five Wine Grape Varieties to 2,4-D, Dicamba, and Glyphosate

Simulated Drift

Scott Wolfe, Roger Downer, Imed Dami, and Douglas Doohan*

Incidents involving sensitive crop injury caused by herbicide spray drift are expected to increase

in the near future as field crops with resistance to 2,4-D and dicamba are commercialized. Grape

is considered to be particularly sensitive to drift of auxinic herbicides; and the rapidly expanding

grape industry in Ohio is particularly vulnerable because many vineyards are in close proximity

to grain fields infested with glyphosate-resistant weeds or fields where the new 2,4-D or dicamba

resistant crops may be planted. The greenhouse study was conducted to determine resistance of

five grape varieties important to the Ohio wine industry to low, drift simulating, doses of 2,4-D

(0.028-0.0028 kg/ha), dicamba (0.019-0.0019 kg/ha) and glyphosate (0.028-0.0028 kg/ha).

Vinifera varieties were slightly more sensitive than hybrid varieties to the rates of herbicide tested. Resistance ranked from most to least sensitive was ‘Chardonnay’ ≥ ‘Riesling’ ≥

‘Chardonel’ ≥ ‘Vidal blanc’ ≥ ‘Traminette.’ Effects on visual injury, shoot length, and internode

length were observed three days after treatment (DAT) and, in the case of 2,4-D and dicamba,

became progressively worse up to 42 DAT. The 0.028 kg/ha rate of 2,4-D killed some vines.

* Current Graduate Student, Research Associate, Associate Professor, and Professor, respectively, Department of Horticulture and Crop Science, The Ohio State University/Ohio Agriculture Research and Development Center (OSU/OARDC), Wooster, Ohio 44691. Corresponding author’s e-mail: [email protected]. 21

Overall, 2,4-D caused the most severe damage (39-69%) 42 DAT, with dicamba causing 8-53% injury, and glyphosate causing minimal damage (2-3%). Growth, including internode and shoot length, was reduced with the higher rates of each herbicide and some vines died as a culmination of the reduction in growth caused by the treatments. Injury symptoms included fan-shaped, parallel veined younger leaves (2,4-D), leaf cupping (dicamba), and chlorosis (glyphosate).

Nomenclature: glyphosate; 2,4-D; dicamba; vinifera grape, Vitis vinifera L.; French American hybrid grape, Vitis sp.

Key Words: Glyphosate, 2,4-D, dicamba, vinifera, hybrid, simulated drift.

22

In the next few years, crops with 2,4-D and dicamba resistance traits will likely be commercially available (B. Olson, personal communications). These resistance traits were created in response to the growing problem presented by glyphosate resistant weeds (WSSA 2011) and to provide farmers with additional weed management tools. However, these new herbicide resistance traits will potentially present specialty crop growers with problems, since specialty crops can be extremely sensitive to 2,4-D and dicamba drift at rates below 1% of the labeled rate for row crops

(Dexter 1993 and Jiang 2010). Drift is defined “as the movement of herbicide from the target area to areas where herbicide application was not intended” (Dexter 1993). Grapes are one of the many specialty crops that can be very sensitive to 2,4-D or dicamba drift (Dami 2002 and Bhatti et al. 1997). The injury symptoms caused by 2,4-D that are most often observed on grape include fan-shaped leaves, strapping (or parallel veins), zigzag shoot growth, epinasty (downward bending of leaves or other plant parts), and poor fruit set (Dami 2002). The injury symptoms observed with dicamba include upward or downward cupping of the leaves caused by partial restricted growth (Dami 2002).

In 2011, there were 3,277,960 hectares of corn and soybean in Ohio of which 79% was planted in genetically modified crops (GMO). In 2008, there were only 769 hectares of vineyards in Ohio, which increases the possibility of some vineyards being surrounded by vast expanses of land dedicated to corn or soybean. It is expected by industry and farmers that the commercialization of the 2,4-D and dicamba resistance traits will be widely adopted and therefore the hectares of soybean and corn around vineyards will likely have these resistance traits and the

23

probability of drift occurring will increase due to the increased number of applications of these

herbicides on the resistant crops.

Previous work has been done to show the effects of 2,4-D and dicamba on grapes

(Stewart et al. 1947 and 1952; Ogg et al. 1991; Comes et al. 1984; Bhatti et al. 1996 and 1997;

Dami et al. 2002; White 2004; Volenberg 2009; Jiang et al. 2010; Bondada 2011; Hellman et al.

1999; Castro et al. 2005; Al-Khatib et al. 1003; Longstroth 2008), but with the introductions of

the new resistant trait crops and the increased probability of spray-drift related injury occurring, it is necessary to reevaluate the sensitivity of grapes to 2,4-D and dicamba. In particular this study aims to better understand the relationships between each herbicide and the differences in sensitivity between grape varieties at various rates. The objective of this research was to identify these differences in sensitivity to low doses of 2,4-D, dicamba, and glyphosate (individually and in combination) among several currently recommended varieties of grapes. It is anticipated that, with the knowledge gained from this experiment, recommendations for the most herbicide-

tolerant varieties can be made to growers planting vineyards near potential drift sources.

24

Materials and Methods

Effect of 2,4-D, dicamba, and glyphosate on five varieties of wine grape. Five varieties were

selected based on predictions of those most likely to be planted in Ohio in the next few years (I.

Dami and D. Scurlock, personal communications) including two vinifera (‘Riesling’ and

‘Chardonnay’) and three hybrids (‘Chardonel,’ ‘Traminette,’ and ‘Vidal blanc’). These varieties

also enabled a comparison between the response of hybrids and vinifera as previous work

indicated that vinifera were more sensitive to 2,4-D and dicamba (L. Jiang, personal

communication). Vines were obtained dormant from Double A Vineyards1 and were planted in

May 2011 in 7.57 L pots using a general purpose peat-based growing medium (ProMix BX2).

Vines were numbered and randomly assigned to a replication and treatment using a random

number generator. Each replication was placed on one bench. Replication was by bench since

there was a temperature gradient across the greenhouse (benches were perpendicular to the

gradient). At 42 DAT, only the internode length had a significant replication effect.

Table 2.1 is a list of the 16 herbicide treatments evaluated. The experimental design was

a randomized complete block with five replications. The experiment was performed one time.

Treatments 1-10 were applied to all five varieties and treatments 11-16 were applied to

‘Riesling,’ one of the five varieties. Herbicides at their 1x labeled rate, were as follows: 2,4-D at

0.84 kg ae/ha, glyphosate at 0.84 kg ae/ha, and dicamba at 0.56 kg ae/ha. Rates used in the

treatments were equivalent to 1/30, 1/100, and 1/300 of these labeled rates for each herbicide.

Treatments were applied using a track-suspended laboratory spray system, located at the Ohio 25

Agricultural Research and Development Center (OARDC) in Wooster, Ohio. Nozzles were

TeeJet 8002 Flat Spray Tips4 with a spray pressure of 275.8 kPa and each nozzle delivering 0.757

L per minute (LPM). The speed of application was 4.8 km/h. The lowest rate of each herbicide

was applied first followed by successively greater rates and the spray boom was completely

flushed with 2 liters of water between different herbicides. Herbicides were applied when the

vines had new leaf growth on approximately 4-6 internodes (see Fig. 2.1). Potted vines were

placed on the floor under the spray track and sprayed with a single pass. Ten minutes after

spraying, each vine was moved to the greenhouse. Conditions in the greenhouse were maintained

at ~27◦C during the day and ~18◦C at night. These conditions were occasionally exceeded during midday, but with no detrimental effect on the grapevines. Vines were pruned to a single shoot throughout the experiment and clusters were removed in order to eliminate the variable of the number of shoots produced by the vine and to replicate the common practice of removing clusters from young vines, respectively.

Vine injury was qualitatively measured using an injury scale, along with shoot length and internode length starting on the day of treatment and thereafter at 3, 7, 14, 21, 28, and 42 days after treatment (DAT). Vine injury, based on chlorosis, epinasty, leaf deformation, and overall growth stunting, was assessed on a 0 – 100 scale, where 0 was no visible injury and 100 was death of the shoot. Shoot length was measured using a flexible tape measuring from the base of the shoot (located on the trunk) to the tip of the terminal leaf. The first three distal internode lengths were measured using a digital caliper3 accurate to 0.01 mm.

26

At the end of September 2011 vines were removed from the greenhouse and placed in storage at a temperature of 2.2 C. In March 2012, they were returned to the greenhouse and identical measurements and ratings to those described above were performed to assess any residual damage from herbicides applied the previous year.

Data were analyzed using SAS for Windows, version 9.25. The general linear model

(proc glm) was used to analyze the data as a factorial treatment. For each variable measured,

interactions between variety, herbicide, and herbicide rate were tested as well as all main effects.

The lengths of the three distal internodes were treated as sub-samples. Means were compared

using pairwise comparisons (LSD). All results reported had p ≤ 0.05.

27

The effect of 2,4-D, dicamba, glyphosate, and combinations of glyphosate with 2,4-D or

dicamba on ‘Riesling.’ To evaluate sensitivity of grapes to combinations of glyphosate with

either 2,4-D or dicamba, ‘Riesling’ vines were also treated with combinations of 2,4-D, dicamba

and glyphosate (Table 2.1, i.e., all 16 treatments). The methods for growing, spraying, rating, and

data analysis for these combination treatments were the same as described for the individual

treatments. All individual and combination herbicide treatments on ‘Riesling’ were analyzed

together as a factorial treatment design. Means comparisons were done pairwise (LSD, p ≤ 0.05).

Interactions between herbicide and herbicide rate were tested as well as the main effects of the herbicide or herbicide rate for each variable measured.

28

Results and Discussion

Effect of 2,4-D, dicamba, and glyphosate on five varieties of wine grape. 2,4-D, dicamba, and glyphosate treatments caused similar injury symptoms on each of the five varieties. The pattern of variation in varietal response to the herbicides was established at the beginning of the experiment and persisted throughout the period of evaluation. There were no interactions, but main effects of herbicide and herbicide rate on each variable were significant.

At all evaluation times after treatment application, there was an interaction between variety and treatment for injury. Injury symptoms were sufficient to rate by 3 DAT at which time they ranged from 4% for glyphosate or dicamba at 0.0028 kg/ha and 0.0019 kg/ha, respectively, to 17% for 2,4-D at 0.028 kg/ha. Injury symptoms caused by 2,4-D and dicamba increased progressively over the course of the experiment. In contrast, the greatest injury with glyphosate was 14 DAT (7-8% for all rates). Glyphosate treated vines showed partial recovery by 42 DAT

(3-6% injury, Table 2.2). The rate of injury increase with 2,4-D or dicamba was greatest during the first 7 DAT; but in all cases injury continued to increase as time progressed and was greatest at 42 DAT.

Averaged across varieties, 2,4-D caused more injury than dicamba or glyphosate with a maximum mean response of 66% injury at 42 DAT (Table 2.2). Symptoms of 2,4-D injury were similar to those described by Dami (2002) including parallel veins, fan-shaped leaves, shortened internodes, and reduction of new growth (resulting in shorter shoots) (Fig. 2.2). Effects were 29

mostly observed in the youngest growth, but at the highest rates (0.028 kg/ha) lower leaves were

progressively affected with the passage of time, most likely due to the death of the youngest

growth. By 42 DAT some vines were dead (100% injury). The effect of dicamba was not as

severe as that of 2,4-D. Injury ranged from 10 to 47% (42 DAT) as the rate of the herbicide

increased (Table 2.2). Symptoms caused by dicamba consisted of upward cupping of the younger

leaves, with very occasional downward cupping (Fig. 2.3). Glyphosate caused only slight injury

that could be detected visually as minor chlorosis typically on mature leaves. Averaged across varieties the response varied from 3 to 6% but was not significantly different from the control

(Table 2.2). The only symptom was chlorosis, typically on the oldest leaves that had been exposed directly to the herbicide at the time of treatment (Fig. 2.4).

Injury increased in response to increasing rates of 2,4-D or dicamba (Table 2.2). Dicamba

at 0.019 kg/ha resulted in 47% injury (42 DAT) and 10% with the 0.0019 kg/ha rate. A similar

trend was noted with 2,4-D; 66% injury with 0.028 kg/ha and 29% with 0.0084 kg/ha. The

response to 0.0084 kg/ha of 2.4-D (29%) was anomalous and we do not have an explanation..

The effect of glyphosate on grapes was similar to the control, confirming the relatively greater

tolerance of grape to drift of this herbicide (Dami 2002).

The severity of injury symptoms observed due to 2,4-D, dicamba, and glyphosate

differed among grape varieties. This was apparent at 3 DAT, continued throughout the time

course of the experiment, and was most pronounced 42 DAT (Table 2.3). Averaged across

herbicide treatments, ‘Traminette’ was least sensitive and exhibited the least injury symptoms at 30

42 DAT; whereas, the ‘Chardonnay’ and ‘Riesling’ (both vinifera varieties) exhibited the greatest

intensity of injury symptoms (Table 2.3). At forty-two DAT, the average response of

‘Traminette’ was 19% (Table 2.3), similar to that of ‘Vidal blanc’ (22%) but less than that of

‘Riesling’ (27%), ‘Chardonnay’ (28%), and ‘Chardonel’ (24%). Averaged across all treatments,

vinifera were more sensitive to 2,4-D and dicamba than were hybrids. Comparing the two

vinifera to the three hybrids, injury was consistently higher beyond 3 DAT and was 7% greater at

28 DAT (Table 2.3). These results concur with those of Dami (2002) and Jiang (2010) who also

reported that vinifera varieties were more sensitive than hybrids.

Growth, as measured by shoot and internode length was affected by the various

treatments. For shoot length the main effects were application rate, herbicide, and variety of

grape. Shoot length differed among varieties and there was an interaction of herbicide and variety 42 DAT. Shoot length was a function of variety and differed at 0 DAT, but the variation in lengths increased among the varieties by 42 DAT in response to herbicides (Table 2.4).

Averaged across herbicide treatments, at 42 DAT ‘Chardonnay’ (119 cm) had longer shoots than

‘Riesling’ (107 cm), ‘Traminette’ (102 cm), and ‘Chardonel’ (91 cm), but not longer than ‘Vidal

blanc’ (110 cm, Table 2.5). ‘Chardonel’ had the shortest shoots at 91 cm at 42 DAT. Overall, the

vinifera had longer average shoot lengths over the duration of the evaluations (Table 2.5). At 42

DAT vines treated with 0.028 kg/ha of 2,4-D (22 cm), 0.019 kg/ha of dicamba (87 cm), and

0.0084 kg/ha of 2,4-D (88 cm) had shorter shoots than vines subjected to the other treatments

(Table 2.4). Control vines and those treated with 0.0028 kg/ha glyphosate, and 0.0028 kg/ha 2,4-

D had the longest shoots; 136 cm, 138 cm, and 124 cm, respectively 42 DAT (Table 2.4). 31

Herbicides also affected internode length. ‘Chardonnay’ and ‘Vidal blanc’ had the shortest

internodes (13.9 and 16.9 mm, respectively) compared to ‘Riesling’ (17.5 mm), ‘Traminette’

(20.2 mm), and ‘Chardonel’ (18.1 mm) (Table 2.6). For internode length, the main effects were

again application rate, herbicide, and variety of grape. The vinifera overall had shorter internode

lengths than the hybrids over the duration of the evaluations (Table 2.6). 2,4-D at 0.028 kg/ha

reduced internode length (2.7 mm at 42 DAT); otherwise, vine internode length did not differ

from that of vines in the control (21.7 mm) (Table 2.7).

2,4-D at 0.028 kg/ha was by far the most damaging treatment in every variable measured

regardless of variety (Tables 2.2, 2.4, and 2.7). This treatment resulted in eight incidents of vine

death. In contrast, glyphosate had little effect on any of the variables measured except for

growth. Dicamba caused less severe injury than that observed with 2,4-D treatments, but greater

than that caused by glyphosate. Although all injury ratings were within 10% of each other at 42

DAT, vinifera varieties exhibited slightly greater injury symptoms than hybrid varieties when the

response for each type was averaged across all herbicide treatments (Table 2.3). This observation

concurs with work by Jiang who reported that hybrids were less sensitive to 2,4-D and glyphosate injury than American or vinifera varieties (personal communication). Injury symptoms were

apparent at rates as low as 0.0028 kg/ha (2,4-D or glyphosate) and 0.0019 kg/ha (dicamba) (Table

2.2). Shoot length data correlated with the overall injury symptoms only at 42 DAT due to the difference in time (compared to the internode length and visual injury) it took the whole shoot to respond to the highest rate of 2,4-D (Table 2.4). At early evaluations, only the youngest leaves were affected and there was minimal effect on shoot length. 32

The effect of 2,4-D, dicamba, glyphosate, and combinations of glyphosate with 2,4-D or dicamba on ‘Riesling’ grape. 2,4-D, dicamba, and glyphosate treatments in combination had similar morphological effects on ‘Riesling’ as those observed on other varieties (Fig. 2.2-2.4). At

42 DAT, the addition of glyphosate to 2,4-D or dicamba increased chlorosis; but otherwise the injury symptoms, shoot length, and internode length observed in the combination treatments did not differ from those caused by individual treatments of 2,4-D or dicamba at similar rates and evaluation timings (Table 2.8-2.10).

At 42 DAT 2,4-D alone at 0.028 kg/ha was the most damaging to ‘Riesling’ with 69% injury (Table 2.8). Nine of the sixteen treatments resulted in vines that had visual injury between

39-57%. Dicamba at 0.0019 kg/ha and all individual glyphosate treatments caused less than 8% injury (similar to the control), (Table 2.8). Growth, shoot and internode length, was affected the greatest by the high rate 2,4-D treatment. Shoot length at 42 DAT ranged from 9% of the control with vines treated with 0.028 kg/ha 2,4-D to 101% of the control with vines treated with 0.0028 kg/ha glyphosate (Table 2.9). At 42 DAT, internode length averaged from 3% of the control with the 0.028 kg/ha 2,4-D treatment to 113% of the control with the 0.0056 kg/ha dicamba plus

0.0084 kg/ha glyphosate treatment.

33

Residual damage in the year following 2,4-D, dicamba, and glyphosate simulated drift on five varieties of grape. The only residual damage observed in the year following the simulated drift treatments was dead vines resulting from treatment induced injury. Specifically, many vines treated with 0.028 kg/ha rates of 2,4-D or 2,4-D + glyphosate did not survive. The majority of the vines, even those displaying significant injury the previous year, showed little (less than 6% visual injury) or no damage the year after treatment. This indicates that damaged vines are likely to recover from damage that does not complete kill the vine (100% visual injury). In the two rating timings (357 and 371 DAT), there was no variation in residual injury between the five varieties tested. The 0.028 kg/ha 2,4-D and 2,4-D + glyphosate killed several vines and so had greater residual injury (average 34% and 20% injury score, respectively, at both 357 and 371

DAT) than all other treatments (0% injury for all other treatments at both 357 and 371 DAT).

Shoot length of ‘Chardonel’ (93 cm) was significantly shorter at 371 DAT compared to the other four varieties (which ranged from 109 – 118 cm). At 371 DAT, vines treated with 0.028 kg/ha 2,4-D and 2,4-D + glyphosate had significantly shorter shoot lengths on average (69% and

89% of the control, respectively) due to the death of several vines within this treatment which reduced the average. Treatments other than the 0.028 kg/ha 2,4-D or 2,4-D + glyphosate caused vines to have shoot lengths ranging from 102-118% of the control at 371 DAT. The internode length showed reduction in only the 0.028 kg/ha 2,4-D + glyphosate (62% of the control at 371

DAT, not significant) due to the death of several vines. All other treatments caused vines to have similar internode length at 371 DAT, ranging from 77% (0.0028 kg/ha glyphosate) to 93% of the control (0.028 kg/ha glyphosate). There was variation in internode length between the varieties 34

with the ‘Vidal blanc’ having the shortest internode lengths (13.3 mm) and the ‘Chardonnay’

having the longest (16.9 mm).

