Environmental and cultural factors affecting the ...

Environmental and cultural factors affecting the persistence and efficacy of fungicides on golf

course turfgrass.

By

Paul Lawrence Koch

A dissertation submitted in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

(Plant Pathology)

at the

UNIVERSITY OF WISCONSIN – MADISON

2012

Date of final oral examination: 7/26/2012

The dissertation is approved by the following members of the Final Oral Committee:

James P. Kerns, Assistant Professor, Plant Pathology

Patricia S. McManus, Professor, Plant Pathology

Douglas I. Rouse, Professor, Plant Pathology

John C. Stier, Professor, Horticulture

Nancy P. Keller, Professor, Medical Microbiology

i

ABSTRACT

Successful management of turfgrass diseases such as Microdochium patch and dollar spot

on intensively-maintained golf course turf requires fungicide applications throughout the year.

Repeat fungicide applications can have negative financial, environmental, and toxicological

consequences and their use should be limited when possible. Research was conducted to

determine the factors that influence degradation of the common turfgrass fungicides

chlorothalonil and iprodione in a winter environment and under varying temperatures from 2009-

2012. Soil temperature, snow melt, and winter rains had the largest influence on fungicide

degradation in a winter environment. Photodegradation, as influenced by the presence or

absence of snow cover, did not impact fungicide degradation during winter. Temperature was

directly related to degradation rates of both fungicides. The most likely mechanisms influencing

degradation at higher temperatures were plant and bacterial metabolism. Strategies for reducing

fungicide inputs were also explored. Alternative fungicide application timings in the spring,

made well before the onset of dollar spot symptoms, delayed the onset of disease symptoms and

reduced the annual number of fungicide applications by up to two applications without

sacrificing turf quality. Disease-resistant creeping bentgrass cultivars such as ‘Declaration’ and

‘Memorial’ reduced dollar spot and Typhula blight severity compared to older cultivars such as

‘Penncross,’ though not to the degree where fungicide applications could be eliminated or

drastically reduced. The cumulative effect of these studies has introduced new methods of

studying and understanding the impact of the environment on turfgrass fungicides, and how

simple strategies available today can reduce fungicide usage and enable more sustainable

turfgrass management in the future.

ii

ACKNOWLEDGEMENTS

There are numerous individuals I would like to thank for their contributions to the

completion of this dissertation, and I will name just a few here. First, I would like to thank my

major advisor Dr. Jim Kerns for his guidance and patience through the many peaks and valleys

of my time as a Ph.D. candidate. In addition, I would like to thank the members of my Ph.D.

committee for their guidance and excellent contributions to the direction of each research

project; Dr. Nancy Keller, Dr. Patricia McManus, Dr. Doug Rouse, and Dr. John Stier. I would

also like to thank the labs of Dr. Amy Charkowski and Dr. Jeri Barak for their guidance on

ELISA methodology and bacterial quantification, respectively. Nick Keuler from the College of

Agriculture and Life Sciences Statistical Consulting Service provided invaluable support in the

analysis of many complicated sets of data. Of utmost importance have been my friends and

family, both inside the department and out, who have provided support and needed relief from

the everyday grind of scientific research. I would like to reserve my most sincere thank you to

the members of the Kerns lab, especially our undergraduate student assistants. Tom Huncosky,

Sam Soper, Ben van Ryzin, Jake Soper, P. J. Liesch, and Renee Rioux have provided assistance

and support whenever and wherever needed, and completion of this project would have been

impossible without their unwavering assistance.

iii

FOREWARD

Each chapter in this dissertation has been developed with submission to a particular

journal in mind, which has influenced the structure of each chapter. Chapter 1 was developed for

submission into the journal Crop Protection. Chapter 2 and Chapter 3 were developed for

submission into the journal Plant Disease. Chapter 4 was developed for submission into the

International Journal of Turfgrass Research. Chapter 5 was developed for submission into

Applied Turfgrass Science, and is the only chapter to deviate significantly from the traditional

‘Introduction’, ‘Materials and Methods’, ‘Results’, and ‘Discussion.’ For consistency, the

‘Literature Cited’ section in each chapter was formatted according to specifications outlined in

Plant Disease.

iv

TABLE OF CONTENTS

Abstract ............................................................................................................................i

Acknowledgements ..........................................................................................................ii

Foreward ..........................................................................................................................iii

List of tables .....................................................................................................................v

List of figures ...................................................................................................................viii

INTRODUCTION ...........................................................................................................1

CHAPTER 1 ....................................................................................................................13

Modification of commercially-available ELISA kits to determine chlorothalonil

and iprodione concentrations on golf course turfgrass.

CHAPTER 2 ....................................................................................................................39

Effect of snow cover on the duration of Microdochium patch control provided by

chlorothalonil and iprodione on golf course turfgrass.

CHAPTER 3 ....................................................................................................................84

Influence of temperature on chlorothalonil and iprodione degradation and in vitro

fungal sensitivity.

CHAPTER 4 ....................................................................................................................123

Impact of novel fungicide timings on the development of snow mold and dollar spot

on golf course turfgrass.

CHAPTER 5 ....................................................................................................................144

Resistance of creeping bentgrass cultivars to dollar spot and snow mold.

CONCLUSION ................................................................................................................158

v

LIST OF TABLES

CHAPTER 1:

Table 1. Iprodione concentration as calculated using a modified Horiba SmartAssay®

ELISA method and a gas chromatography/electron capture detection (GC/ECD) method.

ELISA absorbance values at 450 nm were converted to ELISA fungicide concentrations

using the equation of the linear regression of the absorbance of standard iprodione

concentrations provided by Horiba. All turfgrass sampling was completed 1 h

following iprodione application on creeping bentgrass (Agrostis stolonifera ‘Penncross’)

maintained at a 1.2 cm height ................................................................................................. 34

Table 2. Absorbance values for high and low iprodione standard concentrations

using the Iprodione Horiba SmartAssay® analysis kit. The regression equation

produced from the high and low standards was used to convert absorbance values

from each sample mg of iprodione per L ................................................................................ 35

Table 3. Chlorothalonil concentration as calculated using a modified Horiba

SmartAssay® ELISA method and a gas chromatography/electron capture

detection (GC/ECD) method. ELISA absorbance values at 450 nm were

converted to ELISA fungicide concentrations using the equation of the linear

regression of the absorbance of standard chlorothalonil concentrations provided

by Horiba. All turfgrass sampling was completed 1 h following chlorothalonil

application on creeping bentgrass (Agrostis stolonifera ‘Penncross’) maintained

at a 1.2 cm height .................................................................................................................... 36

Table 4. Absorbance values of high and low chlorothalonil standard

concentrations using the chlorothalonil Horiba SmartAssay® analysis.