All treatments and rates resulted in injury symptoms that were observed at three days

after the treatments were applied. The 2,4-D caused the most severe injury across the rates

applied. The dicamba treatments resulted in severe injury symptoms, but all vines recovered

from the injury and showed very little residual damage approximately one year after the

application of the treatments. Glyphosate alone resulted in minimal chlorosis and all vines

treated with glyphosate alone recovered completely, some within 42 days. The combinations of

2,4-D with glyphosate or dicamba with glyphosate resulted in similar injury as either the 2,4-D or dicamba alone, but with slightly greater incidence of chlorosis symptoms. In conclusion, the vinifera varieties (‘Riesling’ and ‘Chardonnay’) were slightly more sensitive to the herbicide treatments than the hybrid varieties (‘Vidal blanc,’ ‘Traminette,’ and ‘Chardonel’). Further research needs to be done for other varieties, both in the greenhouse and in the field, in order to expand upon the findings in this work and previous work by others. Research also needs to be done to better understand each of the different commercially available formulations of 2,4-D, dicamba, or glyphosate that may have different effects on the severity of damage in grapes, since each formulation varies in adjuvants, , and other additives.

35

Acknowledgments

Funding was provided by The Ohio Agricultural Research and Development Center SEEDS

Grant Program, The Ohio Grapes Industries Committee, and Dow AgroSciences. Thank you to

Linjian Jiang, Steven “Vinny” Font, AJ Kropp, Tim Koch, Roger Downer, Jason Parker, Andy

Glaser, Erick Mvati, Connie Echaíz, Andrea Sosa, Marlon AC Pangan, Heather McDonough, Ben

Morphew, Ashley Kulhanek, David Scurlock, Todd Steiner, Patrick Pierquet, Greg Johns, Mike

Davault, Kesia Hartzler, and Bert Bishop.

36

Source of Materials

1Double A Vineyards, Inc., 10277 Christy Road, Fredonia, NY 14063.

2Premier Tech Horticulture, Ltd., 1 Avenue Premier, Riviere-du-Loup, Quebec, G5R 6C1

Canada.

3Fisher Scientific, 300 Industry Drive, Pittsburgh, PA 15275.

4TeeJet Technologies, North Avenue and Schmale Road, P.O. Box 7900, Wheaton, IL

60187-7901.

5SAS 9.2, SAS Institute Inc. 100 SAS Campus Drive, Cary, NC 27513.

37

Literature Cited

Anonymous. 2003. 2003 Wine Grape Cultivar Trial. Iowa State University. Online.

http://viticulture.hort.iastate.edu/research/pdf/03grapewine04report.pdf Accessed June 2,

2013.

Anonymous. 2013a. Glyphosate-resistant weed problem extends to more species, more farms.

Farm Industry News. Online. http://farmindustrynews.com/herbicides/glyphosate-resistant-

weed-problem-extends-more-species-more-farms Accessed June 2, 2013.

Al-Khatib, K., Parker, R., Fuerst, E.P. 1993. Wine Grape (Vitis vinifera L.) Response to

Simulated Herbicide Drift. Weed Technology, Vol. 7, No. 1, pp. 97-102.

Appleby, A.P., Müller, F., Carpy, S. 2002. Weed Control. Ullmann's Encyclopedia of Industrial

Chemistry, Wiley-VCH, Weinheim.

Behrens, M.R., Mutlu, N., Chakraborty, S., Dumitru, R., Jiang, W.Z., LaVallee, B.J., Herman,

P.L., Clemente, T.E., Weeks, D.P. 2007. Dicamba Resistance: Enlarging and Preserving

Biotechnology-Based Weed Management Strategies. Science, 316: 1185-1188.

Bhatti, M., Al-Khatib, K., Parker, R. 1997. Wine grape (Vitis vinifera) response to fall exposure

of simulated drift from selected herbicides. Weed Technology, Volume 11:532-536.

Bhatti, M.A., Al-Khatib, K., Parker, R. 1996. Wine Grape (Vitis vinifera) Response to Repeated

Exposure of Selected Sulfonylurea Herbicides and 2,4-D. Weed Technology, Vol. 10, No. 4,

pp. 951-956.

Bondada, B.R. 2011. Micromorpho-Anatomical Examination of 2,4-D Phytotoxicity in Grapevine

(Vitis vinifera L.) Leaves. Journal of Plant Growth Regulation. 30:185-198. 38

Castro, A.J., Carapito, C., Zorn, N., Magne, C., Leize, E., Van Dorsselaer, A., Clement, C. 2005.

Proteomis analysis of grapevine (Vitis vinifera L.) tissues subjected to herbicide stress.

Journal of Experimental Botany. Vol. 56, No. 421, pages 2783-2795.

Comes, R.D., Marquis, L.Y., Kelley, A.D. 1984. Response of Concord Grapes (Vitis labrusca) to

2,4-D in Irrigation Water. Weed Science, Vol. 32, No. 4, pp. 455-459.

Cranston, H.J., Kern, A.J., Hackett, J.L., Miller, E.K., Maxwell, B.D., Dyer, W.E. 2001. Dicamba

resistance in kochia. Weed Science, 49:164-170.

Dami, I., Masiunas, J., Bordelon, B. 2002. Herbicide Drift and Injury to Grapes. Southern Illinois

University, Bulletin C1382.

Dexter, A.G. 1993. Herbicide Spray Drift. A-657. North Dakota State University and the

University of Minnesota. http://www.ag.ndsu.edu/pubs/plantsci/weeds/a657w.htm Accessed

June 2, 2013.

Food Engineering and Ingredients. 2008. Herbicide-resistant grape could revitalize Midwest

America’s wine industry. Food Engineering and Ingredients. Volume 33, Issue 4, page 44.

Hellman, E., Fults, J. 1999. Preventing Phenoxy Herbicide Damage to Grape Vineyards. Oregon

State University Extension Service, EM8737.

Jiang, L., Scurlock, D., Dami, I., Doohan, D. 2010. Manage Herbicide Drift Damage to

Grapevines. The Ohio State University Extension Bulletin.

Kegley, S. 2011. Dr. Susan Kegley on Herbicide Drift. March 27, 2011. Online.

www.reignofterroir.com Accessed June 2, 2013.

Longstroth, M. 2008. Think Twice Before Using 2,4-D. Michigan State University Extension

Van Buren County. 39

MFK Research. 2008. The Economic Impact of Wine and Wine Grapes on the State of Ohio.

Commissioned by the OGIC. Online. http://www.tasteohiowines.com/downloads/pdfs/

Accessed June 2, 2013.

Mortensen, D.A., Egan, F., Maxwell, B.D., Ryan, M.R., Smith, R.G. 2012. Navigating a Critical

Juncture for Sustainable Weed Management. BioScience, Vol. 62 No. 1, pp. 75-84.

Ogg, Jr., A.G., Ahmedullah, M.A., Wright, G.M. 1991. Influence of Repeated Applications of

2,4-D on Yield and Juice Quality of Concord Grapes (Vitis labruscana). Weed Science, Vol.

39, No. 2, pp. 284-295.

Roberson, R. 2006. Glyphosate resistant weeds a reality for cotton growers. Online.

http://southeastfarmpress.com/glyphosate-resistant-weeds-reality-cotton-growers Accessed

June 2, 2013.

Stewart, W.S., Gammon, C. 1947. Fog Application of 2,4-D to Wild Grape and Other Plants.

American Journal of Botany, Vol. 34, No. 9, pp. 492-496.

Stewart, W.S., Gammon, C., Hield, H.Z. 1952. Deposit of 2,4-D and Kill of Wild Grape Vines by

Helicopter Spray Application. American Journal of Botany, Vol. 39, No. 1, pp. 1-5.

United States Geological Survey (USGS). 2012. Glyphosate Herbicide Found in Many

Midwestern Streams, Antibiotics Not Common. Online.

http://toxics.usgs.gov/highlights/glyphosate02.html. Accessed June 2, 2013.

Volenberg, D. 2009. Vineyard IPM Scouting Report for Week of June 15, 2009. University of

Wisconsin-Extension Door County and Peninsular Agricultural Research Station. Sturgeon

Bay, WI.

40

Weed Science Society of America (WSSA). 2011. Resistance. Online.

http://www.wssa.net/Weeds/Resistance/index.htm Accessed June 2, 2013.

White, M.L. 2004. Iowa: Viticulture (Grapes) 101. Iowa State Extension. Integrated Crop

Management Conference. December 2, 2004.

Wright, T., Shan, G., Walsh, T., Lira, J., Cui, C., Song, P., Zhang, M., Arnold, N., Lin, G., Yau,

K., Russell, S., Cicchillo, R., Peterson, M., Simpson, D., Zhou, N., Ponsamuel, J., Zhang, Z.

2010. Robust Crop Resistance to Broadleaf and Grass Herbicides Provided By

aryloxyalkanoate dioxygenase Transgenes. PNAS 107: 20240-20245.

41

Figure 2.1: Grapevines located in greenhouse the day of application with herbicide simulated drift treatments.

42

Figure 2.2: Effect of 0.0084 kg/ha 2,4-D on greenhouse grown ‘Chardonnay’ grapevine 21 DAT.

Note typical strapped (or parallel) veins (Panels 1,2,3, and 5), interveinal puckering (Panel 5), and overall fan-shaped structure (Panels 1-5) of these younger leaves.

43

Figure 2.3: Effect of dicamba on greenhouse grown grapevines at 21 DAT. Panels 1-2 are 0.0056 kg/ha on ‘Riesling;’ 3-4 are 0.019 kg/ha on ‘Riesling;’ 5-7 are 0.0056 kg/ha on ‘Traminette;’ 8-9 are 0.019 kg/ha on ‘Traminette.’ Note typical upward cupping (all Panels except 5) and occasional downward cupping (Panel 5).

44

Figure 2.4: Effect of glyphosate on greenhouse grown grapevines at 21 DAT. Panels 1-2 are

0.028 kg/ha on ‘Chardonel;’ 3-4 are 0.0084 kg/ha on ‘Vidal blanc.’ Note typical very slight

interveinal chlorosis, puckering and occasional slight cupping, as in panel 2.

45

Herbicide Rate (kg ae/ha) 2,4-D 0.0028 2,4-D 0.0084 2,4-D 0.028 dicamba 0.0019 dicamba 0.0056 dicamba 0.019 glyphosate 0.0028 glyphosate 0.0084 glyphosate 0.028 2,4-D + glyphosate 0.0028 + 0.0028 2,4-D + glyphosate 0.0084 + 0.0084 2,4-D + glyphosate 0.028 + 0.028 dicamba + glyphosate 0.0019 + 0.0028 dicamba + glyphosate 0.0056 + 0.0084 dicamba + glyphosate 0.019 + 0.028

Table 2.1: Herbicide treatments applied to five varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’

‘Vidal blanc,’ and ‘Traminette’) of vinifera and hybrid grapes grown in pots. Combination treatments were applied to ‘Riesling’ only.

46

% Injury Herbicide Rate (kg/ha) 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 4 E 6 D 15 BC 20 C 27 C 37 C 2,4-D 0.0084 5 CD 13 C 14 C 21 C 27 C 29 D 2,4-D 0.028 17 A 31 A 40 A 56 A 59 A 66 A dicamba 0.0019 4 E 2 E 5 D 7 D 9 D 10 E dicamba 0.0056 6 C 6 D 12 C 24 C 33 BC 36 C dicamba 0.019 15 B 15 B 18 B 31 B 39 B 47 B glyphosate 0.0028 4 E 2 E 8 D 6 D 6 DE 6 EF glyphosate 0.0084 5 CDE 4 E 7 D 6 D 5 DE 3 F glyphosate 0.028 5 CDE 4 E 7 D 6 D 5 DE 3 EF

Table 2.2: The effect of low doses of 2,4-D, dicamba, or glyphosate on the visual injury of five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). LSD, p

≤ 0.05.

47

% Injury Variety 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT ‘Traminette’ 5 C 7 B 10 C 14 B 16 C 19 C ‘Vidal blanc’ 7 AB 9 AB 13 B 16 B 18 BC 22 BC ‘Chardonel’ 7 AB 8 B 12 BC 16 B 22 AB 24 AB ‘Riesling’ 6 BC 9 A 15 A 21 A 24 A 27 A ‘Chardonnay’ 8 A 10 A 13 AB 21 A 25 A 28 A Hybrids 6 8 11 16 18 22 Vinifera 7 9 14 21 25 27

Table 2.3: The effect of 2,4-D, dicamba or glyphosate on the visual injury of five grape varieties

(‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). Hybrid and vinifera results averaged across all treatments within the three hybrid and two vinifera varieties. LSD, p ≤

0.05.

48

Rate Shoot Length (% of control) Herbicide (kg/ha) 0 DAT 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 100 AB 96 AB 102 A 100 A 92 AB 94 AB 91 AB 2,4-D 0.0084 95 AB 88 AB 86 AB 77 BC 66 DE 62 D 65 D 2,4-D 0.028 71 C 70 C 57 C 42 D 28 F 19 E 16 E dicamba 0.0019 95 AB 90 AB 88 AB 87 ABC 82 BC 83 BC 87 BC dicamba 0.0056 95 AB 92 AB 88 AB 83 BC 79 CD 79 C 81 C dicamba 0.019 86 BC 84 BC 79 B 73 C 63 E 60 D 64 D glyphosate 0.0028 100 AB 96 AB 97 A 100 A 99 A 100 A 101 A glyphosate 0.0084 93 AB 96 AB 91 AB 89 AB 82 BC 82 BC 86 BC glyphosate 0.028 105 A 100 A 97 A 92 AB 84 BC 85 BC 88 BC

Table 2.4: The effect of low doses of 2,4-D, dicamba, or glyphosate on the average shoot length of five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’) to low doses of 2,4-D, dicamba, or glyphosate. LSD, p ≤ 0.05.

49

101 113 91 C 102 B 107 B 119 A 110 AB 42 DAT

of five

78 89 83 B 84 B 67 C 83 B 95 A 28 DAT

hoot length hoot

64 76 70 B 67 B 57 C 71 B 81 A 21 DAT

56 66 61 B 51 C 62 B 70 A 56 BC 14 DAT ≤ 0.05.

Shoot (cm) Length 49 55 46 C 57 A LSD, p LSD, 51 BC 50 BC 53 AB 7 DAT

results averaged across all treatments within the the within treatments all across averaged results

43 49 40 C 50 A 45 BC 45 AB 48 AB varieties. 3 DAT D, dicamba, or glyphosate on the s on the glyphosate or dicamba, D, - vinifera

vinifera 38 42 36 C 43 A 38 BC 41 AB 0 DAT 39 ABC Hybrid and and Hybrid (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and and blanc,’ ‘Vidal ‘Chardonel,’ ‘Chardonnay,’ (‘Riesling,’

.

The effect of 2,4 of effect : The

2. 5 hybrid and two hybrid hree Variety ‘Traminette’ blanc’ ‘Vidal ‘Chardonel’ ‘Riesling’ ‘Chardonnay’ Hybrids Vinifera Table varieties grape ‘Traminette’) t

50

18.4 15.7 13.9 B 20.2 A 18.1 A 17.5 A 42 DAT 16.9 AB

22.6 18.8 18.6 B 18.7 B 18.9 B 26.7 A 28 DAT 22.5 AB

nternode length of five length nternode m) 14.6 16.8 13.4 B 17.1 A 17.3 A 21 DAT 16.1 AB 15.7 AB

14.9 13.0 13.9 B 13.9 B 13.2 B 12.7 B 16.9 A 14 DAT ≤ 0.05.

21.7 19.1 Internode Length (m Length Internode LSD, p LSD, 19.0 B 19.2 B 22.2 A 21.7 A 7 DAT 21.2 AB

results averaged across all treatments within the the within treatments all across averaged results

22.9 17.5 D, dicamba, or glyphosate on the i on the glyphosate or dicamba, D, 18.3 B 16.8 B varieties. 24.2 A 22.8 A 21.8 A 3 DAT - vinifera

vinifera 51.1 48.3 50.4 B 45.6 C 49.8 B 57.1 A 0 DAT 46.9 BC Hybrid and and Hybrid (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and and blanc,’ ‘Vidal ‘Chardonel,’ ‘Chardonnay,’ (‘Riesling,’

.

: The effect of 2,4 6

hybrid and two hybrid hree Variety ‘Traminette’ blanc’ ‘Vidal ‘Chardonel’ ‘Riesling’ ‘Chardonnay’ Hybrid Vinifera Table 2. varieties grape ‘Traminette’) t

51

Rate Internode Length (% of control) Herbicide (kg/ha) 0 DAT 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 95 AB 63 C 49 DE 99 A 58 CD 85 BC 78 AB 2,4-D 0.0084 88 B 87 B 59 DE 93 AB 64 CD 67 CD 78 AB 2,4-D 0.028 78 C 96 AB 90 AB 16 D 7 E 13 E 12 C dicamba 0.0019 95 AB 57 C 83 BC 74 BC 61 CD 83 BCD 83 AB dicamba 0.0056 95 AB 63 C 60 D 65 C 56 CD 79 BCD 90 AB dicamba 0.019 90 B 68 C 48 E 79 ABC 53 D 62 D 72 B glyphosate 0.0028 101 A 102 A 94 AB 70 C 84 AB 107 A 89 AB glyphosate 0.0084 103 A 87 B 77 C 86 ABC 85 AB 96 AB 101 A glyphosate 0.028 101 A 66 C 83 BC 85 ABC 74 BC 80 BCD 94 AB

Table 2.7: The effect of low doses of 2,4-D, dicamba, or glyphosate on the average internode length of five grape varieties (‘Riesling,’ ‘Chardonnay,’ ‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’). LSD, p ≤ 0.05.

52

% Injury Rate Herbicide (kg/ha) 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 3 EFGH 7 E 14 CDEF 25 DE 32 BC 45 BC 2,4-D 0.0084 6 E 12 D 16 CDE 28 CD 38 B 39 CD 2,4-D 0.028 16 C 36 A 59 A 69 A 71 A 69 A dicamba 0.0019 1 GH 2 FGH 6 FGH 9 FG 6 D 8 EF dicamba 0.0056 2 FGH 6 EF 13 DEFG 28 CD 42 B 49 BC dicamba 0.019 17 C 18 C 22 C 38 BC 45 B 53 ABC glyphosate 0.0028 4 EFG 1 GH 6 FGH 4 FG 2 D 3 F glyphosate 0.0084 5 EF 5 EFG 8 EFGH 6 FG 4 D 2 F glyphosate 0.028 5 EF 5 EFG 7 FGH 6 FG 4 D 3 F 0.0028 2,4-D + + 4 EFG 6 EF 12 DEFG 29 CD 36 B 41 BCD glyphosate 0.0028 0.0084 2,4-D + + 10 D 6 EF 13 DEFG 29 CD 36 B 46 BC glyphosate 0.0084 0.028 2,4-D + + 29 A 25 B 34 B 47 B 51 B 57 AB glyphosate 0.028 0.0019 dicamba + + 5 EF 4 EFGH 5 GH 13 EF 15 CD 25 DE glyphosate 0.0028 0.0056 dicamba + + 6 E 4 EFGH 11 DEFG 25 DE 33 BC 47 BC glyphosate 0.0084 0.019 dicamba + + 25 B 16 CD 18 CD 33 CD 45 B 51 BC glyphosate 0.028

Table 2.8: The effect of 2,4-D, dicamba, with or without glyphosate treatments on ‘Riesling’ grape. LSD, p ≤ 0.05.

53

Rate Shoot Length (% control) Herbicide (kg/ha) 0 DAT 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 94 ABC 92 ABCD 99 AB 91 ABC 79 ABCD 71 BC 65 CD 2,4-D 0.0084 103 AB 100 ABC 97 AB 81 ABCDE 64 CDE 54 CDE 49 DE 2,4-D 0.028 69 C 67 D 56 C 32 F 14 G 6 G 9 F dicamba 0.0019 74 BC 71 CD 72 BC 67 CDE 64 CDE 66 BCD 75 BC dicamba 0.0056 100 ABC 103 AB 102 AB 89 ABCD 86 ABC 84 AB 86 ABC dicamba 0.019 88 ABC 83 ABCD 78 ABC 65 CDE 54 DEF 44 DEF 45 DE glyphosate 0.0028 100 ABC 94 ABCD 100 AB 105 A 107 A 101 A 101 A glyphosate 0.0084 76 BC 77 BCD 79 ABC 75 BCDE 75 BCDE 73 BC 82 ABC glyphosate 0.028 111 A 110 A 105 A 96 AB 91 ABC 86 AB 84 ABC 0.0028 2,4-D + + 88 ABC 85 ABCD 83 ABC 88 ABCD 88 ABC 83 AB 77 BC glyphosate 0.0028 0.0084 2,4-D + + 92 ABC 88 ABCD 91 AB 79 ABCDE 71 CDE 65 BCD 65 CD glyphosate 0.0084 0.028 2,4-D + + 99 ABC 91 ABCD 86 ABC 55 EF 31 FG 21 FG 33 E glyphosate 0.028 0.0019 dicamba + + 100 ABC 100 ABC 103 AB 102 AB 101 AB 101 A 93 AB glyphosate 0.0028 0.0056 dicamba + + 84 ABC 89 ABCD 89 AB 83 ABCDE 82 ABC 82 AB 83 ABC glyphosate 0.0084 0.019 dicamba + + 88 ABC 82 ABCD 82 ABC 62 DE 51 EF 36 EF 34 E glyphosate 0.028

Table 2.9: The effect of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ shoot length. LSD, p ≤ 0.05.

54

Rate Internode Length (% control) Herbicide (kg/ha) 0 DAT 3 DAT 7 DAT 14 DAT 21 DAT 28 DAT 42 DAT 2,4-D 0.0028 90 ABCD 55 DE 32 GH 120 A 56 ABC 89 ABCD 43 BC 2,4-D 0.0084 79 CD 81 BCD 39 FGH 126 A 84 AB 56 ABCDE 67 AB 2,4-D 0.028 76 D 100 AB 71 BC 0 B 0 D 0 E 3 C dicamba 0.0019 81 CD 56 DE 64 BCD 83 A 62 ABC 82 ABCD 87 AB dicamba 0.0056 95 ABCD 65 DE 27 H 79 A 58 ABC 54 ABCDE 69 AB dicamba 0.019 83 BCD 69 CDE 43 EFGH 111 A 60 ABC 40 CDE 75 AB glyphosate 0.0028 91 ABCD 126 A 81 B 91 A 97 A 96 ABC 96 AB glyphosate 0.0084 91 ABCD 99 AB 71 BC 116 A 106 A 98 ABC 110 A glyphosate 0.028 102 A 66 CDE 67 BC 99 A 73 AB 81 ABCD 72 AB 0.0028 2,4-D + + 90 ABCD 95 BC 59 CDE 112 A 101 A 112 AB 73 AB glyphosate 0.0028 0.0084 2,4-D + + 93 ABCD 54 DE 58 CDEF 91 A 78 AB 106 ABC 74 AB glyphosate 0.0084 2,4-D + 0.028 + 94 ABCD 50 E 68 BC 23 B 20 CD 23 DE 43 BC glyphosate 0.028 0.0019 dicamba + + 95 ABC 80 BCD 63 BCD 117 A 91 AB 124 A 95 AB glyphosate 0.0028 0.0056 dicamba + + 90 ABCD 68 CDE 56 CDEF 84 A 74 AB 113 AB 113 A glyphosate 0.0084 dicamba + 0.019 + 94 ABCD 48 E 47 DEFG 98 A 47 BCD 47 BCDE 58 ABC glyphosate 0.028

Table 2.10: The effect of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ internode length. LSD, p ≤ 0.05.

55

Internode Length (% Rate Visual Injury (% control) Shoot Length (% control) Herbicide control) (kg/ha) 357 DAT 371 DAT 357 DAT 371 DAT 357 DAT 371 DAT 2,4-D 0.0028 0 B 0 B 114 ABC 109 AB 65 BC 78 AB 2,4-D 0.0084 0 B 0 B 91 BCD 102 AB 64 BC 84 AB 2,4-D 0.028 34 A 34 A 75 D 69 C 54 C 89 AB dicamba 0.0019 0 B 0 B 118 AB 116 A 63 BC 86 AB dicamba 0.0056 0 B 0 B 111 ABC 110 AB 61 BC 79 AB dicamba 0.019 0 B 0 B 101 ABCD 107 AB 64 BC 88 AB glyphosate 0.0028 0 B 0 B 114 ABC 107 AB 83 ABC 77 AB glyphosate 0.0084 0 B 0 B 108 ABC 106 AB 81 ABC 80 AB glyphosate 0.028 0 B 0 B 101 ABCD 102 AB 85 ABC 93 A 0.0028 2,4-D + + 0 B 0 B 116 ABC 115 AB 72 ABC 81 AB glyphosate 0.0028 0.0084 2,4-D + + 0 B 0 B 100 ABCD 110 AB 79 ABC 84 AB glyphosate 0.0084 2,4-D + 0.028 + 20 AB 20 AB 88 CD 89 BC 50 C 62 B glyphosate 0.028 0.0019 dicamba + + 0 B 0 B 128 A 123 A 81 ABC 84 AB glyphosate 0.0028 0.0056 dicamba + + 0 B 0 B 119 AB 118 A 106 A 82 AB glyphosate 0.0084 dicamba + 0.019 + 0 B 0 B 110 ABC 109 AB 78 ABC 81 AB glyphosate 0.028

Table 2.11: The residual effects 357 and 371 DAT of individual and combination 2,4-D, dicamba, and/or glyphosate applications on ‘Riesling’ grape vines in the greenhouse after cold storage period. LSD, p ≤ 0.05.

56

Shoot Length Internode Length % Injury (cm) (mm) Variety 357 371 357 371 357 371 DAT DAT DAT DAT DAT DAT ‘Traminette’ 2 A 1 A 72 AB 114 A 17.1 A 15.6 AB ‘Vidal blanc’ 6 A 6 A 68 B 109 A 13.3 C 13.3 B ‘Chardonel’ 6 A 6 A 60 C 93 B 15.6 AB 16.4 AB ‘Riesling’ 3 A 3 A 78 A 118 A 16.6 AB 14.5 AB ‘Chardonnay’ 2 A 2 A 73 AB 111 A 14.5 BC 16.9 A Hybrids 4 4 66 104 16.4 16.0 Vinifera 4 4 73 113 14.8 14.9

Table 2.12: The residual effects 357 and 371 DAT of individual and combination 2,4-D, dicamba, and/or glyphosate applications on five grape varieties (‘Riesling,’ ‘Chardonnay,’

‘Chardonel,’ ‘Vidal blanc,’ and ‘Traminette’) in the greenhouse after cold storage period. LSD, p

≤ 0.05.

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Chapter 3: Response of ‘Riesling’ Grape to Simulated Drift of 2,4-D and Glyphosate

Scott Wolfe, Roger Downer, Imed Dami, and Douglas Doohan†

2,4-D and dicamba resistant crops will aid corn and soybean farmers to improve weed

management. However, 2,4-D drift from the target area can damage sensitive crops such as

grapes, tomatoes, and peppers. With the impending introduction of 2,4-D resistance traits, the

total use of the herbicide will increase; and use at non-traditional times of the year, when

specialty crops are in sensitive growth stages, will also increase, with a corresponding increase in

the severity and frequency of drift-induced damage to sensitive crops. Grapes are extremely

sensitive to auxinic herbicides down to rates as low as 0.0028 kg ae/ha (2,4-D). A field study was conducted to determine the effect of 2,4-D and glyphosate applied to ‘Riesling’ vinifera grapes at three stages of vine growth (pre bloom, full bloom, and post bloom). 2,4-D and glyphosate were evaluated in combination at 0.028 kg ae/ha + 0.028 kg ae/ha, 0.0084 kg ae/ha + 0.0084 kg ae/ha, and 0.0028 kg ae/ha + 0.0028 kg ae/ha at each bloom stage and individually at 0.028 kg/ha at full bloom. Crop injury was visually assessed at 0, 7, 14, 19, 28, 33, 49, 56, 63, and 76 DAT in 2011 and 0, 17, 28, 42, 56, 70, and 84 DAT in 2012; yield and juice quality were assessed both years.

In 2011, 2,4-D + glyphosate at 0.0084 kg ae/ha + 0.0084 kg ae/ha and 0.028 kg ae/ha + 0.028 kg ae/ha reduced shoot growth and increased injury of the vines (compared to untreated control)

† Current Graduate Student, Research Associate, Associate Professor, and Professor, respectively, Department of Horticulture and Crop Science, The Ohio State University/Ohio Agriculture Research and Development Center (OSU/OARDC), Wooster, Ohio 44691. Corresponding author’s e-mail: [email protected]. 58

regardless of vine stage of growth. However, only the 2,4-D + glyphosate at 0.028 kg ae/ha +

0.028 kg ae/ha pre and post bloom and 2,4-D + glyphosate at 0.0084 kg ae/ha + 0.0084 kg ae/ha post bloom treatments affected yield. Simulated drift at post bloom with 2,4-D + glyphosate at

0.028 kg ae/ha + 0.028 kg ae/ha and 0.0084 kg ae/ha + 0.0084 kg ae/ha resulted in a loss of yield in the year following the herbicide treatments due in part to death of some vines. In 2012, the

2,4-D + glyphosate at 0.028 kg ae/ha + 0.028 kg ae/ha resulted in much greater injury and effect on yield than in 2011 regardless of vine stage of growth. In conclusion, damage caused by the combination of 2,4-D + glyphosate is almost always more severe than either herbicide alone.

Nomenclature: glyphosate; 2,4-Dichlorophenoxyacetic acid (2,4-D); vinifera grape, Vitis vinifera L.

Key Words: Glyphosate, 2,4-D, vinifera, simulated drift.

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Failure to use herbicide resistance management tools has led to glyphosate resistance in certain

weeds (WSSA 2011). One way to manage herbicide resistance is to use alternative herbicides.

New genetically modified crops, with resistance to existing herbicides, will allow the use of alternative herbicides that control a broad spectrum of weeds and resistant biotypes. An example

of such new resistance traits are those created for 2,4-D (Wright et al. 2010) and dicamba

(Behrens et al. 2007).

Grapes and certain other specialty crops can be extremely sensitive to the drift of 2,4-D.

A number of crops are injured at application rates that are less than 1% (< 0.0084 kg/ha) of the rate labeled for use on grain and pasture (Dexter 1993; Jiang 2010). Drift is defined “as the

movement of herbicide from the target area to areas where herbicide application was not

intended” (Dexter 1993). In the 1940s and 50s, Stewart et al. (1947 and 1952) demonstrated that

2,4-D in a 27% solution was effective at killing all wild grape vines under 3 meters in height.

From 1980-2000, Comes et al. (1984) showed that 1 ppm 2,4-D sprayed on ‘Concord’ grape vines exhibited moderate injury symptoms, but there was no effect on growth rate, yield, or fruit quality; Ogg et al. (1991) showed that repeated exposure to 2,4-D every year for four years resulted in up to 85% loss of yield; Al-Khatib (1993) and Bhatti et al. (1996 and 1997) showed that rates of 11.20 grams per hectare caused severe damage and affected numerous growth parameters of the grape vines. Grape has also been shown to be more sensitive to the combination of 2,4-D + glyphosate than to either herbicide alone, with glyphosate by itself causing less injury than 2,4-D alone (Bhatti et al. 1997; Jiang 2010). Symptoms typically observed on grape vines following exposure to 2,4-D include fan-shaped leaves, strapping (or 60

parallel veins), zigzag shoot growth, epinasty (downward bending of leaves or other plant parts), and poor fruit set (Dami et al. 2002).

The grape industry in Ohio is expanding at a rapid pace. In 2008, the Ohio Grape

Industries Committee (OGIC) commissioned a study to better understand the impact of the grape

industry in Ohio. Ohio vineyards and wineries are typically embedded in agronomic farming

areas. Of the 769 hectares of vineyard currently in production, most are small and surrounded by large expanses of soybean (1,780,620 ha in 2011) or corn (1,497,340 ha in 2011) farming (MFK

Research 2008). The researchers reported that Ohio contained 124 wineries (a 65% increase over

1999), which included 769 ha of vineyards and production of 4,292,660 L of wine annually.

They also calculated the total contribution to the state economy to be $582.8 million per year.

More recent data shows the number of winery permits issued as of February 2013 to be 176, a

41.9% increase since 2008 (C. Eckstein, personal communications). While the industry is expanding, so are concerns and fears of herbicide drift and resultant crop damage.

Commercialization and wide-spread adoption of crops with resistance to 2,4-D is expected to create particular problems for Ohio’s grape industry, since 2,4-D is much more toxic than glyphosate (Dami 2002; Mortensen et al. 2012). This increased toxicity as well as possible

continued use of older formulations of 2,4-D with greater drift potential are concerns of grape

growers. A close examination of the traditional uses of 2,4-D in Ohio included fall or early

spring applications to cereal grains and pastures that occurred while grapes were typically

dormant (Anonymous 2013c). Proposed uses for 2,4-D on resistant crops include two POST 61

applications during advanced stages of corn and soybean growth. This will result in application

into late spring and early summer when grapevines are growing rapidly and flowering. Bloom

stages have been proposed as the most sensitive stage of the grapevine to herbicide drift (White

2004). As the number of 2,4-D applications per year increases in areas around vineyards, there

will be a corresponding increase in the risk of drift occurrences.

Following release of 2,4-D tolerant crops, the total area treated with the herbicide is bound to increase. Factors that support this contention include: the current dominance of glyphosate resistant crop planting; the fact that there are 24,766,800 hectares affected by resistant weeds (Anonymous 2013); and the fact that, if the areas currently affected by resistant weeds use

the new resistant traits, other farmers will most likely also adopt the new technologies since any

non-resistant crops will be highly sensitive to herbicide damage as well. This guideline would

imply that since a large amount of hectares are already GM and since so many hectares are

currently affected by resistant weeds, those same hectares will probably quickly be planted with

the new resistant crops. Simply due to the large areas in Ohio planted with GM crops, vineyards

are likely to be located near areas that will be planted with the new herbicide resistant crops and

therefore will be at a greater risk of herbicide drift occurring.

Although, as described above, extensive work has been completed demonstrating the

negative impact of 2,4-D/dicamba on grape vines (Stewart et al. 1947 and 1952; Comes et al.

1984; Ogg et al. 1991; Al-Khatib et al. 1993; Bhatti et al. 1996 and 1997; Dami et al. 2002; White

2004; Jiang et al. 2010), the likelihood of increased use and application timings in late spring and 62 early summer necessitates a re-examination of grape response to drift. The objective of this research was to identify differences in sensitivity to low doses of 2,4-D + glyphosate in combination as well as each individually at time points around bloom stage that have been reported as more sensitive than other growth stages. This experiment allowed for comparison of the severity of damage due to the timing of the simulated drift as well as comparison of the individual and combination herbicide treatments at the predicted most sensitive stage of growth.

It is anticipated that, with the knowledge gained from this research, there will be a greater understanding of the implications of drift occurring during the bloom stage. With this understanding, better growing practices can be used and better vineyard management recommendations can be made to both growers with vineyards near potential drift sources, as well as to applicators spraying near vineyards. Specifically, growers can be reassured that vines experiencing only slight 2,4-D or 2,4-D+glyphosate damage (up to 0.0084 kg/ha 2,4-D or 0.0084 kg/ha + 0.0084 kg/ha 2,4-D+glyphosate) will likely recover the following growing season, and may even produce viable fruit in the current growing season; and applicators can be cautioned that exposure of grape vines to even moderate levels of 2,4-D or 2,4-D + glyphosate (0.024 kg/ha or 0.024 kg/ha + 0.024 kg/ha) can result in severe damage to the plant, loss of yield, or vine death, and that proper precautions should be taken when spraying these herbicides (i.e. spraying only on low-wind, lower temperature days less conducive to drift events).

63

Materials and Methods

This research was conducted in a block of ‘Riesling’ and ‘Cabernet franc,’ originally planted at the Ohio Agricultural Research and Development Center (OARDC) branch in Kingsville, Ohio, in 2001. The ‘Cabernet franc’ and ‘Riesling’ varieties alternated rows throughout the block.

‘Riesling’ vines were used for this experiment and rows of ‘Cabernet franc’ vines served as buffer between the treated ‘Riesling’ rows. Plots consisted of a single vine, with an untreated vine between each plot, and treatments were replicated four times. The experiment was conducted in 2011 and repeated in 2012. Treatments, as a factorial treatment design in a

randomized complete block designed (RCBD) experiment with four replications, were

combinations of 2,4-D amine + glyphosate at 0.028 kg ae/ha + 0.028 kg ae/ha,

0.0084 + 0.0084 kg ae/ha, and 0.0028 + 0.0028 kg ae/ha, single treatments of 2,4-D at 0.028

kg/ha or glyphosate at 0.028 kg/ha and a non-treated control. Rates were equivalent to 1/300,

1/100, and 1/30 of the labeled rate of 0.84 kg/ha Weedar 64 and 0.84 kg/ha Roundup PowerMax

(Table 2). Treatments were applied at three growth stages: two weeks prior to full bloom, full

bloom, and two weeks post full bloom. Full bloom was defined as a score of 23 on the Eichhorn

and Lorenz growth stage scale (OMAFRA 2002). Residual crop injury was evaluated in each

following year.

4 Herbicides were applied using a hand-held compressed CO2 sprayer with an aluminum boom equipped with two standard TeeJet 8002 Flat Spray Tips2 spaced at 46 cm. Herbicides

were applied at 0.76 liters per minute (LPM) with a spray pressure of 276 kPa. The boom was 64

held perpendicular to the ground, 46 cm from the vine canopy. One pass was made on either side of the vine.

In 2011, pre bloom treatments were applied on June 8; full bloom treatments on June 15; and post bloom treatments on June 27. In 2012, the pre bloom applications were made on June 4; the full bloom were on June 21; the post bloom were on July 2. Crop injury was evaluated visually at 0, 2, 4, and 8 weeks after each treatment, as well as 3 ratings approximately 12 months after treatment. Injury was rated using a 0 to 100 scale, where 0 was no injury and 100 was death of new growth. Vine growth following herbicide treatment was quantitatively assessed by at each evaluation date by measuring shoot growth (in cm), distal internode growth (in mm, using a caliper1), internode number per shoot, and cluster count per shoot and comparing those measures to equivalent statistics for vines in untreated control plots. Grapes were harvested when mature as determined by the vineyard manager. Cluster count, fruit yield, BRIX, pH, and titratable acid

(TA) were determined following the methods of Gallander (1991).

The general linear model (proc GLM) of SAS for Windows, version 9.23 was used to analyze the data. Cluster count per shoot, shoot growth, internode growth, and internode count each had four measurements per vine and therefore the data were treated as sub-samples. Means comparison was done using pairwise comparisons (LSD). Interaction between herbicide type, rate, and application timing were tested as well as the main effects on each variable measured. A P value of 0.05 was used for all results.

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Results and Discussion

2,4-D treatment alone at a rate of 0.024 kg/ha resulted in the grape vine damage as described previously, including parallel venation, leaf strapping, and chlorosis. When 2,4-D was applied in combination with glyphosate, observed damage was very similar to 2,4-D damage alone, with slight increase in chlorosis due to the addition of the glyphosate. Damage was visible at the lowest rate of simulated drift, 2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha. The occurrence and severity of these symptoms increased as increasing rates of both herbicides were applied.

Vine/leaf damage was visible within days of treatments and in some cases the vines partially recovered within 8 weeks and/or completely recovered within 12 months. Yield and quality were unaffected by 2,4-D + glyphosate at the 0.0028 kg/ha + 0.0028 kg/ha rate regardless of application timings. Similarly, yield and quality were unchanged by application of 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at the pre and full bloom timings in 2011. The effect of the simulated drift treatments at each timing varied between the two years, but several key results were observed in 2011. Several of the vines (all at the post bloom application) were killed by 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha, the maximum simulated drift rate tested. In

2011, injury from the post bloom treatments was much more severe than either pre or full bloom treatments. No interaction effects were observed between the variables measured at each rating timing, but the variables measured between each application timing (stage of growth) were significant and all main effects of each variable measured were significant.