The regression equation produced from the high and low standards was

used to convert absorbance values for each sample to mg of chlorothalonil per L ................ 37

Table 5. Time and cost comparison of ELISA SmartAssay® analysis versus

gas chromatographic methods by the University of Wisconsin and Horiba, Ltd ................... 38

CHAPTER 2:

Table 1. Analysis of variance (ANOVA) of Microdochium patch for turfgrass

cores sprayed with iprodione and chlorothalonil and sampled from snow and

non-snow covered plots at weekly or biweekly intervals during the winter of

2009-2010 in Verona, WI ....................................................................................................... 67

vi

Table 2. Analysis of variance (ANOVA) of Microdochium patch for turfgrass

cores sprayed with iprodione and chlorothalonil and sampled from snow and

non-snow covered plots at weekly or biweekly intervals during the winter of

2010-2011 in Verona, WI ....................................................................................................... 68

Table 3. Analysis of variance (ANOVA) of Microdochium patch severity for

turfgrass cores sprayed with iprodione and chlorothalonil and sampled from

snow and non-snow covered plots at weekly or biweekly intervals during the

winter of 2011-2012 in Verona, WI ........................................................................................ 69

Table 4. Analysis of variance (ANOVA) of iprodione concentration from

turfgrass cores sprayed with iprodione and sampled from snow and non-snow

covered plots at weekly or biweekly intervals during the winter of 2010-2011 in

Verona, WI .............................................................................................................................. 70

Table 5. Analysis of variance (ANOVA) of iprodione concentration from

turfgrass cores sprayed with iprodione and sampled from snow and non-snow

covered plots at weekly or biweekly intervals during the winter of 2011-2012 in

Verona, WI. ............................................................................................................................. 70

CHAPTER 3:

Table 1: Analysis of variance (ANOVA) of iprodione concentration from

turfgrass clippings collected from cores sampled at the OJ Noer Turfgrass Research

Facility in Verona, WI. Study was performed once during the summer of 2010

and replicated twice during the summer of 2011. Turfgrass cores were sprayed

with either iprodione alone or iprodione mixed with chlorothalonil and placed

immediately in a 10, 20, or 30°C for 0, 7, 14, or 21 days. ...................................................... 109

Table 2: Analysis of variance (ANOVA) of iprodione concentration from

turfgrass clippings collected from cores sampled at the OJ Noer Turfgrass

Research Facility in Verona, WI. Study was replicated twice during the summer

of 2011. Turfgrass cores were sprayed with either iprodione alone or iprodione

mixed with chlorothalonil and placed immediately in a 10, 20, or 30°C for 0, 7, 14,

21, 28, or 35 days. ................................................................................................................... 110

Table 3: Pair-wise comparison of iprodione concentration analyzed from turfgrass

clippings collected from cores at 10, 20, and 30°C within each analysis date.

Cores were analyzed at 0, 7, 14, and 21 days following the iprodione application.

P-value represents Tukey’s adjusted p-value. ........................................................................ 111

Table 4: Pair-wise comparison of iprodione concentration analyzed from turfgrass

clippings collected from cores at 10, 20, and 30°C within each analysis date.

vii

Cores were analyzed at 0, 7, 14, 21, 28, and 35 days following the iprodione

application. P-value represents Tukey’s adjusted p-value ..................................................... 112

Table 5: Analysis of variance (ANOVA) of chlorothalonil concentration

from turfgrass clippings collected from cores sampled at the OJ Noer

Turfgrass Research Facility in Verona, WI. Study was replicated twice

during the summer of 2011. Turfgrass cores were sprayed with either

chlorothalonil alone or chlorothalonil mixed with iprodione and placed

immediately in a 10, 20, or 30°C for 0, 7, 14, 21 or 28 days .................................................. 113

Table 6: Pair-wise comparison of chlorothalonil concentration analyzed

from turfgrass clippings collected from cores at 10, 20, and 30°C within

each analysis date. Cores were analyzed at 0, 7, 14, 21, and 28 days following

the chlorothalonil application. P-value represents Tukey’s adjusted p-value ........................ 114

CHAPTER 4:

Table 1. Dates of fungicide application for each treatment in 2009, 2010,

and 2011 at the OJ Noer Turfgrass Research Center in Verona, WI and at

Sentryworld Golf Course in Stevens Point, WI. Applications were made to

the fairway and putting green plots at the OJ Noer on the same date. .................................... 138

CHAPTER 5:

Table 1. Mean number of dollar spot foci per plot from 2009 - 2011.

Means followed by the same letter do not significantly differ. LSD = 70.4.......................... 153

Table 2. Mean snow mold severity per plot from 2010 – 2012.

Means followed by the same letter do not significantly differ. LSD = 10.99........................ 154

viii

LIST OF FIGURES

CHAPTER 2:

Figure 1. Experimental design of the winter fungicide degradation

study at the OJ Noer Turfgrass Research Facility in Verona, WI. Treatments

1-4 are a non-treated control, chlorothalonil, iprodione, and a tank mixture

of both fungicides under snow cover, respectively. Treatments 5-8 are the

same fungicide treatments kept free of snow cover. Fungicide treatments are

randomized within snow treatment in replications 2-4. .......................................................... 71

Figure 2. Template used to count colony forming units (CFUs) on a 10 cm

diameter Petri dish. CFUs were counted from either the diagonal A or B

sections, beginning at segment 8. If less than 30 CFUs were observed in

segment 8, then CFUs in segment 9 were counted as well, and so on until

30 colony forming units were counted.................................................................................... 72

Figure 3. Severity of Microdochium patch as affected by fungicide treatment

and days after application in 2009-2010. Individual points represent average

disease severity values taken every 7 d up to 90 d following fungicide application.

Error bars indicate standard errors of the means. A – Chlorothalonil-treated

turfgrass from snow-covered plots; B – Chlorothalonil-treated turfgrass from

non-snow covered plots; C – iprodione-treated turfgrass from snow-covered plots;

D – iprodione-treated turfgrass from non-snow covered plots ............................................... 73

Figure 4. Soil temperature from snow and non-snow covered plots at the OJ

Noer Turfgrass Research Facility during the winter of 2009-2010. Soil temperature

was recorded hourly at a 5 cm depth from Nov 20, 2009 through Mar 18, 2010

using a Spectrum Technologies® thermometer and Watchdog® data logger ........................ 74



disease severity values taken every 7-14 d up to 119 d following fungicide

application. Error bars indicate standard errors of the means. A – Chlorothalonil-

treated turfgrass from snow-covered plots; B – Chlorothalonil-treated turfgrass from

non-snow covered plots; C – iprodione-treated turfgrass from snow-covered plots;

D – iprodione-treated turfgrass from non-snow covered plots ............................................... 75

Figure 6. Soil temperature from snow and non-snow covered plots at the OJ Noer

Turfgrass Research Facility during the winter of 2010-2011. Soil temperature

was recorded hourly at a 5 cm depth from Nov 30, 2010 through Apr 7, 2011

using a Spectrum Technologies® thermometer and Watchdog® data logger ........................ 76



ix

disease severity values taken every 7 d up to 21 d following fungicide application.