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In 2011, at the time of treatment, there was limited variation in the shoot growth at the pre bloom timing (Table 3.2). Average vine shoot growth in the control was 63 cm; whereas, the

other treatments at pre bloom had shoot growth of 71 cm, 70 cm, and 64 cm (ordered from lowest

rate to highest rate of 2,4-D + glyphosate tank mix). At the time of the full bloom application, the glyphosate and the lowest rate of 2,4-D with glyphosate treated vines had longer internode growth (101.2 mm and 92.0 mm, respectively) than the other treatments. The glyphosate treatment at full bloom also had more clusters present (2.7) than the other treatments at the same application timing.

In 2011, two weeks after each treatment, shoot growth, internode count, and injury varied significantly according to the stage of growth when each treatment was applied (Table 3.2).

There was no variation in internode growth within the full bloom treatments and there was no variation in cluster count within the pre or full bloom treatments. Shoot growth was shortened by

2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha from a minimum of 19% at full bloom, to a maximum of 100% when applied post bloom. When 2,4-D at 0.028 kg/ha was applied by itself at full bloom shoot growth was reduced by 30%. The post bloom timing of 2,4-D + glyphosate at

0.028 kg/ha + 0.028 kg/ha terminated new growth from the cordon (i.e., death of that year’s shoot growth from the cordon). This post bloom treatment resulted in the most severe injury (96%)

observed at two weeks after treatment. This treatment continued to result in the most severe

injury ratings throughout the year, and resulted in the greatest residual damage the following year

(75 to 80%). With applications made at pre and post bloom, internode growth was reduced by

2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha due to the lack of new growth; no young leaves 67

or new internodes were produced (100% reduction for each). Internode count data corroborated

this result; as shoots were increasingly injured, fewer internodes developed and shoots became

shorter. The cluster count varied within the post bloom treatments since vines treated with 2,4-D

+ glyphosate at 0.028 kg/ha + 0.028 kg/ha had no new growth and no clusters and the 2,4-D +

glyphosate at 0.0084 kg/ha + 0.0084 kg/ha resulted in 50% injury, 29% reduction in shoot

growth, 35% reduction in internode count, and 48% reduction in cluster count.

In 2011, four weeks after each application, all variables measured other than cluster count

at full bloom showed variation (Table 3.2). Trends in dependent variables that were observed at

two weeks after treatment continued to be observed at this evaluation. At the pre and post bloom

treatment timings, 2,4-D + glyphosate applied at 0.0084 kg/ha + 0.0084 kg/ha affected all

variables; and 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha affected the variables more

significantly then the 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha. Vines treated with 2,4-

D + glyphosate applied post bloom at 0.028 kg/ha + 0.028 kg/ha showed 100% injury, with zero new growth. With the pre bloom application of this same treatment rate, 86% injury was observed with an 82% reduction in shoot growth and a 78% reduction in internode number. At the full bloom timing, the 2,4-D + glyphosate 0.028 kg/ha + 0.028 kg/ha and 2,4-D at 0.028 kg/ha reduced shoot growth (40 and 32%, respectively), internode count (32 and 36%, respectively), and increased injury (54 and 53%, respectively).

In 2011, eight weeks after treatment, results were similar to those observed at four weeks

(Table 3.2), although vines in several plots were starting to show recovery from the injury 68

symptoms observed earlier (including increases in shoot growth and internode count, as well as

lower injury ratings). Treatments applied pre bloom all had lower injury scores at eight weeks

than at four weeks after treatment, ranging from 4 to 25% recovery (2,4-D + glyphosate at 0.028

kg/ha + 0.028 kg/ha and 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha, respectively). Vines

treated at full bloom also showed some recovery from the 2,4-D + glyphosate at 0.028 kg/ha +

0.028 kg/ha and 2,4-D at 0.028 kg/ha treatments and exhibited 8 and 11% recovery, respectively.

The post bloom 2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha and 2,4-D + glyphosate at

0.0084 kg/ha + 0.0084 kg/ha treatments again showed slight recovery (13 and 1%, respectively.

In contrast vines treated post bloom with 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha resulted in all new growth initiated in 2011 being killed. All other variables measured at eight weeks after application showed similar trends in that the 2,4-D + glyphosate at 0.028 kg/ha +

0.028 kg/ha applications at all timings had the greatest injury and largest reduction in shoot growth, internode count, internode growth, and cluster count (although cluster count again showed no variation at the full bloom timing).

At the 2011 harvest, the post bloom 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha and 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha applications had the most effect on the

variables measured (Table 3.5). Vines treated with 2,4-D + glyphosate at 0.028 kg/ha + 0.028

kg/ha rate post bloom did not produce fruit and the 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084

kg/ha rate (also at post bloom) had an average of 0.1 kg of yield per vine. 2,4-D + glyphosate applied pre bloom at 0.028 kg/ha + 0.028 kg/ha resulted in a decrease in fruit yield of 7.3 kg or

83% compared to the untreated control. Fruit yield from all other treatments ranged from 6.8 kg 69

to 9.8 kg per vine. Cluster count varied across the treatments, with an average of 0 (2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha post bloom) to 78.3 (control) clusters per vine, again with the most severely injured vines having few if any clusters. Berries (if present) ranged in weight between treatments from 1.98 g (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha at full bloom, glyphosate at 0.028 kg/ha at full bloom, and 2,4-D + glyphosate at 0.0028 kg/ha +

0.0028 kg/ha at post bloom) to 0.48 g (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha post bloom). The number of berries per cluster also ranged across treatments from 97.7 (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha pre bloom) down to 21.7 (2,4-D + glyphosate at

0.0084 kg/ha + 0.0084 kg/ha post bloom). The pH, BRIX, and TA did not vary across treatments.

In 2012, at the time of applications (zero days after treatment), there was no significant variation in the variables measured other than shoot growth at the full bloom application timing and cluster count at the post bloom timing (Table 3.3). The shoot growth of the control vines at full bloom had an average length shorter than that of the 2,4-D + glyphosate at 0.0028 kg/ha +

0.0028 kg/ha treated vines (91 cm vs. 108 cm, respectively). The other vines treated at full bloom were similar to both the control and the 2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha treated vines. The cluster count varied slightly at the post bloom timing, between 2.1 (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha and 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha treatments) and 2.4 (2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha treatment) clusters per vine. The control had 2.2 clusters per vine at the post bloom timing.

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In 2012, two weeks after each treatment, all variables measured showed variation at the pre bloom and full bloom timings. At the post bloom timing, only the internode growth and cluster count did not vary between treatments (Table 3.3). The pre bloom 2,4-D + glyphosate at

0.028 kg/ha + 0.028 kg/ha treatment showed the greatest level of injury (89%) with shorter average shoot growth (25 cm, a 73% reduction), no new growth present (therefore no internode growth measurements). This treatment also had an average of 0.4 clusters per shoot compared to the control which had 2.1 (81% reduction). The full bloom treatments showed the greatest injury with the 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha and 2,4-D alone, 60% and 49% respectively. These two full bloom treatments also had decreased shoot growth (44 and 40%, respectively) , cluster count (14 and 5%, respectively), and internode growth (50 and 42%, respectively) similar to the pre bloom timing of the same 2,4-D + glyphosate rate; but these reductions were not as great as the pre bloom timings. The post bloom treated vines showed less than 21% injury (2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha) but did show a small reduction in the average internode count (35% or less) and shoot growth (10% or less).

In 2012, at four weeks after each treatment timing, almost all the pre and full bloom treated vines showed high rates of injury (21 to 64%). The lowest rate (2,4-D + glyphosate at

0.0028 kg/ha + 0.0028 kg/ha) at both pre (43% injury) and full bloom (21% injury) showed the greatest damage from any rating throughout the experiment at this lowest rate. All variables measured at pre and full bloom showed effects of the treatments which included slight increase in shoot growth (4%), reduction in shoot growth (up to 92%), reduction in clusters per shoot (4 to

100%), increase in internode growth (3%), reduction of internode growth (up to 100%), and 71

reduction of internode count (11 to 88%) (Table 3.3). At both pre and full bloom, the high rate

(2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha) showed 94% injury with virtually all new growth having been killed by the treatments. At the post bloom timing, the 2,4-D + glyphosate at

0.028 kg/ha + 0.028 kg/ha treatment had shortened shoot growth (18%) and 29% overall injury.

No other variables measured at four weeks after the post bloom treatments showed variation.

In 2012, at eight weeks after the application of the treatments, the pre and full bloom again showed the greatest damage, with the 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha and

2,4-D alone treatments at full bloom being 100% injured with no active growth and the 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha treatment at pre bloom showing 96% injury (Table 3.3).

All variables measured in the pre and full bloom treated vines showed similar differences between rates as at the four week post application ratings. With the increase in 2,4-D +

glyphosate concentration (for pre and full bloom treatments), there was a reduction of shoot

growth (20 to 100%), internode growth (up to 100%), internode count (20 to 100%), and cluster count (up to 100%). The post bloom treated vines showed some reduction internode count (13 to

34%) and injury (18 to 35%), with the 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha rate having the shortest shoots (139 cm), fewest internodes (20.7) and greatest injury (35%) of the post bloom treatments.

In the 2012 harvest, there was more variation between the treatments than there had been in 2011 (Table 3.6). The overall yield ranged from 0 kg (2,4-D + glyphosate at 0.028 kg/ha +

0.028 kg/ha at pre bloom, 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha at full bloom, and 72

0.028 kg/ha 2,4-D alone at full bloom) to 6.8 kg (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha at post bloom) with the control having a yield of 5.6 kg. For the remaining variables, the treatments with no yield were not included when referring to the lowest values but were included in statistical analysis. The cluster count varied among the treatments, ranging from 46 (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at full bloom) to 84 (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha at post bloom) with the control having 63 clusters on average per vine.

Berry weight ranged from 1.88 g (control) down to 1.48 g (2,4-D + glyphosate at 0.0084 kg/ha +

0.0084 kg/ha at pre bloom) with all treatments having a decrease in berry weight. The number of berries per cluster ranged from 50.9 (2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha at pre bloom) to 33.9 (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at full bloom) with the control having an average of 45.8 berries per cluster (there was no significant difference between these treatments in berries per cluster). The pH, BRIX, and TA varied in 2012, whereas in 2011 there was no variation. The pH ranged from 3.12 (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at pre bloom) to 2.97 (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at post bloom) with the control having a pH of 3.03. The BRIX ranged from 20.9 (2,4-D + glyphosate at 0.0084 kg/ha +

0.0084 kg/ha at full bloom) to 18.2 (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha at post bloom) with the control having BRIX of 19.0. The TA of the control was 1.13% and ranged between treatments from 1.07% (0.028 kg/ha glyphosate at full bloom) to 1.19% (2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha and 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha at post bloom).

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. Post bloom treatments caused the most damage in the year they were treated (2011) and that effect carried over into the following year (2012). Vines that were sprayed in 2011 were measured at 362, 379, and 404 days after the pre bloom treatments (Table 3.4). The same variables that were measured in the spray year (2011) were measured, including yield at the end of the season. Less than 16% injury was observed in the vines that had been treated pre bloom or full bloom. Symptoms observed included slight striation and parallel veins in the youngest leaves, typical of 2,4-D damage observed in 2011 and similar to previous reports by Dami (2002).

In contrast, four vines that had been treated with 2,4-D + glyphosate at 0.0028 kg/ha + 0.0028 kg/ha or 0.0084 kg/ha + 0.0084 kg/ha post bloom were dead and the injury of a fifth was 80%.

The high rate of 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha post bloom had an average residual injury of between 75 and 80% at each evaluation. Vines treated with 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha rate display between 28 and 45% residual injury over the three evaluation timings

The 2,4-D + glyphosate at 0.028 kg/ha + 0.028 kg/ha rate at the pre bloom and post bloom timings as well as the 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha rate applied post bloom resulted in loss of yield the following year (data not reported, p ≤ 0.05) due to the death or severe residual injury of the vines within each of these treatments as described previously.

Residual effects on yield, average berry weight, pH, BRIX, TA, and berries per cluster were not detected from the other treatments other than the post bloom 2,4-D + glyphosate at 0.028 kg/ha +

0.028 kg/ha and post bloom 2,4-D + glyphosate at 0.0084 kg/ha + 0.0084 kg/ha.

74

The highest rate (0.028 kg/ha + 0.028 kg/ha) of 2,4-D + glyphosate treatment resulted in

3 of 12 vines dying in 2011 and 6 of 12 dying in 2012. The vines that did survive had decreased yield as a result of the pre and post bloom treatments in 2011 and the pre and full bloom treatments in 2012. The middle rate (0.0084 kg/ha + 0.0084 kg/ha) of 2,4-D + glyphosate resulted in only one vine dying over both years (in 2011) but did cause a decrease in yield in 2011

(post bloom) and 2012 (pre and full bloom). The 2,4-D alone at full bloom (0.028 kg/ha) caused minimal effects in 2011, but in 2012 caused 2 of 4 vines to die and fruit were not produced on those vines that survived. The results also show that the pre bloom and full bloom timings resulted in less damage than post bloom applications in 2011. In contrast the pre and full bloom timings in 2012 resulted in severe damage. Yet in both years the grapevines were sprayed at the

same bloom stages, indicating that the growth stage does not appear to be a good indicator of

maximum sensitivity. The variation in the severity of damage between the two years did not

appear to correlate with the weather, but based on the conditions of the trial as well as previous

work, weather is the variable most likely resulting in the difference in damage observed, although

this cannot be determined from the current data set. It can be stated that the injury observed as a

result of the treatments at each growth stage can be severe at very low rates (0.0028 kg/ha – 0.028

kg/ha) and can result in significant loss of yield and/or death of the vine. At the lowest rates

tested (0.0028 kg/ha), the visual injury symptoms were often significant, but the vines recovered

and produced comparable yields to the vines that were not subjected to simulated drift treatments

(control). Future research needs to be done to continue to better understand the timing effects of

drift and the potential damage to vineyards, including the effects of weather, the concentration of 75 drift particles, adjuvants present in the herbicides, age of vines, and variety of grape vines. The potential for drift to occur will increase with the 2,4-D resistant trait crops being introduced and therefore the understanding of the risks involved need to continue to be investigated.

76

Acknowledgments

Funding was provided by The Ohio Agricultural Research and Development Center SEEDS

Grant Program, The Ohio Grapes Industries Committee, and Dow AgroSciences. Thank you to

Linjian Jiang, Steven “Vinny” Font, AJ Kropp, Tim Koch, Roger Downer, Jason Parker, Andy

Glaser, Erick Mvati, Connie Echaíz, Andrea Sosa, Marlon AC Pangan, Heather McDonough, Ben

Morphew, Ashley Kulhanek, David Scurlock, Todd Steiner, Patrick Pierquet, Greg Johns, Mike

Davault, Kesia Hartzler, and Bert Bishop.

77

Source of Materials

1Fisher Scientific, 300 Industry Drive, Pittsburgh, PA 15275.

2TeeJet Technologies, North Avenue and Schmale Road, P.O. Box 7900, Wheaton, IL

60187-7901.

3SAS 9.2, SAS Institute Inc. 100 SAS Campus Drive, Cary, NC 27513.

4Bellspray, Inc. P.O. Box 267, Opelousas, LA 70571-0267.

78

Literature Cited

Anonymous. 2003. 2003 Wine Grape Cultivar Trial. Iowa State University. Online.

http://viticulture.hort.iastate.edu/research/pdf/03grapewine04report.pdf Accessed June 2,

2013.

Anonymous. 2013. Glyphosate-resistant weed problem extends to more species, more farms.

Farm Industry News. Online. http://farmindustrynews.com/herbicides/glyphosate-resistant-

weed-problem-extends-more-species-more-farms Accessed June 2, 2013.

Anonymous. 2013. Ontario Ministry of Agriculture, Food, and Rural Affairs. Online. 2,4-D.

Excerpt from Guide to Weed Control.

http://www.omafra.gov.on.ca/english/crops/facts/notes/24d.htm Accessed June 2, 2013.

Al-Khatib, K., Parker, R., Fuerst, E.P. 1993. Wine Grape (Vitis vinifera L.) Response to

Simulated Herbicide Drift. Weed Technology, Vol. 7, No. 1, pp. 97-102.

Appleby, A.P., Müller, F., Carpy, S. 2002. Weed Control. Ullmann's Encyclopedia of Industrial

Chemistry, Wiley-VCH, Weinheim.

Behrens, M.R., Mutlu, N., Chakraborty, S., Dumitru, R., Jiang, W.Z., LaVallee, B.J., Herman,

P.L., Clemente, T.E., Weeks, D.P. 2007. Dicamba Resistance: Enlarging and Preserving

Biotechnology-Based Weed Management Strategies. Science, 316: 1185-1188.

Bhatti, M., Al-Khatib, K., Parker, R. 1997. Wine grape (Vitis vinifera) response to fall exposure

of simulated drift from selected herbicides. Weed Technology, Vol. 11, pp. 532-536.

Bhatti, M.A., Al-Khatib, K., Parker, R. 1996. Wine Grape (Vitis vinifera) Response to Repeated

Exposure of Selected Sulfonylurea Herbicides and 2,4-D. Weed Technology, Vol. 10, No. 4,

pp. 951-956. 79

Bondada, B.R. 2011. Micromorpho-Anatomical Examination of 2,4-D Phytotoxicity in Grapevine

(Vitis vinifera L.) Leaves. Journal of Plant Growth Regulation. 30:185-198.

Castro, A.J., Carapito, C., Zorn, N., Magne, C., Leize, E., Van Dorsselaer, A., Clement, C. 2005.

Proteomis analysis of grapevine (Vitis vinifera L.) tissues subjected to herbicide stress.

Journal of Experimental Botany. Vol. 56, No. 421, pages 2783-2795.

Comes, R.D., Marquis, L.Y., Kelley, A.D. 1984. Response of Concord Grapes (Vitis labrusca) to

2,4-D in Irrigation Water. Weed Science, Vol. 32, No. 4, pp. 455-459.

Cranston, H.J., Kern, A.J., Hackett, J.L., Miller, E.K., Maxwell, B.D., Dyer, W.E. 2001. Dicamba

resistance in kochia. Weed Science, 49:164-170.

Dami, I., Masiunas, J., Bordelon, B. 2002. Herbicide Drift and Injury to Grapes. Southern Illinois

University, Bulletin C1382.

Dexter, A.G. 1993. Herbicide Spray Drift. A-657. North Dakota State University and the

University of Minnesota. Online. http://www.ag.ndsu.edu/pubs/plantsci/weeds/a657w.htm

Accessed June 2, 2013.

Food Engineering and Ingredients. 2008. Herbicide-resistant grape could revitalize Midwest

America’s wine industry. Food Engineering and Ingredients. Volume 33, Issue 4, page 44.

Gallander, J., Briner, L., Stetson, J., Liu, J., Krielow, L., Wilker, K., Romberger, R., Stamp, C.,

Riesen, R. 1991. Manual for Wine Analysis and Laboratory Techniques. The Ohio State

University, Ohio Agricultural Research and Development Center. Horticulture Series 542.

Hellman, E., Fults, J. 1999. Preventing Phenoxy Herbicide Damage to Grape Vineyards. Oregon

State University Extension Service, EM8737.

80

Industry Task Force II on 2,4-D Research Data. Online. http://www.24d.org/ Accessed June 2,

2013.

Jiang, L., Scurlock, D., Dami, I., Doohan, D. 2010. Manage Herbicide Drift Damage to

Grapevines. The Ohio State University Extension Bulletin.

Kegley, S. 2011. Dr. Susan Kegley on Herbicide Drift. March 27, 2011 (interview). Online.

www.reignofterroir.com Accessed June 2, 2013.

Longstroth, M. 2008. Think Twice Before Using 2,4-D. Michigan State University Extension

Van Buren County.

MFK Research. 2008. The Economic Impact of Wine and Wine Grapes on the State of Ohio.

Commissioned by the OGIC. Online. http://www.tasteohiowines.com/downloads/pdfs/

Accessed June 2, 2013.

Mortensen, D.A., Egan, F., Maxwell, B.D., Ryan, M.R., Smith, R.G. 2012. Navigating a Critical

Juncture for Sustainable Weed Management. BioScience, Vol. 62 No. 1, pp. 75-84.

Ogg, Jr., A.G., Ahmedullah, M.A., Wright, G.M. 1991. Influence of Repeated Applications of

2,4-D on Yield and Juice Quality of Concord Grapes (Vitis labruscana) Weed Science, Vol.

39, No. 2, pp. 284-295.

OMAFRA Staff. 2002. Growth Stages of Grapevines. Ontario Ministry of Agriculture and Food.

Online. http://www.omafra.gov.on.ca/english/crops/facts/grapestages.htm Accessed June 2,

2013.

Roberson, R. Glyphosate resistant weeds a reality for cotton growers. Online.

http://southeastfarmpress.com/glyphosate-resistant-weeds-reality-cotton-growers Accessed

June 2, 2013. 81

Stewart, W.S., Gammon, C. 1947. Fog Application of 2,4-D to Wild Grape and Other Plants.

American Journal of Botany, Vol. 34, No. 9, pp. 492-496.

Stewart, W.S., Gammon, C., Hield, H.Z. 1952. Deposit of 2,4-D and Kill of Wild Grape Vines by

Helicopter Spray Application. American Journal of Botany, Vol. 39, No. 1, pp. 1-5.

United States Geological Survey (USGS). 2012. Glyphosate Herbicide Found in Many

Midwestern Streams, Antibiotics Not Common. Online.

http://toxics.usgs.gov/highlights/glyphosate02.html Accessed June 2, 2013.

Volenberg, D. 2009. Vineyard IPM Scouting Report for week of June 15, 2009. University of

Wisconsin-Extension Door County and Peninsular Agricultural Research Station. Sturgeon

Bay, WI.

Weed Science Society of America (WSSA). 2011. Resistance. Online.

http://www.wssa.net/Weeds/Resistance/index.htm Accessed June 2, 2013.

White, M.L. 2004. Iowa: Viticulture (Grapes) 101. Iowa State Extension. Integrated Crop

Management Conference.

Wright, T., Shan, G., Walsh, T., Lira, J., Cui, C., Song, P., Zhang, M., Arnold, N., Lin, G., Yau,

K., Russell, S., Cicchillo, R., Peterson, M., Simpson, D., Zhou, N., Ponsamuel, J., Zhang, Z.

2010. Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate

dioxygenase transgenes. PNAS 107: 20240-20245.

82

Herbicide Rate (kg/ha) Bloom Stage 2,4-D + glyphosate 0.0028 + 0.0028 2 weeks pre bloom 2,4-D + glyphosate 0.0084 + 0.0084 2 weeks pre bloom 2,4-D + glyphosate 0.028 + 0.028 2 weeks pre bloom 2,4-D + glyphosate 0.0028 + 0.0028 Full bloom 2,4-D + glyphosate 0.0084 + 0.0084 Full bloom 2,4-D + glyphosate 0.028 + 0.028 Full bloom 2,4-D 0.028 Full bloom glyphosate 0.028 Full bloom 2,4-D + glyphosate 0.0028 + 0.0028 2 weeks post bloom 2,4-D + glyphosate 0.0084 + 0.0084 2 weeks post bloom 2,4-D + glyphosate 0.028 + 0.028 2 weeks post bloom

Table 3.1: 2,4-D and/or glyphosate tank mix treatments, rates, and application timings applied to

‘Riesling’ grapevines, Kingsville, Ohio in 2011 and 2012.

83

Shoot Length Internode Length Internode Count Cluster Count Bloom Injury Score (0-100) Treatment (% of control) (% of control) (% of control) (% of control) Stage

2 WAT 4 WAT 8 WAT 2 WAT 4 WAT 8 WAT 2 WAT 4 WAT 8 WAT 2 WAT 4 WAT 8 WAT 2 WAT 4 WAT 8 WAT

2,4-D + glyph. Pre 29 B 51 B 28 B 108 A 88 A 63 B 93 A 52 B 62 B 100 A 88 A 60 B 109 ns 111 A 79 B 0.0028 Bloom

2,4-D + glyph. Pre 40 B 61 B 36 B 77 B 44 B 43 BC 78 A 57 B 69 B 70 B 53 B 35 C 104 ns 89 A 67 C 0.0084 Bloom

2,4-D + glyph. Pre 74 A 86 A 83 A 46 C 18 C 22 C 0 B 0 C 65 B 43 C 22 C 22 C 96 ns 63 B 39 D 0.028 Bloom

2,4-D + glyph. Full 8 C 11 D 18 C 103 A 97 A 77 B 81 B 77 AB 98 AB 91 A 108 A 84 AB 95 ns 96 ns 76 B 0.0028 Bloom

2,4-D + glyph. Full 18 B 28 C 29 B 95 AB 101 A 77 B 77 B 91 A 78 C 95 A 94 A 74 B 118 ns 104 ns 76 B 0.0084 Bloom 84

2,4-D + glyph. Full 38 A 54 B 46 A 81 BC 60 B 48 C 82 B 55 B 80 C 76 BC 68 B 37 C 100 ns 100 ns 70 B 0.028 Bloom

Full 2,4-D 0.028 39 A 53 B 41 A 70 C 68 B 54 C 78 B 55 B 82 BC 62 C 64 B 40 C 105 ns 104 ns 76 B Bloom

Full Glyph. 0.028 5 CD 4 DE 8 D 98 AB 114 A 83 B 66 B 79 AB 95 ABC 95 A 111 A 86 AB 109 ns 91 ns 76 B Bloom

2,4-D + glyph. Post 9 D 26 C 14 C 107 A 104 A 95 A 82 A 91 A 85 A 103 A 90 A 80 A 109 A 81 B 72 B 0.0028 Bloom

2,4-D + glyph. Post 50 B 86 B 85 B 71 B 29 B 33 B 56 B 21 B 38 B 65 B 28 B 34 B 52 C 19 C 16 C 0.0084 Bloom

2,4-D + glyph. Post 96 A 100 A 100 A 0 C 0 C 0 C 0 C 0 B 0 C 0 C 0 C 0 C 0 D 0 D 0 D 0.028 Bloom

Table 3.2: The effect of 2,4-D and glyphosate tank mixes on growth of ‘Riesling’ grapevines following applications at pre bloom, full bloom, and post

bloom growth stages in 2011. Means separation tests are for means within a growth stage.

5 C 0 C 0 C 82 B 89 B 95 A 111 A 111 A 100 100 ns 100 ns 100 ns 100 8 WAT

0 C 0 B 8 B 86 B 88 A 92 A 96 A 95 AB ns 105 ns 105 ns 105 4 WAT

bloom, full bloom, (% of control) Cluster Count 19 B 95 A 81 A 86 D 96 ns 96 ns 100 ns 100 2 WAT AB 105 95 BCD 95 BCD 105 ABC 105

7 D 0 D 0 D 76 B 54 C 58 C 66 B 87 A 79 BC 80 AB 80 AB 8 WAT

88 B 47 C 49 C 84 B 12 D 15 D 21 D 96 ns 81 ns 89 AB ns 101 4 WAT

A (% of control) Internode Count Count Internode 54 B 30 C 65 B 92 A 94 86 A 59 EF 68 DE 79 CD 2 WAT AB 102 96 ABC

s following applications at the pre following s

0 B 0 B 14 B 87 A 90 A 102 A 102 A 118 A 102 127 ns 127 ns 118 ns 124 8 WAT

0 C 5 B 0 B 63 B 99 A 91 A 103 A 103 74 AB ns 104 ns 105 ns 101 4 WAT

ns

(% of control) Internode Length 0 C 69 B 50 D 100 A 100 A 102 58 CD 90 AB ns 107 ns 119 106 2 WAT 84 ABC

5 C 0 C 0 C 55 B 65 B 58 B 73 B 58 C 80 A 71 BC 83 AB 8 WAT

8 D 70 B 39 C 64 B 15 C 27 C 82 B 90 A 104 A 104 A 108 4 WAT AB 101

Shoot Length Length Shoot (% of control) 58 B 27 C 90 B 116 A 116 A 108 56 DE 77 BC 94 AB 66 CD 60 CD 2 WAT AB 102

. Means. separation tests are for means withingrowth a stage.

2 34 B 44 B 16 C 36 B 18 B 19 B 96 A 35 A - 100) 100 A 100 A 100 28 BC 8 WAT

(0

43 C 60 B 21 C 51 B 24 C 94 A 94 A 86 A 29 A Score 10 BC 20 AB 4 WAT

D and glyphosate tank mixes on growth of ‘Riesling’ grapevine ‘Riesling’ of growth on mixes tank glyphosate and - D 9 B 9 B 38 B 33 C 28 C 49 B 89 A 60 A 10 D 21 A 15 D Injury Injury 2 WAT

Pre Pre Pre bloom growth stages in 201 in stages growth bloom Full Full Full Full Full Post Post Post

Stage Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom

The effect of2,4

:

3 glyph.

D + glyph. + - D glyph. + - D glyph. + - D glyph. + - D glyph. + - D glyph. + - D glyph. 0.028 - D - D + + - D glyph. + - D glyph.

Table 3. post and bloom,

Treatment 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.028 Glyph. 2,4 0.0028 2,4 0.0084 2,4 0.028 85

404 404 40 B 20 B 92 A 80 A 80 A 80 A 80 A DAT 100 A 100 A 100 A 100 A 100

379 379 50 B 15 C DAT 100 A 100 A 100 A 100 A 100 A 100 A 115 A 100 A 115 A 100

(% of control) Cluster Count 362 362 75 B 15 C DAT 125 A 125 90 AB 100 AB 100 AB 115 AB 100 AB 100 AB 100 AB 100 AB 100

404 404 67 B 19 C DAT 101 A 101 A 102 91 AB 98 AB 99 AB 85 AB 97 AB 100 AB 100 AB 100

379 379 67 B 22 C 99 A DAT 93 AB 93 AB 92 AB 96 AB 91 AB 94 AB 93 AB 97 AB

bloom application in 2011. in application bloom

(% of control) Internode Count Count Internode 362 362 69 B 22 C DAT 106 A 106 A 106 A 106 A 105 A 112 99 AB s oneyears after applications at thepre 101 AB 101 AB 101 AB 101

404 404 29 B 92 A 91 A 95 A 92 A 99 A 84 A 90 A 71 A DAT 101 A 101 A 105

379 22 B 91 A 90 A 98 A 92 A 90 A 97 A 87 A 73 A DAT 100 A 100 A 100

(% of control) 362 362 67 B 23 C Internode Length DAT 102 A 102 A 117 A 110 A 101 A 112 A 105 A 114 A 115 100 AB 100

404 404 27 B 92 A 97 A 92 A 84 A 98 A 82 A 94 A 77 A DAT 102 A 102 A 106

379 379 64 B 19 C 99 A DAT 110 A 110 A 105 A 100 A 104 89 AB 97 AB 94 AB 90 AB

Shoot Length Length Shoot (% of control) 362 362 27 D DAT 129 A 129 92 BC 64 CD 105 AB 105 AB 107 AB 107 AB 103 AB 108 98 ABC 102 ABC 102

3 B 4 B 8 B 3 B 8 B 5 B 4 B 404 404 10 B 11 B 28 B 75 A - 100) DAT (0

BC

3 C 4 C 0 C 1 C 1 C 379 379 31 B 80 A 8 6 BC DAT 10 BC 16 BC Score

bloom growthbloom stages in 2011. Days after treatment (DAT) are from pre

D and glyphosate tank mixes on growth of ‘Riesling’ grapevine ‘Riesling’ of growth on mixes tank glyphosate and - D

0 C 0 C 3 C 0 C 0 C 0 C 0 C 3 C 3 C 362 362 45 B 75 A DAT Injury

Pre Pre Pre Full Full Full Full Full Post Post Post Stage Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom Bloom

bloom, and post The effect of2,4

:

4 glyph.

D + glyph. + D glyph. D + + D glyph. + D glyph. + D glyph. + D glyph. + D glyph. - - - - + - D glyph. - 0.028 - D - + - D glyph. - Table 3. full bloom,

Treatment 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.028 Glyph. 2,4 0.0028 2,4 0.0084 2,4 0.028

86

0 C 0.22 B 0.22 1.04 A 1.04 A 0.94 A 1.01 A 1.06 A 1.06 A 0.96 A 1.02 A 1.02 A 1.00 A 1.05 TA (%)* TA

0 C 5.3 B 5.3 18.5 A 18.5 A 16.5 A 16.4 A 18.6 A 17.9 A 16.5 A 15.5 A 16.1 A 18.2 A 19.2 BRIX*

0 C pH* 1.57 B 1.57 3.05 A 3.05 A 3.09 A 3.14 A 3.29 A 3.04 A 3.10 A 3.11 A 3.10 A 3.05 A 3.06 s sprayed with glyphosate and/or and/or glyphosate with sprayed s

C C A A A D BC BC AB ABC ABC 0 D 59 61 98 94 96 22 64 68 87 Cluster 73 75 Berries per

0 F 0.5 E 0.5 1.4 D 1.4 A 2.0 A 2.0 A 2.0 Berry 2.0 AB 2.0 CD 1.6 CD 1.6 1.7 ABC 1.7 ABC 1.8 1.7 BCD Weight (g)

B B C B B B B A C AB AB

2 0 C 62 58 14 54 59 62 57 78 65 65 Count Cluster

0 C 1.5 C 1.5 B 6.8 C 0.1 9.5 A 9.5 A 9.4 A 9.5 A 9.8 8.8 AB 8.8 AB 8.8 AB 7.7 AB 7.7 Yield (kg) Yield

Control Pre Bloom Pre Bloom Pre Bloom Full Bloom Full Bloom Full Bloom Full Bloom Full Bloom Full Post Bloom Post Bloom Post Bloom Post Bloom Stage Bloom

Harvest measurements taken after individual treatmentof ‘Riesling’ grapevine : 5 glyph.

D + + D glyph. + D glyph. + D glyph. D + glyph. + - D glyph. - - + - D glyph. + - D glyph. + - D glyph. 0.028 - D - + - D glyph. - present on a vine,value berries recordedno was as zero. *When 2011. in stage bloom around timings various at - D Treatment Control 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.0028 2,4 0.0084 2,4 0.028 2,4 0.028 Glyph. 2,4 0.0028 2,4 0.0084 2,4 0.028 Table 3. 2,4

87

Berry Berries per Treatment Bloom Stage Yield (kg) Cluster Count pH* BRIX* TA (%)* Weight (g) Cluster

Control Control 5.6 ABC 63 ABC 1.9 A 46 AB 3.03 BC 19.0 CDE 1.13 BC

2,4-D + glyph. Pre Bloom 5.8 ABC 74 AB 1.6 C 51 A 3.02 BC 19.1 CDE 1.11 BC 0.0028 2,4-D + glyph. Pre Bloom 3.4 CD 48 C 1.5 C 48 A 3.12 A 20.2 ABC 1.11 BC 0.0084

2,4-D + glyph. Pre Bloom 0 E 0 D 0 D 0 C 0 D 0 F 0 D 0.028 2,4-D + glyph. Full Bloom 6.3 AB 79 AB 1.7 B 46 AB 3.02 BC 19.5 BCD 1.17 AB 0.0028 2,4-D + glyph. Full Bloom 2.4 DE 46 C 1.6 C 34 B 3.06 AB 20.9 A 1.11 C

88 0.0084

2,4-D + glyph. Full Bloom 0 E 0 D 0 D 0 C 0 D 0 F 0 D 0.028

2,4-D 0.028 Full Bloom 0 E 0 D 0 D 0 C 0 D 0 F 0 D

Glyph. 0.028 Full Bloom 5.3 ABC 77 AB 1.7 B 39 AB 3.01 BC 18.7 DE 1.07 C

2,4-D + glyph. Post Bloom 6.8 A 84 A 1.8 AB 45 AB 3.03 BC 19.4 BCDE 1.13 BC 0.0028 2,4-D + glyph. Post Bloom 6.1 AB 73 AB 1.8 AB 48 AB 2.97 C 18.2 E 1.19 A 0.0084 2,4-D + glyph. Post Bloom 3.9 BCD 57 BC 1.6 C 44 AB 3.00 BC 20.4 AB 1.19 A 0.028 Table 3.6: Harvest measurements taken after individual treatment of ‘Riesling’ grapevines sprayed with glyphosate and/or 2,4-D at

various timings around bloom stage in 2012. *When no berries present on a vine, value was recorded as zero. References

Anonymous. 2003. 2003 Wine Grape Cultivar Trial. Iowa State University. Online.

http://viticulture.hort.iastate.edu/research/pdf/03grapewine04report.pdf Accessed June 2,

2013.

Anonymous. 2011. Enlist Weed Control System. Dow AgroSciences. M09-137-006 (02/11) BR

010-42158 DAAGDHTA0076

Anonymous 2011b. National Agricultural Statistics Service. United States Department of

Agriculture. Online http://www.nass.usda.gov Accessed June 2, 2013.

Anonymous. 2012. Industry Task Force II on 2,4-D Research Data. Online. http://www.24d.org

Accessed June 2, 2013.

Anonymous. 2013a. Glyphosate-resistant weed problem extends to more species, more farms.

Farm Industry News. Online. http://farmindustrynews.com/herbicides/glyphosate-resistant-

weed-problem-extends-more-species-more-farms Accessed June 2, 2013.

Anonymous. 2013b. Ontario Ministry of Agriculture, Food, and Rural Affairs. Online. 2,4-D.

Excerpt from Guide to Weed Control.

http://www.omafra.gov.on.ca/english/crops/facts/notes/24d.htm Accessed June 2, 2013.

Anonymous. 2013c. Weedar 64 Herbicide Label. Nufarm Inc.

Anonymous. 2013d. Banvel Herbicide Label. Arysta LifeScience North America, LLC.

Anonymous 2013e. Roundup Ready 2 Xtend Soybeans. Monsanto Company. Online.

http://www.monsanto.com/products/Pages/roundup-ready-2-xtend-soybeans.aspx Accessed

June 2, 2013. 89

Al-Khatib, K., Parker, R., Fuerst, E.P. 1993. Wine Grape (Vitis vinifera L.) Response to

Simulated Herbicide Drift. Weed Technology, Vol. 7, No. 1, pp. 97-102.

Appleby, A.P., Müller, F., Carpy, S. 2002. Weed Control. Ullmann's Encyclopedia of Industrial

Chemistry, Wiley-VCH, Weinheim.

Behrens, M.R., Mutlu, N., Chakraborty, S., Dumitru, R., Jiang, W.Z., LaVallee, B.J., Herman,

P.L., Clemente, T.E., Weeks, D.P. 2007. Dicamba Resistance: Enlarging and Preserving

Biotechnology-Based Weed Management Strategies. Science, 316: 1185-1188.

Bhatti, M., Al-Khatib, K., Parker, R. 1997. Wine grape (Vitis vinifera) response to fall exposure

of simulated drift from selected herbicides. Weed Technology, Volume 11:532-536.

Bhatti, M.A., Al-Khatib, K., Parker, R. 1996. Wine Grape (Vitis vinifera) Response to Repeated

Exposure of Selected Sulfonylurea Herbicides and 2,4-D. Weed Technology, Vol. 10, No. 4,

pp. 951-956.

Bondada, B.R. 2011. Micromorpho-Anatomical Examination of 2,4-D Phytotoxicity in Grapevine

(Vitis vinifera L.) Leaves. Journal of Plant Growth Regulation. 30:185-198.

Bunch, T.R., Gervais, J. A., Buhl, K., Stone, D. 2012. Dicamba Technical Fact Sheet; National

Pesticide Information Center, Oregon State University Extension Services. Online.

http://npic.orst.edu/factsheets/dicambaTech.pdf Accessed June 2, 2013.