Error bars indicate standard errors of the means. A – Chlorothalonil-treated

turfgrass from snow-covered plots; B – Chlorothalonil-treated turfgrass

from non-snow covered plots; C – iprodione-treated turfgrass from snow-

covered plots; D – iprodione-treated turfgrass from non-snow covered plots ........................ 77

Figure 8. Soil temperature from snow and non-snow covered plots at the

OJ Noer Turfgrass Research Facility during the winter of 2011-2012. Soil

temperature was recorded hourly at a 5 cm depth from Nov 29, 2011 through

Mar 18, 2012 using a Spectrum Technologies® thermometer and Watchdog®

data logger. .............................................................................................................................. 78

Figure 9. Concentration of iprodione as affected by snow cover and days

after application in 2010-2011. Individual points represent average iprodione

concentration taken every 7-14 d up to 119 d following fungicide application.

Error bars indicate standard errors of the means. .................................................................. 79

Figure 10. Concentration of iprodione as affected by snow cover and days

after application in 2011-2012. Individual points represent average iprodione

concentration taken every 7-14 d up to 84 d following fungicide application.

Error bars indicate standard errors of the means. ................................................................... 80

Figure 11. Concentration of iprodione as affected by placement in autoclaved

or non-autoclaved melted snow and hours kept in melted snow in 2011-2012.

Individual points represent average iprodione concentration taken 0, 1, 6, 24, or

96 h following placement in melted snow. Error bars indicate standard errors

of the means. .......................................................................................................................... 81

Figure 12. Concentration of chlorothalonil as affected by placement in

autoclaved or non-autoclaved melted snow and hours kept in melted snow in

2011-2012. Individual points represent average chlorothalonil concentration

taken 0, 1, 6, 24, or 96 h following placement in melted snow. Error bars indicate

standard errors of the means. ................................................................................................. 82

Figure 13. Bacterial quantification on turfgrass leaf blades treated with

chlorothalonil, iprodione, or a mixture of both fungicides from snow and

non-snow covered plots at the OJ Noer Turfgrass Research and Educational

Facility. Cores were sampled on Feb 21 and Mar 6, 2012. Error bars indicate

standard errors of the means. .................................................................................................. 83

x

CHAPTER 3:

Figure 1: Iprodione concentration as affected by temperature and

days following fungicide application on turfgrass clippings collected

from cores during the summer of 2010 and twice during the summer 2011.

Cores were immediately placed in growth chambers at 10, 20, or 30°C following

the fungicide application. Concentration was analyzed weekly for 3 weeks

during the summer of 2010 and 5 weeks during both 2011 analyses. Error

bars represent standard error for each temperature at each analysis date. A –

Iprodione concentration in both 2011 analyses through 35 days following the

application; B – Iprodione concentration in all 2010 and 2011 analyses runs

through 21 days following the application................................................................................115

Figure 2: Iprodione concentration from turfgrass clippings collected from

cores sampled from the OJ Noer Turfgrass Research Facility during the

summer of 2011. Cores were analyzed 0, 7, and 14 days following the

application. Error bars represent standard errors within each analysis date ............................117

Figure 3: Chlorothalonil concentration as affected by temperature and days

following fungicide application on turfgrass clippings collected from cores

twice during the summer 2011. Cores were immediately placed in growth

chambers at 10, 20, or 30°C following the fungicide application and concentration

analyzed weekly for 4 weeks. Error bars represent standard error for each

temperature at each analysis date .............................................................................................. 118

Figure 4: Chlorothalonil concentration from turfgrass clippings collected

from cores sampled from the OJ Noer Turfgrass Research Facility during

the summer of 2011. Cores were analyzed 0, 7, 14, 21, and 28 days following

the application. Error bars represent standard errors within each analysis date ......................119

Figure 5: In vitro fungicide sensitivity of Sclerotinia homoeocarpa on

chlorothalonil and iprodione-amended potato dextrose agar media at 10, 15,

20, 25, and 30°C. Fungicide sensitivity determined by calculating the estimated

concentration to inhibit 50% of fungal growth (EC50) of 2 S. homoeocarpa isolates

collected from creeping bentgrass (Agrostis stolonifera) in Madison, WI.

Error bars represent standard errors within each temperature ..................................................120

Figure 6: In vitro fungicide sensitivity of Microdochium nivale on

chlorothalonil and iprodione-amended potato dextrose agar media at 5, 10,

15, 20, and 25°C. Fungicide sensitivity determined by calculating the estimated

concentration to inhibit 50% of fungal growth (EC50) of 2 M. nivale isolates

collected from creeping bentgrass (Agrostis stolonifera) in Madison, WI. Error

bars represent standard errors within each temperature ............................................................121

xi

CHAPTER 4:

Figure 1. Mean number of dollar spot foci per plot on the putting green

plot at the OJ Noer Turfgrass Research Center in Verona, WI during the

summer of (A) 2009 and (B) 2010. Dates were analyzed individually, and

disease severity values were subjected to analysis of variance and mean

separations using the Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated

control; LF = late fall; LS = late spring; LF/LS = late fall + late spring;

EF/LF = early fall + late fall; ES/LS = early spring + late spring; All = early

fall + late fall + early spring + late spring; TP = traditional program ......................................139

Figure 2. Mean number of dollar spot foci per plot on the fairway plot

at the OJ Noer Turfgrass Research Center in Verona, WI during the

summer of 2009. Dates were analyzed individually, and disease severity

values were subjected to analysis of variance and mean separations using

the Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated control; LF =

late fall; LS = late spring; LF/LS = late fall + late spring; EF/LF = early fall +

late fall; ES/LS = early spring + late spring; All = early fall + late fall +

early spring + late spring; TP = traditional program ................................................................141

Figure 3. Mean snow mold severity per plot on the fairway plot at the OJ

Noer Turfgrass Research Center in Verona, WI during the springs of 2009,

2010, and 2011. Snow mold severity was visually assessed as percent area of

the plot affected. Dates were analyzed individually, and disease severity values

were subjected to analysis of variance and mean separations using the

Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated control; LF =

late fall; LS = late spring; LF/LS = late fall + late spring; EF/LF = early fall

+ late fall; ES/LS = early spring + late spring; All = early fall + late fall +

early spring + late spring; TP = traditional program ................................................................142