Burnside, O.C. 1996. The History of 2,4-D and Its Impact on Development of the Discipline of

Weed Science in the United States. United States Department of Agriculture. No. 1-PA-96.

Castro, A.J., Carapito, C., Zorn, N., Magne, C., Leize, E., Van Dorsselaer, A., Clement, C. 2005.

Proteomis analysis of grapevine (Vitis vinifera L.) tissues subjected to herbicide stress.

Journal of Experimental Botany. Vol. 56, No. 421, pages 2783-2795. 90

Comes, R.D., Marquis, L.Y., Kelley, A.D. 1984. Response of Concord Grapes (Vitis labrusca) to

2,4-D in Irrigation Water. Weed Science, Vol. 32, No. 4, pp. 455-459.

Cranston, H.J., Kern, A.J., Hackett, J.L., Miller, E.K., Maxwell, B.D., Dyer, W.E. 2001. Dicamba

resistance in kochia. Weed Science, 49:164-170.

Dami, I., Masiunas, J., Bordelon, B. 2002. Herbicide Drift and Injury to Grapes. Southern Illinois

University, Bulletin C1382.

Dexter, A.G. 1993. Herbicide Spray Drift. A-657. North Dakota State University and the

University of Minnesota. Online. http://www.ag.ndsu.edu/pubs/plantsci/weeds/a657w.htm

Accessed June 2, 2013.

Food Engineering and Ingredients. 2008. Herbicide-resistant grape could revitalize Midwest

America’s wine industry. Food Engineering and Ingredients. Volume 33, Issue 4, page 44.

Gervais, J. A., Luukinen, B., Buhl, K., Stone, D. 2008. 2,4-D Technical Fact Sheet; National

Pesticide Information Center, Oregon State University Extension Services. Online.

http://npic.orst.edu/factsheets/2,4-DTech.pdf Accessed June 2, 2013.

Hellman, E., Fults, J. 1999. Preventing Phenoxy Herbicide Damage to Grape Vineyards. Oregon

State University Extension Service, EM8737.

Jiang, L., Scurlock, D., Dami, I., Doohan, D. 2010. Manage Herbicide Drift Damage to

Grapevines. The Ohio State University Extension Bulletin.

Kegley, S. 2011. Dr. Susan Kegley on Herbicide Drift. March 27, 2011 (interview). Online.

www.reignofterroir.com Accessed June 2, 2013.

Longstroth, M. 2008. Think Twice Before Using 2,4-D. Michigan State University Extension

Van Buren County. 91

MFK Research. 2008. The Economic Impact of Wine and Wine Grapes on the State of Ohio.

Commissioned by the OGIC. Online. http://www.tasteohiowines.com/downloads/pdfs/

Accessed June 2, 2013.

Miller, A., Gervais, J. A., Luukinen, B., Buhl, K., Stone, D. 2010. Glyphosate Technical Fact

Sheet. National Pesticide Information Center, Oregon State University Extension Services.

Online. http://npic.orst.edu/factsheets/glyphotech.pdf. Accessed June 2, 2013.

Mortensen, D.A., Egan, F., Maxwell, B.D., Ryan, M.R., Smith, R.G. 2012. Navigating a Critical

Juncture for Sustainable Weed Management. BioScience, Vol. 62 No. 1, pp. 75-84.

Ogg, Jr., A.G., Ahmedullah, M.A., Wright, G.M. 1991. Influence of Repeated Applications of

2,4-D on Yield and Juice Quality of Concord Grapes (Vitis labruscana) Weed Science, Vol.

39, No. 2, pp. 284-295.

OMAFRA Staff. 2002. Growth Stages of Grapevines. Ontario Ministry of Agriculture and Food.

Online. http://www.omafra.gov.on.ca/english/crops/facts/grapestages.htm Accessed June 2,

2013.

Roberson, R. Glyphosate resistant weeds a reality for cotton growers. Online.

http://southeastfarmpress.com/glyphosate-resistant-weeds-reality-cotton-growers Accessed

June 2, 2013.

Stewart, W.S., Gammon, C. 1947. Fog Application of 2,4-D to Wild Grape and Other Plants.

American Journal of Botany, Vol. 34, No. 9, pp. 492-496.

Stewart, W.S., Gammon, C., Hield, H.Z. 1952. Deposit of 2,4-D and Kill of Wild Grape Vines by

Helicopter Spray Application. American Journal of Botany, Vol. 39, No. 1, pp. 1-5.

92

United States Geological Survey (USGS). 2012. Glyphosate Herbicide Found in Many

Midwestern Streams, Antibiotics Not Common. Online.

http://toxics.usgs.gov/highlights/glyphosate02.html Accessed June 2, 2013.

Volenberg, D. 2009. Vineyard IPM Scouting Report for week of June 15, 2009. University of

Wisconsin-Extension Door County and Peninsular Agricultural Research Station. Sturgeon

Bay, WI.

Walker, T. 2011. Avoiding 2,4-D Injury to Grapevines. Colorado State University Extension.

Weed Science Society of America (WSSA). 2011. Resistance. Online.

http://www.wssa.net/Weeds/Resistance/index.htm Accessed June 2, 2013.

White, M.L. 2004. Iowa: Viticulture (Grapes) 101. Iowa State Extension. Integrated Crop

Management Conference.

Wright, T., Shan, G., Walsh, T., Lira, J., Cui, C., Song, P., Zhang, M., Arnold, N., Lin, G., Yau,

K., Russell, S., Cicchillo, R., Peterson, M., Simpson, D., Zhou, N., Ponsamuel, J., Zhang, Z.

2010. Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate

dioxygenase transgenes. PNAS 107: 20240-20245.

93

Appendix A: Weather Data for Ashtabula Agricultural Research Station, Kingsville, Ohio

94

Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 1/1/2011 0.36 56.9 33.4 49.4 94 57 83 0 1/2/2011 0 33.3 23.3 26 76 64 71 0 1/3/2011 0 37.2 20.4 28.9 80 45 62 0 1/4/2011 0 36.9 28.4 32.9 91 58 65 0 1/5/2011 0 29 14.9 23.3 92 70 83 0 1/6/2011 0.08 27.8 17.5 23.2 95 84 90 0 1/7/2011 0.12 25.5 15.5 21.1 93 61 83 0 1/8/2011 0.05 24.3 15.2 20.2 92 68 86 0 1/9/2011 0 25.5 22.5 23.9 86 67 77 0 1/10/2011 0 27.6 9.3 20 91 72 82 0 1/11/2011 0.16 29.3 8.8 20.6 94 68 87 0 1/12/2011 0.03 24.2 19.4 21.8 93 72 85 0 1/13/2011 0.15 24.7 21.1 23 93 72 86 0 1/14/2011 0.01 24.5 16.8 21.3 93 76 86 0 1/15/2011 0.02 30.7 18.8 25.6 94 75 85 0 1/16/2011 0 26.5 14.9 18.7 87 68 75 0 1/17/2011 0 31.1 6.3 21 86 54 70 0 1/18/2011 0.03 39.1 30.3 35 96 70 88 0 1/19/2011 0.01 32.4 22.7 27.1 96 74 90 0 1/20/2011 0.11 24.1 19.1 21.5 93 66 85 0 1/21/2011 0.01 22 12.7 15.8 93 59 77 0 1/22/2011 0 17.2 2.8 11.2 90 59 76 0 1/23/2011 0 16.6 -6.9 9 90 59 75 0 1/24/2011 0 29 -10 10.9 88 61 79 0 1/25/2011 0 32.7 27.4 29.9 92 77 86 0 1/26/2011 0 28.4 26.7 27.5 91 87 89 0 1/27/2011 0.01 29.1 24.9 27.3 94 82 89 0 1/28/2011 0.02 26.9 24.7 26.2 93 85 90 0 1/29/2011 0.1 29.4 25 26.8 94 88 92 0 1/30/2011 0 28.3 12.9 22.4 94 69 86 0 1/31/2011 0 19.5 -2.5 11.1 90 68 82 0 2/1/2011 0 23.5 17.3 20.6 92 75 89 0 2/2/2011 0.21 40.3 19.4 26.6 97 73 89 0 2/3/2011 0.15 27.9 11.4 20.2 90 54 73 0

Continued Table A.1: Weather Data for Ashtabula Agricultural Research Station, Kingsville, Ohio.

95 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 2/4/2011 0.08 35.2 14.8 24 87 34 64 0 2/5/2011 0.15 32.8 23.4 27.1 95 62 78 0 2/6/2011 0.02 32.5 24.4 29 95 74 83 0 2/7/2011 0.05 34.9 23.2 31.6 95 84 91 0 2/8/2011 0 23.1 2.3 15 94 64 80 0 2/9/2011 0 25.8 7.3 16.2 83 30 58 0 2/10/2011 0 17.7 7.8 13 86 43 68 0 2/11/2011 0 30.1 8 19.4 69 51 60 0 2/12/2011 0.04 31.8 27.3 29.8 94 54 73 0 2/13/2011 0.01 47.9 28.4 39.5 94 54 67 0 2/14/2011 0 50.7 25.1 38.9 89 48 70 0 2/15/2011 0 34.3 10.4 24.4 89 37 65 0 2/16/2011 0 52.4 31.3 40 72 47 55 0 2/17/2011 0 56.2 44 50 83 61 69 0 2/18/2011 0 57.4 38.7 51.8 86 31 59 1.7 2/19/2011 0 39.9 25.3 31 83 51 67 0 2/20/2011 0.37 35.6 17.4 27.3 95 51 79 0 2/21/2011 0.13 28.7 16.1 21.9 95 79 89 0 2/22/2011 0 21.9 12.4 17.1 91 62 75 0 2/23/2011 0.03 37 2.3 18.6 92 47 81 0 2/24/2011 0.01 36.4 17 30.5 94 83 90 0 2/25/2011 0.16 31.8 8.2 26.7 96 83 93 0 2/26/2011 0.05 34 9.4 25 95 67 85 0 2/27/2011 0 45.3 28.8 36.6 95 70 84 0 2/28/2011 1.75 50.9 26.7 37.2 97 75 88 0 3/1/2011 0.01 40.2 18.1 30.7 93 51 71 0 3/2/2011 0 40.7 17.8 29.9 85 59 71 0 3/3/2011 0 33.1 11 21.6 90 45 73 0 3/4/2011 0.17 45.2 26.1 38.6 92 45 65 0 3/5/2011 0.72 50.1 32.7 43.6 96 65 89 0 3/6/2011 0.29 32.5 25.6 28.2 96 80 93 0 3/7/2011 0 29.4 11.1 23.1 92 60 81 0 3/8/2011 0 46.9 18.6 32.4 93 35 71 0 3/9/2011 0.33 43.5 36.4 40.2 92 49 77 0

Continued

96 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 3/10/2011 0.53 50.9 31.7 41.9 97 85 94 0 3/11/2011 0.33 33.1 30 31.3 97 89 95 0 3/12/2011 0 47.4 26.4 36.5 92 64 80 0 3/13/2011 0 36.9 32.6 34.5 95 75 87 0 3/14/2011 0.02 32.8 22.6 29.1 95 71 85 0 3/15/2011 0.09 45 22.5 35 94 60 82 0 3/16/2011 0.01 45.9 38.5 41 96 77 90 0 3/17/2011 0 64.9 38.7 51.6 93 48 71 1.5 3/18/2011 0 66.5 39.5 53.4 87 50 73 3.4 3/19/2011 0 40.2 30.4 35.1 89 68 79 0 3/20/2011 0.08 53.1 25 37.2 94 45 77 0 3/21/2011 0.32 55.8 42.9 47.4 96 77 87 0 3/22/2011 0.15 42.7 33.3 38 95 74 86 0 3/23/2011 0.38 36.4 29.2 32.2 96 91 95 0 3/24/2011 0.01 31.2 23.3 27.9 95 65 80 0 3/25/2011 0 30.6 20.5 25.2 83 60 73 0 3/26/2011 0 27.8 16.6 23 79 49 64 0 3/27/2011 0 30.1 19.8 25.8 86 49 68 0 3/28/2011 0 31.5 20.5 26.1 81 53 71 0 3/29/2011 0 37.1 17 28 91 46 71 0 3/30/2011 0.27 39.7 19.7 29.4 96 56 84 0 3/31/2011 0 35.9 32 33.3 97 90 95 0 4/1/2011 0 44 29.7 36.2 96 43 80 0 4/2/2011 0 46.6 27.5 38.2 90 53 76 0 4/3/2011 0.05 47.4 33.4 41 90 52 77 0 4/4/2011 0.87 64.2 42.6 55.5 96 53 78 5.4 4/5/2011 0.02 42.7 35 38 94 56 76 0 4/6/2011 0.92 42.4 33.3 36.6 96 66 86 0 4/7/2011 0.08 44 34.4 37.9 97 70 91 0 4/8/2011 0.19 51.6 37.9 45.2 95 72 84 0 4/9/2011 0 54.3 35.6 46 95 75 85 0 4/10/2011 0 81.8 44.5 63.2 93 49 74 13.2 4/12/2011 0 46.9 39.7 43 85 48 75 0 4/13/2011 0.02 53.8 38.1 44 93 43 72 0

Continued

97 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 4/14/2011 0 54.9 31.2 44.5 91 38 68 0 4/15/2011 0 60 37 43.2 90 58 73 0 4/16/2011 0.55 59.3 43.3 52.4 94 60 82 2.3 4/17/2011 0.01 47 37.1 42.2 90 59 72 0 4/18/2011 0.06 41 30.3 35.2 94 68 87 0 4/19/2011 0.26 43.3 35.3 37.7 97 88 94 0 4/20/2011 0.44 62.7 40.6 49.3 98 78 88 0 4/21/2011 0 44.2 33.6 40 88 57 76 0 4/22/2011 0.14 46.4 31.9 41.2 93 57 79 0 4/23/2011 1.01 72.1 45.9 61 96 56 80 11 4/24/2011 0.01 55 47 51.4 95 79 89 1.3 4/25/2011 0.92 54.3 44.1 49.5 97 90 95 0 4/26/2011 0.01 81.3 44.2 64 98 46 76 13.9 4/27/2011 0 81.2 60.4 69.4 90 46 71 19.4 4/28/2011 0 69.2 47.6 57.7 90 49 69 7.6 4/29/2011 0.1 47.6 40.1 43.9 93 72 83 0 4/30/2011 0 58.3 32 47.5 96 56 77 0 5/1/2011 0.02 63.4 52.6 59.6 92 37 71 9.6 5/2/2011 0.17 61.2 48.5 53.8 96 54 77 3.8 5/3/2011 0.56 48.8 41.2 43.4 97 80 95 0 5/4/2011 0.08 51.6 40.5 44.8 97 61 82 0 5/5/2011 0 59.3 38.7 50.1 82 41 61 4.9 5/6/2011 0.17 65.3 43.5 52.6 94 41 68 2.5 5/7/2011 0 61.1 43.7 52.7 95 52 79 2.7 5/8/2011 0 62.2 40.7 52.4 96 42 74 2.3 5/9/2011 0 60.7 38.7 52.2 96 49 69 2.1 5/10/2011 0.14 69.2 50.9 58.4 93 40 55 8.3 5/11/2011 0 75.7 47.2 61.2 96 35 68 11.1 5/12/2011 0.03 81.3 51.3 65.1 95 53 74 15 5/13/2011 0.12 82.8 61.2 67.7 96 60 87 17.7 5/14/2011 0.22 74.6 57.1 65.9 97 71 91 15.8 5/15/2011 0.41 57.7 44.6 48.3 98 95 97 0 5/16/2011 0.09 45.7 43.4 44.6 97 93 95 0 5/17/2011 0.14 49.2 44.8 46.3 98 93 96 0

Continued

98 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 5/18/2011 0.25 61.5 48.3 55 98 91 96 5 5/19/2011 0.06 65.8 48.6 57.3 98 75 90 7.2 5/20/2011 0 67.9 49.2 58.5 98 72 89 8.5 5/21/2011 0 72.4 49.9 62.7 98 63 83 12.7 5/22/2011 0.03 83.8 63.8 71.6 92 55 75 21.6 5/23/2011 0.11 79 62.2 70.5 95 66 79 20.4 5/24/2011 0 68.3 52.5 63.6 95 72 85 13.5 5/25/2011 0.91 79.9 48.9 62 97 63 84 12 5/26/2011 0.77 78.1 60.1 66.1 97 66 88 16 5/27/2011 0 65.2 53.5 57.3 98 85 96 7.3 5/28/2011 0 77.7 55.6 63.8 98 60 84 13.7 5/29/2011 0.11 84 60.2 72.1 95 68 83 22 5/30/2011 0 86.6 60.9 74.9 97 60 80 24.9 5/31/2011 0 92.5 70.3 81.8 94 53 73 31.7 6/1/2011 0 81 65.3 76.3 83 32 56 26.3 6/2/2011 0 67.5 46.1 57.5 93 44 67 7.5 6/3/2011 0 70.7 41.9 57.9 96 37 68 7.9 6/4/2011 0 84.6 53.2 70.1 87 54 65 20 6/5/2011 0 79.3 56.8 68.1 97 41 75 18 6/6/2011 0 81.4 52.6 68.7 96 32 67 18.7 6/7/2011 0.69 85.7 62.5 73.8 96 62 77 23.8 6/8/2011 0 93.6 67.4 81.7 92 45 70 31.6 6/9/2011 0.07 82 60.1 73.3 93 67 79 23.2 6/10/2011 0.13 76.6 57.2 62.9 95 70 87 12.8 6/11/2011 0.16 79 59.7 68.3 97 69 88 18.3 6/12/2011 0 66.6 56.3 60.9 97 73 87 10.9 6/13/2011 0 68.7 50 60.1 96 58 77 10.1 6/14/2011 0.01 65.7 50.9 59.9 94 61 80 9.9 6/15/2011 0 78.7 46.5 63.9 96 45 71 13.9 6/16/2011 0.03 71.3 60 65.4 96 64 82 15.4 6/17/2011 0 74.7 58.6 66.6 96 66 85 16.5 6/18/2011 0 78.1 56.7 68 97 46 76 17.9 6/19/2011 0 77.7 59.8 68.5 93 55 75 18.5 6/20/2011 0.03 80.6 60.5 70.4 96 68 84 20.3

Continued

99 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 6/21/2011 0.15 85.6 66.2 75.1 96 72 86 25 6/22/2011 0.11 83.6 68.2 75.1 96 69 83 25 6/23/2011 1.5 78.5 65.7 70.1 96 70 89 20 6/24/2011 0.1 70.3 64 66.5 95 83 91 16.5 6/25/2011 0.02 66 60.3 63.2 94 81 88 13.2 6/26/2011 0 74.1 55.6 65.3 97 61 83 15.3 6/27/2011 0 82.1 54.2 69.6 97 52 77 19.6 6/28/2011 0 79.6 66.6 73.1 93 50 77 23.1 6/29/2011 0 67.9 55.4 63 95 69 80 13 6/30/2011 0 76.7 54.4 65.8 96 53 78 15.7 7/1/2011 0 80.2 52.6 67.6 96 35 69 17.5 7/2/2011 0.34 85.9 63.9 74.5 92 69 77 24.5 7/3/2011 0.23 81.5 65.7 73.9 95 55 81 23.8 7/4/2011 0.1 80.3 59.5 71.5 96 39 72 21.4 7/5/2011 0 83 54.4 70.4 97 40 73 20.4 7/6/2011 0 87.2 67.7 76.4 96 50 71 26.4 7/7/2011 0 79.3 64.2 71.8 97 53 79 21.7 7/8/2011 0.22 78.3 61.5 69.7 96 59 83 19.6 7/9/2011 0 82.2 59.1 71.5 97 55 78 21.5 7/10/2011 0 86.8 64.3 75.2 92 49 72 25.2 7/11/2011 0.14 88.5 68.1 76.8 94 55 78 26.7 7/12/2011 0 85.4 69.5 76.3 95 69 85 26.3 7/13/2011 0 77.2 66.7 71.8 95 61 75 21.8 7/14/2011 0 77.6 55.7 69.6 96 49 71 19.6 7/15/2011 0 84.8 61.1 72.4 94 46 72 22.4 7/16/2011 0 86.4 62.2 74.6 93 53 74 24.5 7/17/2011 0 88.8 66.2 77.1 95 55 80 27.1 7/18/2011 0.08 90.7 72.9 79.4 94 54 79 29.4 7/19/2011 0.03 84.3 69.2 76.8 97 73 88 26.8 7/20/2011 0 91.5 67.1 79.6 97 55 79 29.6 7/21/2011 0 97.1 78.1 87.7 86 53 70 37.7 7/22/2011 0.04 91.5 71.6 81.2 95 52 79 31.2 7/23/2011 0.3 87.1 71.1 78.6 96 73 85 28.6 7/24/2011 0 83.9 71.4 77.3 97 78 90 27.2