Figure 4. Mean snow mold severity per plot at Sentryworld Golf Course

in Stevens Point, WI during the springs of 2009 and 2010. Snow mold

severity was visually assessed as percent area of the plot affected. Dates

were analyzed individually, and disease severity values were subjected to

analysis of variance and mean separations using the Waller-Duncan k-ratio

t-test (k=100). NTC = Nontreated control; LF = late fall; LS = late spring;

LF/LS = late fall + late spring; EF/LF = early fall + late fall; ES/LS =

early spring + late spring; All = early fall + late fall + early spring + late spring;

TP = traditional program. ..........................................................................................................143

xii

CHAPTER 5:

Figure 1. Mean number of dollar spot foci per cultivar on September 29,

June 21, and August 11 in 2009, 2010, and 2011, respectively, at the

OJ Noer Turfgrass Research Center in Verona, WI. Error bars represent

standard error for each cultivar at each rating date. ..................................................................155

Figure 2. Mean snow mold severity per cultivar on March 18, April 7,

and March 18 of 2010, 2011, and 2012, respectively, at the OJ Noer

Turfgrass Research Center in Verona, WI. Error bars represent standard

error for each cultivar at each rating date .................................................................................156

Figure 3. Difference in gray snow mold severity between ‘Penncross’

creeping bentgrass and ‘Declaration’ creeping bentgrass on March 18,

2010 at the OJ Noer Turfgrass Research Facility in Verona, WI .............................................157

1

INTRODUCTION

2

Highly maintained turfgrass has become an important aspect of the urban and suburban

landscape in the past century. In the United States alone, 50 million acres of land is turfgrass

(National Turf Research Initiative, 2003). In Wisconsin alone, nearly 1.2 million acres of land is

turfgrass, third in total crop acreage behind hay and corn (Wisconsin Turf Industry Survey,

1999). Beard and Green (1994) reviewed the recreational, aesthetic, and environmental benefits

of healthy turfgrass. The recreational benefits of healthy turfgrass include surfaces for outdoor

activities that help prevent injury and are relatively affordable to maintain. The aesthetic

benefits of healthy turfgrass in a landscape have been shown to increase mental health, and well-

maintained landscapes can increase home property values by 10 to 15%. Turfgrasses also

provide environmental benefits in the urban and suburban landscape; including reduced soil

erosion, filtration and reduction of surface runoff, and carbon sequestration. Unfortunately,

healthy turfgrass also requires maintenance that can adversely affect the environment and human

health. Frequent mowing releases carbon dioxide and other byproducts of combustion into the

atmosphere (Priest et al., 2000). Irrigation is required in most locations to maintain a healthy

lawn throughout the year, which can strain scarce resources in arid climates (Beard and Green,

1994). In addition, the use of fertilizers and pesticides has been shown in rare cases to

contaminate both surface and ground water stores (Baird et al., 2000; Baris et al., 2010).

The most intensively managed turfgrass is found on golf courses, which make up 1.5

million acres of land in the United States. Golf course putting greens are the most intensively-

managed areas on golf courses, representing approximately 3% of total golf course turf acreage

(Lyman et al., 2007). Mowing heights on golf course putting surfaces can reach as low as 2.5

mm and daily irrigation is often required. Numerous fungal diseases can become problematic

under these intense management conditions. Management of fungal diseases on golf courses is

3

accomplished primarily through preventative fungicide applications, which can have non-target

and adverse environmental and toxicological effects (Baird et al., 2000; Baris et al., 2010).

Routine fungicide applications also administer a substantial financial burden, with season-long

protection of golf course putting greens costing between $7,000 and $10,000 (Vincelli and

Dixon, 2003).

The primary low temperature disease for turfgrass managers in temperate regions of the

world is Microdochium patch caused by the fungus Microdochium nivale (Fr.) Samuels & I. C.

Hallett (teleomorph Monographella nivalis (Schaffnit) E. Mueller). M. nivale has a relatively

wide host range and is a common pathogen of most turfgrasses, especially bentgrasses (Agrostis

spp.) and annual bluegrass (Poa annua L.). In addition, M. nivale can also cause disease on

wheat, oats, and barley and is part of the Fusarium head blight complex (Couch, 1995) . The

pathogen can be found in temperate climates around the world but is most prevalent in the

consistently cool, wet regions of the North American Pacific Northwest, United Kingdom, and

northern Europe. In these areas, Microdochium patch is the most common turfgrass disease all

year round (Mann and Newell, 2005).

Symptoms of Microdochium patch can vary depending on the environmental conditions.

When snow cover is not present, symptoms first appear as small, reddish or rust-colored spots

less than 5 cm in diameter. Under persistent moisture, symptoms may be streaked in a roughly

linear fashion by surface water flow or mechanical traffic due to the dispersal of conidia. Spots

may coalesce to form larger patches, but individual infection centers rarely expand beyond 20

cm. Under prolonged snow cover, larger and more circular patches of tan to bleached turf 30-60

cm in diameter may occur. In some cases, a thin pink ring can be observed around the perimeter

of the patch due to the production of sporodochia in response to sunlight (Smiley et al., 2005).

4

Microdochium patch on golf course turfgrass is managed primarily through one or two

fungicide applications in the fall prior to snow cover. These applications are expected to provide

protection for weeks or even months at a time. Recent winters with widely fluctuating

temperatures across the northern half of the United States have resulted in extended periods

without snow cover. Consequently, turfgrass fungicides have been exposed to periods of

extreme winter conditions. The effect of exposed turfgrass in a winter environment may lead to

increased rates of fungicide degradation when compared to fungicides under an insulating

blanket of snow. According to the book Fate and Management of Turfgrass Chemicals (Sigler et

al., 2000), the six physical and chemical processes that affect the fate of turfgrass chemicals are

solubility-based movement in water, sorption and desorption to surfaces, volatilization, plant

uptake, biotic degradation, and abiotic degradation. How these processes are affected by winter

conditions such as extreme temperatures, sunlight, and melting snow is unclear.

In temperate climates the most common warm-weather disease on golf course turfgrass is

dollar spot, caused by the fungus Sclerotinia homoeocarpa F. T. Bennett (Walsh et al., 1999).

Efforts to manage dollar spot through cultural or biological means have been ineffective

(Goodman and Burpee, 1991; Walsh et al., 1999). In intensively-managed turfgrass, successful

dollar spot management typically requires repeat fungicide applications throughout the growing

season. This has resulted in more fungicide applications made to manage dollar spot than any

other turfgrass disease in the United States (Vargas, 1994).

S. homoeocarpa has a wide host range among turfgrass species, but its primary impact is

on creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua L.) used for

golf course putting greens, tees, and fairways. Symptoms initially appear on the leaf blade as

small, straw-colored lesions with a reddish-brown border. In optimal environmental conditions

5

with temperatures between 18 and 30°C and relative humidity greater than 85%, multiple lesions

may coalesce and blight the entire leaf blade (Smiley et al., 2005). The fungus spreads locally

through contact with surrounding leaf tissue, forming distinct silver dollar-sized bleached

patches 3 to 5 cm in diameter on low-cut turfgrass (Endo, 1963).

Two of the most common fungicides used to manage Microdochium patch and dollar

spot are iprodione and chlorothalonil. Iprodione is a localized penetrant fungicide first registered

in the United States in 1979 (US EPA, 1998). Its biochemical mode of action is the disruption of

mitogen-activated protein histidine kinase, which interferes with mitotic cell division and

prevents germination of fungal spores and growth of mycelium (Tomlin, 2009). Iprodione has

low acute toxicities in every category measured, but is listed as a Group B2 (likely) human

carcinogen based on the development of tumors in mice livers and male mice Leydig cells (US

EPA, 1998). Iprodione has also been identified as a potential endocrine disruptor in numerous

toxicological studies (Andersen et al., 2002; Blystone et al., 2007; Ferraris et al., 2005; Ghisari

and Bonefield-Jorgensen, 2005; Long et al., 2003). Iprodione has a low to intermediate

persistence in the field, with estimates of half-life in the soil ranging from 7 to 171 days (Garcia-

Cazorla and Xirau-Vayreda, 1998; Klose et al., 2010; Leistra and Matser, 2004). The primary

mechanism for iprodione breakdown in the soil is through microbial metabolism, with bacteria

such as Pseudomonas and yeast such as Zygosaccharomyces identified as organisms that readily

metabolize iprodione to its primary metabolite; 3, 5 dichloroaniline (Mercadier et al., 1997;

Wang et al., 2004; Zadra et al., 2006). Research has also suggested that repeated applications of

iprodione can lead to increased rates of degradation in the soil, presumably due to buildup of

organisms that can rapidly degrade the parent compound (Garcia-Cazorla and Xirau-Vayreda,

1998; Mercadier et al., 1997; Klose et al., 2010, Walker 1987). Enhanced degradation was not

6

observed with iprodione on turfgrass leaf blades (Sigler et al., 2002). Iprodione can also be

degraded by photochemical means, which may be a more important form of degradation on

turfgrass leaf blades because of lower microbial populations relative to those found in the soil

(Hustert and Moza, 1997; Schwack et al., 1995; Sigler et al., 2002).

Chlorothalonil is a broad-spectrum, contact fungicide first registered for use in the United

States in 1966 (US EPA, 1999). Its biochemical mode of action is conjugation to thiols such as

glutathione, rapidly depleting their cellular levels and inhibiting glutathione-dependent reactions

involved in oxidative stress, glycolysis, and mitochondrial metabolism (Baier-Anderson and

Anderson, 2000; Parsons, 2001; Raman, 2005; Suzuki et al., 2004, Tomlin, 2009).

Chlorothalonil is not acutely toxic (Category IV) for oral or dermal exposures, but is acutely

toxic for inhalation (Category II) and ocular exposure (Category I) (US EPA, 1999). Despite the

general lack of acute toxicity, chlorothalonil has been classified by the EPA as a Category B2

carcinogen (likely human) based on tumors observed in the mouse forestomach and mouse renal

tubular epithelial cells (US EPA, 1999). Evidence for the same carcinogenic effects in humans is

disputed due to the lack of a forestomach in humans and the different mechanisms for renal

clearance than those seen in mice and rats (Wilkinson and Killeen, 1996). As assessed by the

EPA, chlorothalonil is ‘practically non-toxic’ to birds and small mammals, ‘relatively non-toxic’

to bees, and ‘very highly toxic’ to fish and aquatic invertebrates (US EPA, 1999). Chlorothalonil

is rapidly metabolized in the environment when microbial organisms are present, with soil half

life ranging from 3 to 20 days (Potter et al., 2001; Singh et al., 2002). In contrast to iprodione,

some evidence suggests that repeated chlorothalonil applications lead to decreased soil

degradation rates. This may be due to the suppressive effects of the primary chlorothalonil

7

metabolite, 4-hydroxychlorothalonil, which is more toxic then the parent compound (Singh et al.,

2002).

Chemical fungicide applications remain a critical component of disease management on

golf course turfgrass, and will remain so for the foreseeable future. A greater understanding of

the activity and persistence of common turfgrass fungicides will lead to more targeted, efficient

usage and a reduction in non-target effects. The goal of the research presented here was to

elucidate how fungicides interact in a turfgrass environment under a variety of conditions and

how that affects turfgrass disease management. In addition, potential strategies for reducing

chemical inputs were investigated and their effectiveness at both maintaining turfgrass quality

and reducing fungicide usage was determined.

LITERATURE CITED

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E. C. 2002. Effects of currently used pesticides in assays for estrogenicity,

androgenicity, and aromatase activity in vitro. Tox. and Appl. Pharm. 179: 1-12.

Baris, R. D., Cohen, S. Z., Barnes, N. L., Lam, J., Ma, Q. 2010. Quantitative analysis of over 20

years of golf course monitoring studies. Env. Tox. Chem. 29: 1224 – 1236.

Baird, J. H., Basta, N. T., Huhnke, R. L., Johnson, G. V., Payton, M. E., Storm, D. E.,

Wilson, C. A., Smolen, M. D., Martin, D. L., Cole, J. T. 2000. Best management

practices to reduce pesticide and nutrient runoff from turf. p. 268-293 in: Fate and

Management of Turfgrass Chemicals, J. M. Clark and M. P. Kenna, eds. ASC

Symposium Series 743, American Chemical Society, Washington DC.

Beard, J. B., Green, R. L. 1994. The role of turfgrasses in environmental protection and

8

their benefits to humans. J. Environ. Qual. 23: 452-460.

Blystone, C. R., Lambright, C. S., Furr, J., Wilson, V. S., Gray, L. E. 2007. Iprodione delays

male rat pubertal development, reduces serum testosterone levels, and decreases ex vivo

testicular testosterone production. Tox. Letters 174: 74-81.

Couch, H. B. 1995. Diseases of Turfgrasses, 3rd

ed. Krieger Publishing Co., Malabar,

FL.

Endo, R. M. 1963. Influence of temperature on rate of growth of five fungus pathogens of

turfgrass and rate of disease spread. Phytopathology 53: 857-861.