Continued

100 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 7/25/2011 0 82.4 66.4 76 97 71 88 25.9 7/26/2011 0 79.9 65.4 73.4 96 57 78 23.4 7/27/2011 0 79.9 56.5 70.2 96 58 77 20.1 7/28/2011 0 87 66.2 75.4 96 71 87 25.4 7/29/2011 0 81.5 71.9 77.2 97 81 90 27.2 7/30/2011 0 84.4 67.2 76.6 98 49 77 26.5 7/31/2011 0 86.5 65.3 76 95 56 76 26 8/1/2011 0 87 66.1 78.1 94 60 80 28.1 8/2/2011 0 85.6 62.7 73.9 96 61 85 23.9 8/3/2011 0 79 67.2 74 97 85 93 23.9 8/4/2011 0 78.9 68 74.1 96 75 87 24.1 8/5/2011 0 84 65.3 74.7 97 69 86 24.7 8/6/2011 0 84.9 70.5 77.5 95 75 87 27.5 8/7/2011 0 83 69.5 76.7 96 71 87 26.7 8/8/2011 0 79 66.5 73 97 74 88 22.9 8/9/2011 0 77.6 65.1 70.9 97 75 89 20.8 8/10/2011 0 75.9 63.8 70.5 94 55 76 20.4 8/11/2011 0 74.1 58.6 68.5 89 50 63 18.5 8/12/2011 0 79.7 57.1 68.1 95 56 74 18.1 8/13/2011 0 81.1 59.4 70.6 96 53 76 20.5 8/14/2011 0 75.5 63.4 67.9 97 74 90 17.9 8/15/2011 0 76.4 63.1 70.3 96 76 87 20.2 8/16/2011 0 77.4 59 70.4 96 64 79 20.3 8/17/2011 0 82.6 56.2 69 97 50 79 18.9 8/18/2011 0 83.4 62.6 72.2 95 58 79 22.1 8/19/2011 0 80.6 63.7 71.6 97 71 84 21.6 8/20/2011 0 84.2 62.6 72 98 54 84 21.9 8/21/2011 0 76.5 64.7 70.1 97 62 85 20.1 8/22/2011 0 71.2 55.2 65.5 90 60 72 15.5 8/23/2011 0 80 54.1 67.1 90 46 70 17 8/24/2011 0 84.1 63.8 73.4 90 64 76 23.4 8/25/2011 0 77.6 66.6 70.6 97 74 86 20.6 8/26/2011 0 75.1 58.2 68.1 97 68 84 18.1 8/27/2011 0 75.2 54.8 66.7 98 70 86 16.6

Continued

101 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 8/28/2011 0 74.4 64.7 69.9 90 54 75 19.9 8/29/2011 0 73.8 51.9 63.4 96 55 79 13.3 8/30/2011 0 76.7 52.8 64.8 95 48 79 14.7 8/31/2011 0 81.5 59.4 70.2 96 62 80 20.2 9/1/2011 0 85.1 64.5 73.3 97 73 87 23.2 9/2/2011 0 88.6 66.7 78.2 98 70 88 28.2 9/3/2011 0 92.8 71 80.9 97 57 82 30.8 9/4/2011 0 78 66.8 72.4 97 80 90 22.4 9/5/2011 0 67.1 59.6 64.2 94 76 82 14.1 9/6/2011 0 65.8 58.1 61.6 94 74 83 11.6 9/7/2011 0 66.7 57.8 62.3 96 78 90 12.2 9/8/2011 0 71.7 61.3 66.1 97 87 94 16.1 9/9/2011 0 75.7 61.5 67.1 98 84 95 17 9/10/2011 0 72.1 63.9 67 98 80 94 16.9 9/11/2011 0 75.7 60 66.3 98 75 92 16.2 9/12/2011 0 80.9 60.1 69.5 96 57 83 19.5 9/13/2011 0 83.6 63.3 71.4 91 59 80 21.3 9/14/2011 0 68 55.3 62.3 97 71 84 12.2 9/15/2011 0 58.8 50.9 54.5 95 53 75 4.5 9/16/2011 0 60.5 48.2 53.8 95 63 80 3.8 9/17/2011 0 63.9 48.2 55.6 95 62 80 5.5 9/18/2011 0 70.5 46.4 57.2 93 57 80 7.2 9/19/2011 0 63.3 53.1 58.1 96 77 89 8.1 9/20/2011 0 71.4 57.2 63.6 97 73 90 13.5 9/21/2011 0 78.3 59.5 67.1 97 72 90 17 9/22/2011 0 74.7 58.1 66 96 52 80 16 9/23/2011 0.11 61.9 54.7 59.3 97 74 90 9.2 9/24/2011 0 68.9 53 60 97 71 89 10 9/25/2011 0.01 80.6 54.1 66.2 97 64 87 16.1 9/26/2011 2.25 81.4 64.3 70.3 97 67 86 20.2 9/27/2011 0.36 72.2 56.3 63.5 98 58 87 13.4 9/28/2011 0 73.5 54.6 61 97 63 87 11 9/29/2011 0.07 64.1 55.4 58.8 97 74 88 8.8 9/30/2011 0.64 59.1 48 53.7 95 84 90 3.6

Continued

102 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 10/1/2011 0.52 51.4 46.8 49.1 97 63 86 0 10/2/2011 0.51 51 42.6 46.1 94 66 84 0 10/3/2011 0.12 58.3 49.5 53.3 97 87 93 3.3 10/4/2011 0.01 64.5 51.8 57.8 97 71 88 7.7 10/5/2011 0.01 69 47.1 56.8 97 60 88 6.8 10/6/2011 0 69.5 48.7 56.9 96 56 80 6.8 10/7/2011 0 74.9 49.5 59.9 95 51 81 9.9 10/8/2011 0 79.8 52.3 63.7 94 46 77 13.7 10/9/2011 0 77 56.2 64.5 95 55 78 14.5 10/10/2011 0 78.3 53.8 63.3 96 52 81 13.3 10/11/2011 0 77.9 52.9 63.9 94 48 78 13.8 10/12/2011 0.28 64.1 58.2 60 96 74 90 9.9 10/13/2011 0.39 68.2 58.4 61.8 97 79 92 11.7 10/14/2011 0.69 61.8 51.7 57.7 97 64 86 7.6 10/15/2011 1.64 56.4 45.2 50.8 95 51 78 0.8 10/16/2011 0.39 56.8 48 51.6 96 51 81 1.5 10/17/2011 0 62.3 45.3 53.3 86 27 58 3.3 10/18/2011 0.03 58.4 46.9 51.9 95 57 74 1.8 10/19/2011 0.57 60 51 54.8 97 79 90 4.7 10/20/2011 0.47 57.5 44.5 48.1 96 75 88 0 10/21/2011 0.76 49 44.5 46.6 96 81 90 0 10/22/2011 0 52.8 40.7 46.8 95 61 84 0 10/23/2011 0 64.7 39.7 50.9 92 47 72 0.8 10/24/2011 0.08 57 46.9 52.2 94 60 79 2.1 10/25/2011 0.01 60.6 38.2 51.7 94 56 74 1.7 10/26/2011 0.46 63.8 48 54.3 97 66 88 4.2 10/27/2011 0.35 48 33.6 42 97 86 93 0 10/28/2011 0.01 46.5 31.2 37.9 97 71 89 0 10/29/2011 0 45.8 31.4 37 96 72 88 0 10/30/2011 0.01 48.8 31.1 37.8 96 73 89 0 10/31/2011 0.01 52.8 36.2 43.2 95 63 83 0 11/1/2011 0.01 58.3 35.7 45.4 97 49 80 0 11/2/2011 0 66.7 43.4 53.8 77 38 60 3.7 11/3/2011 0 57.3 47.9 52 91 54 72 1.9

Continued

103 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 11/4/2011 0 47.9 32.2 43.2 91 54 75 0 11/5/2011 0 55.4 25.1 39.1 94 30 70 0 11/6/2011 0 63.5 40 50.2 61 40 48 0.1 11/7/2011 0 60 51.8 55 82 54 65 5 11/8/2011 0 69.6 50.6 59.3 86 48 67 9.2 11/10/2011 0.07 49.1 36.6 42.5 88 50 72 0 11/11/2011 0.29 42.5 32.8 38 96 65 78 0 11/12/2011 0 61 35 47.1 75 45 60 0 11/13/2011 0 63.5 50.8 57.3 61 47 54 7.2 11/14/2011 1.68 66.5 50.5 58.8 97 62 85 8.8 11/15/2011 0 58.7 49.2 52.2 98 77 91 2.2 11/16/2011 0 53.7 42.1 49.1 96 51 80 0 11/17/2011 0 42.6 32.1 37.2 90 46 65 0 11/18/2011 0 45.5 30.8 37.7 73 38 56 0 11/19/2011 0.02 56 39 47.9 83 44 55 0 11/20/2011 0 62.3 42.8 53.8 86 58 74 3.7 11/21/2011 0 45.8 34.5 40.6 93 69 82 0 11/22/2011 0.92 45.2 32.9 39.5 97 81 90 0 11/23/2011 0.34 46.4 35.2 42.4 97 74 90 0 11/24/2011 0 54.8 37.7 43.5 94 61 85 0 11/25/2011 0 61 40.2 49.2 91 47 72 0 11/26/2011 0 61.3 45.7 53.3 71 56 64 3.3 11/27/2011 0.34 58.1 45.9 55 96 64 81 4.9 11/28/2011 0.26 46.2 41.2 44.1 96 91 94 0 11/29/2011 0.03 48.9 42 44.4 97 81 89 0 11/30/2011 0.08 42 30.1 37.6 96 74 84 0 12/1/2011 0 38.3 29.2 32.5 93 81 89 0 12/2/2011 0 40.6 29.5 35.1 95 75 88 0 12/3/2011 0.01 49.9 27.7 38.6 96 62 80 0 12/4/2011 0.06 60.3 43.7 50.4 91 44 66 0.3 12/5/2011 1.08 51 41.7 46.8 97 90 96 0 12/6/2011 0.29 41.9 38 39.2 97 96 96 0 12/7/2011 0.04 39.5 33.6 36.1 97 67 87 0 12/8/2011 0 40.9 32.2 36 83 46 68 0

Continued

104 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 12/9/2011 0.16 38.6 31.3 34.2 97 75 88 0 12/10/2011 0 31.2 24.6 28.1 87 65 74 0 12/11/2011 0 36.1 21.4 28 76 47 64 0 12/12/2011 0 41.6 22.3 30.4 85 40 63 0 12/13/2011 0 45.4 24.2 34.1 85 48 72 0 12/14/2011 0.27 51 37.4 41.7 95 75 86 0 12/15/2011 0.46 58.6 42.3 52 94 73 88 1.9 12/16/2011 0 42.2 33.7 35.5 79 66 73 0 12/17/2011 0.02 35.1 25.2 30.3 93 69 82 0 12/18/2011 0.05 34.1 26.6 30.8 95 76 87 0 12/19/2011 0.04 47.8 33.4 40.6 95 74 80 0 12/20/2011 0.03 40.4 34.9 36.8 96 86 92 0 12/21/2011 0.72 59.4 40.4 48.9 96 82 92 0 12/22/2011 0.23 46 37.7 42.7 96 85 92 0 12/23/2011 0.03 38 29.4 33.1 95 74 84 0 12/24/2011 0 36.7 28.2 31.5 89 71 82 0 12/25/2011 0.01 46.9 31.3 36.9 86 54 78 0 12/26/2011 0 44.1 34.3 38.5 81 60 72 0 12/27/2011 0.46 39.2 31 35.1 97 69 87 0 12/28/2011 0.02 36.3 18.7 27.1 96 71 83 0 12/29/2011 0 39.8 18 30.1 91 79 85 0 12/30/2011 0.02 48.6 38.8 43 88 77 82 0 12/31/2011 0.01 47.9 38.6 41.6 96 84 93 0 1/1/2012 0.05 51 33.8 40.9 96 69 85 0 1/2/2012 0.14 33.7 24.8 29.1 96 64 84 0 1/3/2012 0 25.7 12.3 18.5 90 52 71 0 1/4/2012 0 32 11.5 22.4 86 54 72 0 1/5/2012 0 39.1 29.3 34.3 81 65 75 0 1/6/2012 0 54.7 36.5 44.7 74 50 64 0 1/7/2012 0 45.4 38.2 42.2 85 68 75 0 1/8/2012 0 38.1 26.1 32.8 90 63 74 0 1/9/2012 0 41.9 27.2 34.5 87 56 72 0 1/10/2012 0 42.7 27.8 36.9 95 56 82 0 1/11/2012 0.17 45.1 28.5 38.1 95 63 82 0

Continued

105 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 1/12/2012 0.11 45.6 35.5 42.5 96 90 94 0 1/13/2012 0 35 17.7 22 94 72 86 0 1/14/2012 0.31 23.4 18.5 21.7 94 81 92 0 1/15/2012 0.01 25.6 2.5 14.3 90 61 79 0 1/16/2012 0.05 42.4 18.1 30.6 94 60 77 0 1/17/2012 0.59 57.2 33 45.1 95 78 89 0 1/18/2012 0 32.9 16.3 24.7 90 66 76 0 1/19/2012 0.04 28.3 15.4 22.7 95 67 81 0 1/20/2012 0.03 21.3 13.7 17.8 91 55 68 0 1/21/2012 0.14 26.3 18.7 23.2 93 75 85 0 1/22/2012 0 40 11.6 28 92 63 77 0 1/23/2012 0.3 53.2 37.6 43 94 76 86 0 1/24/2012 0 37.8 32.4 34.1 90 77 82 0 1/25/2012 0 33.6 31.3 32.2 88 77 82 0 1/26/2012 0.18 45.7 30.4 35.3 97 88 94 0 1/27/2012 0.78 49.1 32.3 36.7 98 79 94 0 1/28/2012 0.07 35.8 31.1 33.3 97 60 83 0 1/29/2012 0.03 38.9 27.4 32 95 56 72 0 1/30/2012 0 40.6 25.2 31 82 60 67 0 1/31/2012 0 60.1 40.1 50.7 68 49 58 0.7 2/1/2012 0.1 55.4 36.9 46 94 69 85 0 2/2/2012 0 38.2 34 35.5 92 82 87 0 2/3/2012 0 44.6 30 35.9 93 65 81 0 2/4/2012 0 40.5 27.4 34.6 95 71 87 0 2/5/2012 0 39.3 23.7 31.8 96 70 88 0 2/6/2012 0 47.4 30.8 37.9 88 53 77 0 2/7/2012 0 38.9 31.9 34.7 91 79 87 0 2/8/2012 0 32.4 24.5 28.9 86 61 80 0 2/9/2012 0 38.4 21.4 29.7 91 52 77 0 2/10/2012 0 32.5 26.2 29.6 91 64 78 0 2/11/2012 0.08 29.3 17.3 22.7 95 67 87 0 2/12/2012 0 29.1 19.6 23.8 90 69 77 0 2/13/2012 0 37.1 19.4 29.9 90 37 64 0 2/14/2012 0.02 36.7 29 32.9 95 56 82 0

Continued

106 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 2/15/2012 0 40.4 33.5 35.8 94 67 81 0 2/16/2012 0.09 44.4 36.9 40.1 97 79 91 0 2/17/2012 0 39.7 29.6 35.6 91 61 77 0 2/18/2012 0 39.3 30.6 34.3 93 69 80 0 2/19/2012 0 32 28.5 29.6 79 67 73 0 2/20/2012 0 34.1 23.3 29.2 89 68 78 0 2/21/2012 0.05 43 25.5 36.8 96 49 76 0 2/22/2012 0.14 49 32.9 39.3 96 71 86 0 2/23/2012 0.07 40.4 30.4 34.3 97 79 93 0 2/24/2012 0.39 47.5 32.4 37.5 97 66 90 0 2/25/2012 0 33.7 30.2 32.2 89 60 78 0 2/26/2012 0 39 27.4 32.9 92 57 73 0 2/27/2012 0 52.7 32.7 39.3 79 42 60 0 2/28/2012 0 40.2 26.3 34 92 55 73 0 2/29/2012 0.4 55.3 33.4 41.9 97 54 86 0 3/1/2012 0 51.6 35.9 40.1 95 75 83 0 3/2/2012 0.31 52.1 32.6 42.5 93 63 82 0 3/3/2012 0 54.9 31.8 38.7 91 62 70 0 3/4/2012 0.09 32.9 25.9 29.4 94 73 82 0 3/5/2012 0 28.6 21.9 25.1 86 64 76 0 3/6/2012 0 46.8 22.2 34.6 81 46 64 0 3/7/2012 0 67.5 44.3 55.3 56 34 46 5.3 3/8/2012 0.43 61 34.8 52.2 97 51 76 2.1 3/9/2012 0 37 28.1 33.7 92 59 74 0 3/10/2012 0 44.1 23.3 33.8 81 39 56 0 3/11/2012 0 62 36.1 48.5 65 32 47 0 3/12/2012 0.27 61.8 46.9 52.9 94 43 73 2.8 3/13/2012 0.07 66.8 47 58.7 96 46 73 8.7 3/14/2012 0 74.5 34.6 55.1 90 35 59 5.1 3/15/2012 0.18 75.9 57.3 63.1 93 48 71 13 3/16/2012 0.19 65.1 49.8 58.9 97 80 90 8.9 3/17/2012 0 77.5 48.4 61.5 98 52 83 11.4 3/18/2012 0.09 75.9 58.6 64.4 96 61 76 14.4 3/19/2012 0.18 72.8 55.7 62.5 98 66 88 12.5

Continued

107 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 3/20/2012 0.03 79.9 58.3 64.6 91 49 80 14.6 3/21/2012 0 78.6 60 67.9 85 53 71 17.8 3/22/2012 0 78.9 55.4 66.9 90 50 72 16.8 3/23/2012 0 73.6 49.2 58.3 95 59 80 8.3 3/24/2012 0.68 67 44.5 53.1 97 81 95 3 3/25/2012 0 57.4 42.5 47.6 98 78 94 0 3/26/2012 0 45.5 33.6 38.2 87 45 67 0 3/27/2012 0 52.1 24.2 39.2 87 32 53 0 3/28/2012 0.01 69.7 44 57.3 83 36 57 7.3 3/29/2012 0 43.8 38.4 39.9 85 72 78 0 3/30/2012 0.26 48.5 31 39.3 95 55 79 0 3/31/2012 0 40.8 30.3 37.1 96 86 92 0 4/1/2012 0 52.4 28.7 39.6 96 69 89 0 4/2/2012 0 48.9 32.9 42.6 94 41 75 0 4/3/2012 0 64.7 29.2 44.3 95 28 66 0 4/4/2012 0 51.9 39.4 45.6 87 56 73 0 4/5/2012 0 43.5 29.1 38 95 63 79 0 4/6/2012 0 50.7 29.3 41.3 94 38 68 0 4/7/2012 0 55.5 27 43.2 95 27 61 0 4/8/2012 0 56.3 36.2 47.4 87 41 61 0 4/9/2012 0 54.4 41.8 47.6 87 42 69 0 4/10/2012 0.08 47.4 34.2 41.1 94 54 75 0 4/11/2012 0.01 46.4 35.1 40.4 92 70 84 0 4/12/2012 0 52.5 30 42.8 96 44 72 0 4/13/2012 0 58.1 29.3 44.1 93 40 66 0 4/14/2012 0.02 59 41.7 51.2 90 47 72 1.1 4/15/2012 0.08 81 55.3 66.1 94 45 75 16.1 4/16/2012 0 81.6 52.4 68.8 74 42 62 18.8 4/17/2012 0 52.2 36.3 47.1 93 59 74 0 4/18/2012 0 53.7 32.3 43.6 96 54 78 0 4/19/2012 0 70.3 45.3 58.2 79 46 65 8.2 4/20/2012 0.06 79.1 47.8 65 94 36 60 14.9 4/21/2012 0.25 47.6 40.1 41.5 96 92 95 0 4/22/2012 0 43.9 41.2 42.2 91 76 82 0