Ferraris, M., Flora, A., Chiesara, E., Fornasari, D., Luccetti, H., Marabini, L., Frigerio, S.,

Radice, S. 2005. Molecular mechanisms of the aryl hydrocarbon receptor activation by

the fungicide iprodione in rainbow trout (Oncorhynchus mykiss) hepatocytes. Aq. Tox.

72: 209-220.

Garcia-Cazorla, J., Xirau-Vayreda, M. 1998. Monitoring degradation of dicarboximide

fungicide residues in soils. J. Agric. Food Chem. 46: 2845-2850.

Ghisari, M., Bonefield-Jorgensen, E. C. 2005. Impact of environmental chemicals on the thyroid

hormone function in pituitary rat GH3 cells. Mol. Cel. Endocrinology 244: 31-41.

Goodman, D. M., and Burpee, L. L. 1991. Biological-control of dollar spot disease of creeping

bentgrass. Phytopathology 81: 1438-1446.

Hustert, K., Moza, P. N. 1997. Photochemical degradation of dicarboximide fungicides in the

presence of soil constituents. Chemosphere 35: 33-37.

Klose, S., Wu, B. M., Ajwa, H. A., Koike, S. T., Subbarao, K. V. 2010. Reduced efficacy of

rovral and botran to control Sclerotinia minor in lettuce production in the Salinas Valley

may be related to accelerated fungicide degradation in soil. Crop Protection 29: 751-756.

9

Leistra, M., Matser, A. M., 2004. Adsorption, transformation, and bioavailability of the

fungicides carbendazim and iprodione in soil, alone and in combination. J. Env. Sci. and

Health B 39: 1-17.

Long, M., Laier, P., Vinggard, A. M., Andersen, H. R., Lynggaard, J., Bonefield-Jorgensen, E.

C. 2003. Effects of currently used pesticides in the AhR-CALUX assay: comparison

between the human TV101L and the rat H4IIE cell line. Toxicology 194: 77-93.

Lyman, G. T., Throssell, C. S., Johnson, M. E., Stacey, G. A. 2007. Golf course profile

describes turfgrass, landscape, and environmental stewardship features. App. Turf. Sci.

10.1094/ATS-2007-1107-01-RS.

Mann, R. L., Newell, A. J. 2005. A survey to determine the incidence and severity of

Pests and diseases on golf course putting greens in England, Ireland, Scotland, and

Wales. Int. Turf. Res. Jnl. 10: 224-229.

Mercadier, C., Vega, D., Bastide, J. 1997. Iprodione degradation by isolated soil

microorganisms. FEMS Microbiology Ecology 23: 207-215.

National Turfgrass Research Initiative, 2003. April 2003.

http://www.ntep.org/pdf/turfinitiative.pdf

Parsons, P. P. 2001. Mammalian toxicokinetics and toxicology of chlorothalonil. Pages 1743-

1757 in Handbook of Pesticide Toxicology. Krieger, R., ed. Academic Press, San

Diego, CA.

Potter, T. L., Wauchope, R. D., Culbreath, A. K. 2001. Accumulation and decay of

chlorothalonil and selected metabolites in surface soil and following foliar application to

peanuts. Environ. Sci. Technol. 35: 2634-2639.


10

Priest, M. W., Williams, D. J., Bridgman, H. A. 2000. Emissions from in-use lawn-mowers in

Australia. Atmospheric Environment 34: 657-664.

Raman, P. 2005. Chlorothalonil. Pages 574-577 in: Encyclopedia of Toxicology. Wexler, P.,

ed. Elsevier Academic Press, San Diego, CA.

Schwack, W., Bourgeois, B., Walker, F. 1995. Fungicides and photochemistry:

photodegradation of the dicarboximide fungicide iprodione. Chemosphere 31: 2993-

3000.

Sigler, W. V., Taylor C. P., Throssell, C. S., Bischoff, M., Turco, R. F. (2000).

Environmental fates of fungicides in the turfgrass environment. Pages 127-149 in: Fate

and Management of Turfgrass Chemicals. Clark, J. M and Kenna, M., eds. American

Chemical Society, Washington D. C.

Sigler, W. V., Reicher, Z., Throssell, C., Bischoff, M., Turco, R. F. 2002. Sorption and

degradation of selected fungicides in the turfgrass canopy. Water, Air, and Soil Pollution

142: 311-326.

Singh, B. K., Walker, A., Wright, D. 2002. Degradation of chlorpyrifos, fenamiphos, and

chlorothalonil alone and in combination and their effects on soil microbial activity. Env.

Tox. Chem. 21: 2600-2605.

Smiley, R. W., Dernoeden, P. H., Clarke, B. B. 2005. Compendium of Turfgrass

Diseases, 3rd

ed. APS Press, St. Paul, MN.

Suzuki, T., Nojiri, H., Isono, H., Ochi, T. 2004. Oxidative damages in isolated rat hepatocytes

treated with the organochlorine fungicides captan, dichlofluanid, and chlorothalonil.

Toxicology 204: 97-107.

11

Tomlin, C. D. 2009. The Pesticide Manual, 15th

ed. Chlorothalonil. British Crop Production

Council, Hampshire, UK. p. 197-199.


ed. Iprodione. British Crop Production


United States Environmental Protection Agency. 1998. Reregistration Eligibility Decision Fact

sheet: Iprodione. EPA-738-F-98-017.


sheet: Chlorothalonil. EPA-738-F-99-008.

Vargas, J. M. 1994. Management of Turfgrass Diseases. Lewis Publishers, Boca Raton, FL. p

23-27.

Vincelli, P., Dixon, E. 2003. Summer fungicide spray programs for creeping bentgrass greens.

Golf Course Management 71: 87-90.

Walker, A. 1987. Further observation on the enhanced degradation of iprodione and vinclozolin

in soil. Pesticide Sci. 21: 219-231.

Walsh, B., Ikeda, S. S., and Boland, G. J. 1999. Biology and management of dollar spot

(Sclerotinia homoeocarpa); an important disease of turfgrass. HortScience 34: 13-21.

Wang, Y. S., Wen, C. H., Chiu, T. C., Yen, J. H. 2004. Effect of fungicide iprodione on soil

bacterial community. Ecotox. Env. Safety 59: 127-132.

Wilkinson, C. F., Killeen, J. C. 1996. A mechanistic interpretation of the oncogenicity of

chlorothalonil in rodents and an assessment of human relevance. Regulatory Tox. Pharm.

24: 69-84.

12

Wisconsin Turfgrass Industry Survey, 1999. Conducted by: Wisconsin Agricultural Statistics

Service, USDA. Coordinated by: University of Wisconsin – Madison and University of

Wisconsin – Extension.

Zadra, C., Cardinali, G., Corte, L., Fatichenti, F., Marucchini, C. 2006. Biodegradation of the

fungicide iprodione by Zygosaccharomyces rouxli strain DBVPG 6399. J. Agric. Food

Chem. 54: 4734-4739.

13

CHAPTER 1:

Modification of commercially-available ELISA kits to determine chlorothalonil and iprodione

concentrations on golf course turfgrass.

14

ABSTRACT

Repeated fungicide applications are often required for successful management of diseases

on golf course turfgrass. Modification of existing commercially-available enzyme-linked

immunosorbent assays (ELISA) for analyzing fungicide concentration on turfgrass would allow

for more direct research of fungicide fate under varying environmental conditions. The objective

of this research was to modify Horiba SmartAssay® ELISA kits for iprodione and chlorothalonil

to increase their efficiency and practicality for use in analyzing large numbers of turfgrass

samples. Both fungicides were applied to creeping bentgrass (Agrostis stolonifera L.) turf. The

ELISA results were compared to fungicide concentrations obtained using gas

chromatography/electron capture detection (GC/ECD). Iprodione concentrations from turfgrass

1 h following application using ELISA averaged 321 mg L-1

, whereas GC/ECD averaged 151 mg

L-1

. Chlorothalonil concentrations from turfgrass 1 h following application using ELISA

averaged 911 mg l-1

, compared to average concentrations of 467 mg l-1

using GC/ECD.

Modification of Horiba’s SmartAssay® ELISA kits for both chlorothalonil and iprodione

analysis on turfgrass yielded accurate, precise results at a fraction of the cost, time, and skillset

of using gas chromatographic methods. The modified ELISA protocol could be used to gain a

further understanding of fungicide fate in turfgrass systems under varying environmental

conditions, potentially improving the efficiency of fungicide applications.

15

1. INTRODUCTION

Highly maintained turfgrass has become an important aspect of the urban and suburban

landscape around the world. In the United States alone, 50 million acres of land is planted with

turfgrass (National Turf Research Initiative, 2003). The most intensively managed turfgrass is

found on golf courses, where mowing heights can be as low as 2.5 mm on putting surfaces and

daily irrigation is often required. Under these intense management conditions, numerous fungal

diseases may cause significant damage under a variety of environmental conditions (Smiley et

al., 2005). Management of turfgrass diseases is accomplished primarily through repeated

preventative fungicide applications, which can have adverse environmental and toxicological

effects (Baird et al., 2000; Baris et al., 2010). Routine fungicide applications also administer a

substantial financial burden, with season-long protection of golf course putting greens costing

between $7,000 and $10,000 (Vincelli and Dixon, 2003).

Chlorothalonil (tetrachloroisophtalonitrile) and iprodione (3-(3,5-dichlorophenyl)-N-

isopropyl-2,4-dioxoimidazolidine-1-carboximide) are commonly used to manage a number of

fungal diseases on turfgrasses. Chlorothalonil is the most commonly applied conventional

pesticide in the world (EPA, 2011). It is a contact fungicide first registered in the United States

in 1966, and is labeled for use on turfgrass and many other horticultural and agronomic crops

(US EPA, 1999). Chlorothalonil has a multisite mode of action and is effective against a wide

range of foliar fungal pathogens including Alternaria, Sclerotinia, and Colletotrichum species.

In turfgrass, chlorothalonil is frequently used to manage dollar spot caused by the fungus

Sclerotinia homoeocarpa, which requires more fungicide applications to manage than any other

turfgrass disease in temperate conditions (Latin, 2011; Vargas, 1994).

16

Iprodione is a commonly-applied foliar fungicide in the turfgrass market and was first

registered in the United States in 1979 (US EPA, 1998). It belongs to the dicarboximide class of

fungicides along with other active ingredients vinclozolin and procymidone. In addition to

turfgrass, iprodione is also used on almonds, berries, grapes, lettuce, ornamentals, peaches,

peanuts, potatoes, and rice (US EPA, 1998). Iprodione is highly effective against fungal

pathogens from the genera Alternaria, Sclerotinia, Botrytis, and Rhizoctonia (Mukherjee et al.,

2003). In turfgrass, iprodione is most commonly used to control dollar spot, leaf spot diseases

caused by Drechslera and Bipolaris fungi, as well as Microdochium patch (pink snow mold)

caused by the fungus Microdochium nivale (Latin, 2011).

Season-long control of turfgrass diseases often requires repeated fungicide applications.

Reapplication of fungicides in turfgrass and other horticultural crops is based on intervals

recommended on the manufacturer label. These recommended intervals remain constant

throughout the year, and may not fully account for variable environmental conditions.

Temperature and moisture may affect the rate of fungicide degradation and hence the duration of

fungicide protection provided (Bruhn and Fry, 1982; Frederick et al., 1996). More precise

knowledge on the persistence of fungicides such as iprodione and chlorothalonil on a turfgrass

leaf blade under variable environmental conditions may lead to a more targeted, need-based

application strategy.

Enzyme-linked immunosorbent assays (ELISA) have become a common method for

measuring pesticide concentration in various matrices including water, soil, and plant products

such as fruits, grains, and vegetables (Van Emon, 2001). Horiba, Ltd produces commercially-

available SmartAssay® ELISA assays for a number of pesticides, including iprodione and

chlorothalonil (Watanabe et al., 2006; Watanabe and Miyake, 2007). These kits were developed

17

to measure fungicide concentration in fresh market produce, and are sensitive enough to measure

minute quantities of fungicide. However, three primary difficulties led to the need for alteration

of the Horiba method for turfgrass with the goal of increasing the practicality and efficiency of

the assays. First, the assays were initially intended to measure fungicide concentrations in the

range of 0.15 g L-1

to 30 g L-1

, which is much lower than would be expected on a leaf blade

following a recent pesticide application. Second, 5 g of plant material was required for

homogenization, which is impractical considering the size of leaf blades on golf course fairways

and putting greens. Third, the protocol calls for shaking each sample for 30 min and filtering

slowly through filter paper, which is not conducive for analyzing numerous of samples

simultaneously.

The primary objectives of our research were to (1) modify an existing, commercially-

available ELISA kit to accurately measure iprodione and chlorothalonil concentration of

turfgrass leaves, and (2) compare sensitivity and cost efficiency of the ELISA method with gas

chromatography/election capture detection (GC/ECD). Successful modification would allow for

the efficient and accurate analysis of iprodione and chlorothalonil residues on turfgrass plants.

These kits could then be utilized to determine the persistence of both iprodione and

chlorothalonil under a variety of environmental conditions, which could ultimately allow turf

managers to apply fungicides based on need rather than a standard recommended interval.