Continued

108 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 4/23/2012 0.03 47.4 37.6 42.6 92 51 71 0 4/24/2012 0 54.1 33.9 43.9 90 39 65 0 4/25/2012 0 57.6 30.3 46.7 95 34 61 0 4/26/2012 0 63.5 42.6 51.1 89 48 68 1 4/27/2012 0 47 29.6 40.8 87 42 63 0 4/28/2012 0 46.4 28.2 37.7 93 44 70 0 4/29/2012 0 58.6 25.8 42.4 93 26 65 0 4/30/2012 0.79 73.8 33 49.8 96 36 69 0 5/1/2012 0.19 57.5 49.6 53.3 98 85 94 3.3 5/2/2012 0.01 84.5 51.9 67.5 96 56 80 17.5 5/3/2012 0 85.8 59.1 74.9 97 57 75 24.9 5/4/2012 0.33 80.6 60.8 67.6 96 59 84 17.6 5/5/2012 0 62.3 49.3 55.9 95 69 81 5.8 5/6/2012 0 64 42.6 55.2 96 40 66 5.1 5/7/2012 0.23 75.2 53.8 61.5 96 66 84 11.4 5/8/2012 0.48 66.5 54.5 59.9 98 62 89 9.9 5/9/2012 0 66.9 49.3 57.3 91 56 77 7.2 5/10/2012 0 57.4 47.3 51.5 91 57 74 1.5 5/11/2012 0 67.8 40.4 56.4 93 37 62 6.4 5/12/2012 0 75.2 51.3 62.9 79 35 56 12.9 5/13/2012 0 69.4 50.4 58.9 94 48 75 8.9 5/14/2012 0 68.5 47.9 59.2 97 54 78 9.1 5/15/2012 0 76.4 46.3 62.2 97 36 71 12.1 5/16/2012 0 66 40.2 56.2 94 55 73 6.1 5/17/2012 0 59.7 34.9 48.7 96 39 71 0 5/18/2012 0 71.2 37.5 56 95 37 67 6 5/19/2012 0 82.4 49.9 67 86 34 59 17 5/20/2012 0 85.4 53 70.7 88 35 62 20.6 5/21/2012 0 83.4 61.7 72.6 90 41 61 22.5 5/22/2012 0 63.5 53 59.5 95 80 88 9.4 5/23/2012 0 70.6 50.4 60.3 97 59 83 10.3 5/24/2012 0 85.2 57 73.2 95 48 71 23.2 5/25/2012 0 89.5 67.4 77 93 53 72 27 5/26/2012 0 76.9 61 68.7 96 49 77 18.7

Continued

109 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 5/27/2012 0.02 86.8 57.4 68.7 93 52 80 18.6 5/28/2012 0 91.7 68.1 79.8 93 49 73 29.7 5/29/2012 0 81.1 63.3 75.2 91 59 77 25.1 5/30/2012 0 71.8 53.9 66.1 93 47 69 16 5/31/2012 0 65.1 53.4 60.2 94 61 73 10.2 6/1/2012 1.11 70.3 54.5 60.5 97 67 89 10.4 6/2/2012 0.17 72.7 50.1 60.3 91 41 69 10.2 6/3/2012 0.32 72.6 55 60.5 95 52 82 10.5 6/4/2012 0 63.3 49.4 56.6 96 74 88 6.6 6/5/2012 0.06 64.3 49.8 57.3 95 62 82 7.3 6/6/2012 0 72 45.2 60.3 97 51 75 10.2 6/7/2012 0 74.2 51 63.6 97 55 77 13.5 6/8/2012 0 78.7 52.5 67.2 94 40 66 17.1 6/9/2012 0 84.5 64.8 73.3 82 38 56 23.2 6/10/2012 0 86 63.4 75.7 84 40 59 25.7 6/11/2012 0.02 83.6 64.8 73.3 96 51 78 23.3 6/12/2012 0.04 80.1 63.6 72.5 97 64 85 22.5 6/13/2012 0 65.7 50.3 58.8 95 66 76 8.8 6/14/2012 0 73.5 48.6 62.4 96 59 77 12.4 6/15/2012 0 85.4 55.6 71.5 91 48 71 21.4 6/16/2012 0 85.4 63.4 74.8 82 50 66 24.7 6/17/2012 0.37 80.4 65.2 72 93 63 77 22 6/18/2012 0.01 84.5 66.2 74.6 96 56 80 24.6 6/19/2012 0 90 69.1 79.9 89 51 70 29.8 6/20/2012 0 88.9 71.8 81.2 83 52 66 31.2 6/21/2012 0 91.1 69.7 81.4 92 44 64 31.4 6/22/2012 0 77.5 61.8 71.6 97 63 83 21.6 6/23/2012 0 76.7 57.9 67.7 96 44 72 17.6 6/24/2012 0 83.4 56.3 70.7 93 44 68 20.6 6/25/2012 0.35 71.3 62.4 65.7 95 51 73 15.7 6/26/2012 0 74.6 61.3 67.4 78 49 68 17.4 6/27/2012 0 81.3 56.8 70.1 94 36 66 20.1 6/28/2012 0 89 65.5 77.8 72 44 58 27.7 6/29/2012 0 85.2 70.7 78.9 93 53 72 28.9

Continued

110 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 6/30/2012 0 86 61.9 75.2 88 44 67 25.2 7/1/2012 0 83 65.2 76.5 90 44 67 26.5 7/2/2012 0 86.3 60.9 74.1 96 43 74 24 7/3/2012 1.36 81.7 64.3 71.7 97 61 83 21.7 7/4/2012 0 91.5 67.9 78.6 96 59 83 28.5 7/5/2012 0 85.6 71.4 77.8 95 61 80 27.8 7/6/2012 0 89.6 69.7 79.8 96 61 81 29.7 7/7/2012 0.1 92.1 70.6 81.1 96 65 80 31.1 7/8/2012 0.2 81 70.9 75.9 97 57 78 25.8 7/9/2012 0 78.3 60.1 71.4 94 51 72 21.4 7/10/2012 0.01 79 57.6 68.5 96 49 76 18.5 7/11/2012 0 82.5 55.1 70.4 96 38 68 20.3 7/12/2012 0 86.3 58.1 73.7 91 55 72 23.6 7/13/2012 0 88.7 64.3 76.9 90 44 65 26.9 7/14/2012 0 83.4 59.8 71.9 94 64 82 21.9 7/15/2012 1.01 85 69.6 76 97 68 87 25.9 7/16/2012 0.01 84.3 67.3 76.1 97 61 82 26.1 7/17/2012 0 93.2 72.7 83.9 80 46 64 33.9 7/18/2012 0 84.4 68.5 77.4 96 66 83 27.4 7/19/2012 0.47 81.1 65.9 70.8 97 71 92 20.7 7/20/2012 0.01 71.4 63.6 67.1 95 77 87 17 7/21/2012 0 77.5 58.2 68.7 97 68 84 18.7 7/22/2012 0 87 66 75.7 94 60 78 25.6 7/23/2012 0 93.3 73.4 83 82 45 65 33 7/24/2012 0 85.8 70.3 77 93 55 74 27 7/25/2012 0 86.5 55.2 73.1 96 38 63 23.1 7/26/2012 0.93 83.6 70.3 76.1 97 56 86 26 7/27/2012 0 80.1 69.4 74.1 97 68 88 24.1 7/28/2012 0.07 78.1 67.4 72 97 74 89 21.9 7/29/2012 0 79.1 58.7 71.2 97 52 82 21.2 7/30/2012 0 85.1 57.2 71.9 94 48 74 21.8 7/31/2012 0 87 66.7 75.3 93 51 76 25.3 8/1/2012 0 80.4 61.5 71.5 97 58 82 21.4 8/2/2012 0 88.4 60.5 72.5 97 44 78 22.5

Continued

111 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 8/3/2012 0 93.1 66.6 79.5 87 40 66 29.4 8/4/2012 0 92.5 72.9 82.7 92 52 71 32.6 8/5/2012 0.17 82.5 69.4 77.1 94 72 83 27 8/6/2012 0 75.9 56.3 69.3 93 51 69 19.3 8/7/2012 0 81.6 56.1 69.5 94 52 74 19.5 8/8/2012 0 84.7 61.9 74.3 91 62 77 24.2 8/9/2012 0.16 77.4 58.9 68.1 96 64 85 18.1 8/10/2012 0.22 73.8 64.2 67.5 96 75 91 17.5 8/11/2012 0.64 71.2 58.7 64.2 96 70 88 14.2 8/12/2012 0.21 75.5 62.4 67.1 97 67 87 17.1 8/13/2012 0.04 80.6 60.4 69 95 49 79 19 8/14/2012 0.09 72 61.1 66.8 97 81 91 16.7 8/15/2012 0 77.3 59.1 68.6 97 64 85 18.6 8/16/2012 0 84.4 60.1 72.3 96 56 77 22.3 8/17/2012 0.08 74.6 62.5 70.2 92 61 77 20.2 8/18/2012 0 71.3 51.5 63 96 48 74 13 8/19/2012 0 75.9 50.9 63.3 90 47 72 13.2 8/20/2012 0 74.9 54.9 65.1 95 54 78 15 8/21/2012 0 76.3 52.5 64.6 96 51 77 14.5 8/22/2012 0.01 77.9 55.6 66.2 96 51 77 16.1 8/23/2012 0 82.3 57.7 69.7 90 45 69 19.6 8/24/2012 0 87.8 57.6 72.7 91 39 68 22.6 8/25/2012 0 90.1 66.3 77 86 36 64 26.9 8/26/2012 0 87.3 64.6 75.4 85 51 70 25.3 8/27/2012 1.28 72.9 65.6 69.4 98 79 92 19.4 8/28/2012 0 75.4 64.3 70.4 98 70 84 20.4 8/29/2012 0 71.9 53.4 66.1 96 56 77 16 8/30/2012 0 81.1 51.4 65.2 96 42 78 15.2 8/31/2012 0 89.4 63.1 77.1 79 42 64 27.1 9/1/2012 0 82.4 64.7 73.9 95 57 79 23.9 9/2/2012 0 80.6 66.2 73.4 93 57 76 23.3 9/3/2012 0 89.6 67 77.3 95 62 82 27.2 9/4/2012 0.41 80.8 68.4 73.4 97 78 91 23.4 9/5/2012 0 83.5 63.2 72.1 98 61 87 22.1

Continued

112 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 9/6/2012 0 81.2 63.7 73 96 64 86 22.9 9/7/2012 0 83.1 64 72 97 51 82 22 9/8/2012 1.2 71.3 61 65.6 97 64 83 15.5 9/9/2012 0.26 68.5 57.9 63.1 96 51 75 13 9/10/2012 0 68.7 48 60.1 94 48 70 10.1 9/11/2012 0 75.4 48.5 61.1 94 47 77 11.1 9/12/2012 0 81.1 54.5 65.5 90 29 70 15.5 9/13/2012 0 81.2 59.3 68.7 90 49 71 18.7 9/14/2012 0.34 72.9 49.6 62 99 74 86 12 9/15/2012 0.01 66.3 47.5 56.7 99 51 81 6.6 9/16/2012 0 71.4 46.1 58 93 48 76 8 9/17/2012 0 74.3 50.7 62.3 91 40 67 12.3 9/18/2012 0.27 66.3 54.7 60.7 97 59 84 10.7 9/19/2012 0 62.5 46.4 54.2 83 44 61 4.1 9/20/2012 0 70.6 43.5 58.4 86 44 62 8.3 9/21/2012 0.08 70 53.2 62.5 95 37 66 12.5 9/22/2012 1.19 60.8 46.7 53.1 99 68 92 3.1 9/23/2012 0.08 57.8 43 48.6 97 54 85 0 9/24/2012 0.35 60 42.4 50.4 96 42 73 0.3 9/25/2012 0.01 66 47.3 56.4 92 52 68 6.3 9/26/2012 0.07 63.5 56.9 60.7 98 90 94 10.7 9/27/2012 0 61.6 46.3 56.4 94 58 76 6.3 9/28/2012 0 61 44.4 54.7 98 56 78 4.7 9/29/2012 0 61.6 44.9 53.1 94 58 80 3.1 9/30/2012 0.02 60.4 42.6 51.3 98 62 86 1.3 10/1/2012 0 63.9 41 52.2 98 65 83 2.2 10/2/2012 0.43 67 52.6 59.1 100 80 95 9.1 10/3/2012 0 75.7 56.6 64.4 100 59 89 14.4 10/4/2012 0 73.4 56.3 62.6 90 49 77 12.5 10/5/2012 0.5 65.5 50.5 59 97 75 87 9 10/6/2012 0.57 52 45.6 48.4 97 59 78 0 10/7/2012 0.38 46.7 40.9 43.6 98 74 90 0 10/8/2012 0.1 52.3 36.5 42.9 95 60 82 0 10/9/2012 0.01 58.9 34.4 45.4 94 43 74 0

Continued

113 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 10/10/2012 0.67 51.6 43.1 45.8 96 52 81 0 10/11/2012 0 57.4 36.2 47.3 81 40 55 0 10/12/2012 0.08 50.2 30.4 43.5 94 54 73 0 10/13/2012 0.07 59.6 30.2 45.2 89 43 70 0 10/14/2012 0.08 75.3 56.2 65.8 86 53 74 15.8 10/15/2012 0.23 65.9 49 53.4 95 68 80 3.4 10/16/2012 0 53.3 39.7 47.5 95 64 75 0 10/17/2012 0 70.4 44 56.2 84 46 63 6.2 10/18/2012 0.04 66.5 47.4 55.1 88 50 70 5 10/19/2012 0.08 63.5 42.5 52 95 43 73 1.9 10/20/2012 0.18 52.7 43.7 47.8 93 66 85 0 10/21/2012 0.11 57 38.3 49 96 56 82 0 10/22/2012 0 72.4 38.7 55.7 93 47 71 5.7 10/23/2012 0.1 66.9 57.9 61.7 97 65 82 11.6 10/24/2012 0.01 76.2 54.8 62.4 100 57 84 12.3 10/25/2012 0 81.3 58.3 68.3 79 32 57 18.3 10/26/2012 0.03 66.1 47.6 56.2 97 52 77 6.1 10/27/2012 1.08 47.9 43.6 46.2 97 83 91 0 10/28/2012 0.79 45.9 40.3 42.3 96 83 91 0 10/29/2012 1.71 42.4 40.1 41 96 92 94 0 10/30/2012 0.74 51.8 41 45.6 98 76 92 0 10/31/2012 0.68 45.8 39.8 41.9 97 90 95 0 11/1/2012 0.24 43.2 38.8 41 96 63 89 0 11/2/2012 0.02 42.3 38 39.8 88 65 74 0 11/3/2012 0.08 41 35.9 38.6 91 71 81 0 11/4/2012 0 39.4 34.7 36.8 77 67 72 0 11/5/2012 0 38.4 33.2 35.2 80 67 73 0 11/6/2012 0 40.6 26.3 34.6 89 59 71 0 11/7/2012 0 41.8 25.8 33.6 87 53 71 0 11/8/2012 0 42.2 23.1 35.1 94 60 76 0 11/9/2012 0 47.8 30 38 95 66 84 0 11/10/2012 0.1 59.9 40.8 50 95 53 76 3.9 11/11/2012 0 69 51 59.9 59 33 46 9.9 11/12/2012 0.51 66.4 35.7 54.1 96 37 67 4

Continued

114 Table A.1 continued Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 11/13/2012 0.02 35.6 31.8 33.2 86 71 79 0 11/14/2012 0 37.9 26.3 33.6 91 59 78 0 11/15/2012 0 42.3 25 33.1 95 58 78 0 11/16/2012 0 45.9 24.8 33.7 97 65 86 0 11/17/2012 0 51.8 24.2 35.7 98 52 86 0 11/18/2012 0 53.6 27 39.6 98 46 76 0 11/19/2012 0 51.7 33.9 41.1 92 52 75 0 11/20/2012 0 53 34.2 41.5 93 48 78 0 11/21/2012 0 55.2 27 38.9 97 45 85 0 11/22/2012 0 60.8 32.6 46.7 94 47 65 0 11/23/2012 0.04 52.7 33.3 45.4 92 54 71 0 11/24/2012 0 34.8 31.4 32.6 69 56 63 0 11/25/2012 0.03 37.1 25.7 31.5 94 62 74 0 11/26/2012 0 37.9 31.9 35.5 74 60 69 0 11/27/2012 0 36.4 23.4 31.9 85 61 70 0 11/28/2012 0 35.3 23.5 30.4 83 70 75 0 11/29/2012 0 46.6 28.7 36.1 82 36 61 0 11/30/2012 0 46.2 31.4 37.7 92 51 70 0 12/1/2012 0 54.3 29.5 42.9 94 61 77 0 12/2/2012 0.81 54.6 47.8 51.9 98 65 87 1.8 12/3/2012 0 58.9 47.1 53.6 100 90 96 3.5 12/4/2012 0.35 61.3 43 54.6 99 73 86 4.5 12/5/2012 0 44.5 30.6 36.3 89 62 76 0 12/6/2012 0 43.3 23.1 32.9 92 47 72 0 12/7/2012 0 45.2 36.1 41 98 64 86 0 12/8/2012 0.19 46.9 35.3 42.1 99 85 97 0 12/9/2012 0.13 51 31.5 39.4 98 70 87 0 12/10/2012 0.18 54.9 34.8 43.6 99 82 93 0 12/11/2012 0.02 36.6 29.2 33.4 93 64 79 0 12/12/2012 0.02 40.3 24.9 30.7 94 59 78 0 12/13/2012 0 43.2 22.2 32.3 91 44 70 0 12/14/2012 0 43.3 27.4 35.1 97 57 74 0 12/15/2012 0 45.3 27.2 37.6 97 49 71 0 12/16/2012 0 58.2 44.5 51.3 92 57 72 1.3

Continued

115 Table A.1 continued

Max. Min. Avg. Max. Min. Avg. Precip. Air Air Air Rel. Rel. Rel. Date GDD (in) Temp. Temp. Temp. Hum. Hum. Hum. (F) (F) (F) (%) (%) (%) 12/17/2012 0.03 50.4 40.1 43.8 96 82 87 0 12/18/2012 0.78 40.8 32.5 37.1 98 74 90 0 12/19/2012 0 40.8 31.2 36.6 97 83 91 0 12/20/2012 0.17 45.9 31.5 39.5 98 69 84 0 12/21/2012 0.15 42.5 29.7 32.8 98 69 88 0 12/22/2012 0.03 32.1 29.5 30.4 95 67 79 0 12/23/2012 0 35.5 19.5 28.2 87 69 79 0 12/24/2012 0.04 35.4 24.5 29.7 97 65 80 0 12/25/2012 0.01 34.9 30.2 31.9 97 67 85 0 12/26/2012 0.46 31.1 25.6 27.3 97 69 84 0 12/27/2012 0.08 31.5 25.5 28.3 96 80 86 0 12/28/2012 0 31.9 17.4 27.4 94 72 80 0 12/29/2012 0.12 31.1 20.3 27.3 96 83 91 0 12/30/2012 0.01 31.3 20 26.8 97 76 83 0 12/31/2012 0.03 33.8 17.1 26.8 95 65 80 0

116