2. MATERIALS AND METHODS

2.1 ELISA method modification

Iprodione SmartAssay and Chlorothalonil SmartAssay ELISA kits were purchased

from Horiba, Ltd (Kyoto, Japan). Each kit included a 96-well plate coated with monoclonal anti-

18

iprodione or anti-chlorothalonil antibodies, lyophilized iprodione or chlorothalonil labeled with

horseradish peroxidase (HRP), lyophilized standard concentrations of each fungicide at both a

high and low concentration, tetramethylbenzidene to act as a chromogenic reagent, sulfuric acid

to act as a stop reagent, and concentrated phosphate buffered saline with tween (PBST) to use as

a washing agent. Without alteration the Iprodione SmartAssay can measure iprodione in water

ranging in concentration from 1.5 g L-1

to 30 g L-1

, and in fruits, vegetables, and grains

ranging in concentration from 0.075 mg L-1

to 1.5 mg L-1

. The Chlorothalonil SmartAssay

effectively measures chlorothalonil in water ranging in concentration from 0.15 g L-1

to 1.5 g

L-1

, and in produce ranging in concentration from 0.0075 mg L-1

to 0.075 mg L-1

. Measuring

chlorothalonil or iprodione concentrations above the upper detection limit of each kit requires

dilution of sample solutions until the range of measurement fits within the upper and lower limit

of the kit.

The original Horiba procedure for chlorothalonil can be found in Watanabe et al., (2006)

and the nearly identical procedure for iprodione can be found in Watanabe and Miyake (2007).

Briefly, 5 g of plant material was homogenized and placed into a centrifuge tube with 25 ml of

100% methanol. For the chlorothalonil assay, 10% phosphoric acid was then added at 10% w/w

to each tube to prevent alkaline hydrolysis of the chlorothalonil molecule. The tube was then

agitated for 30 min, after which the extract was filtered through filter paper into a glass test tube.

Following filtration, 1.5 ml of extract was diluted with 7.5 ml of sterilized deionized (DI) water

and 150 l of diluted extract is combined with 150 l of enzyme-labeled fungicide solution.

Following combination of the extract and enzyme-labeled fungicide molecule, 100 l of the

mixture was placed into an antibody-coated well, sealed, and allowed to react for 1 h at 22C.

19

Following the 1 h reaction time, each well was washed three times with 100 l of PBST buffer to

remove unbound antigen, followed by addition of 100 l well-1

of tetramethylbenzidene. After

10 min of chromogenic reaction, 100 l of a 5% sulfuric acid stop solution was added.

Absorbance was then measured at 450 nm (Labsystems Original Multiskan Plus Labsystems,

Helsinki, Finland). Absorbance readings were converted to fungicide concentration using a

regression equation formed using data from the two standard fungicide concentrations provided

by Horiba. The standard concentrations for iprodione were 1.5 µg L-1

and 30 µg L-1

, and for

chlorothalonil were 0.15 µg L-1

and 1.5 µg L-1

.

Our alterations focused on increasing the upper limit of detection to match our expected

values and increasing the efficiency and practicality of the assay for use on turfgrass. First, 0.2 g

of turfgrass leaf tissue was placed in a 2-ml microcentrifuge tube (MP Biomedicals, Solon, OH)

containing approximately 200 1.4-mm diameter ceramic spheres designed to pulverize leaf tissue

(Lysing matrix D). One ml of 100% methanol was added to each tube, and 20 µl of 50%

phosphoric acid was added to the tubes containing chlorothalonil extract. Tubes were then

placed in an MP Biomedical FastPrep-24 Tissue Homogenizer for 40 s at a speed of 6.0 m s-1

.

Following homogenization, each tube was centrifuged (Eppendorf, Hamburg, Germany) for 2-

min at a relative centrifugal force of 2348 x g to sediment the plant solids, then 200-l of

supernatant was removed and placed in 1.5 ml of purified deionized water. The Environmental

Protection Agency’s (EPA) Kenaga nomogram method was used to determine the expected

concentrations of iprodione and chlorothalonil on turfgrass leaf tissue (Hoerger and Kenaga,

1972). The initial iprodione concentration was expected to be 234 mg kg-1

and initial

chlorothalonil concentration was expected to be 954 mg kg-1

when applied at the full label rate

(Fletcher et al., 1994). The remainder of the assay was performed according to the procedures

20

provided by Horiba. Preliminary analysis using GC/ECD indicated treated turfgrass samples had

iprodione concentrations in the range of 150-250 mg L-1

and chlorothalonil concentrations in the

range of 500-600 mg L-1

. In order to measure in this range using the Horiba SmartAssay kit,

further dilution of the extract in 10% methanol was needed to increase the upper limit of

detection. For iprodione, each sample was diluted 200-fold following placement in 1.5 ml of

water to provide a new sensitivity range of 15 to 300 mg L-1

. For chlorothalonil, each sample

was diluted an additional 10,000-fold following placement in 1.5 ml of water in order to detect

concentrations between 75 and 750 mg L-1

.

2.2 Field Sampling and Validation with Gas Chromatography/Electron Capture Detection

To determine the accuracy of the modified ELISA method, turfgrass treated separately

with iprodione, chlorothalonil, and water were sampled on four different occasions and analyzed

using both the modified ELISA method and GC/ECD. The four sampling dates were 19 Nov

2009, 19 May 2010, 2 Feb 2012, and 22 Feb 2012. Prior to each sampling, chlorothalonil was

applied as Daconil WeatherStik® (Syngenta Crop Protection, Greensboro, NC) at the rate of

12.6 kg active ingredient (a.i.) ha-1

and iprodione was applied as Chipco 26GT® (Bayer Crop

Science, Kansas City, MO) at the rate of 3.1 kg a.i. ha-1

. Both fungicides were applied in a water

volume of 814 L water ha-1

. Fungicides were applied at a nozzle pressure of 276 kPa using a

CO2- pressurized boom sprayer equipped with two XR Teejet 8004 flat fan VS nozzles (Teejet

Technologies, Wheaton, IL). Each fungicide was applied to creeping bentgrass (Agrostis

stolonifera ‘Penncross’) maintained at a height of 1.25-cm at the OJ Noer Turfgrass Research

Facility in Verona, WI. The most recent pesticide application to the experimental area was more

than 6 months prior to the first sampling date, and all 4 samplings were conducted on different

21

sections of the same experimental area. Approximately 1-h following the fungicide application,

six 10-cm diameter cores were sampled 1-m apart within each fungicide-treated area and six

cores were sampled from non-treated turfgrass. The cores were sampled using a golf hole cutter

to a depth of approximately 10-cm. Following sampling, the cores were transported for 20-min

to the laboratory in sealed plastic containers. Once in the lab, two 0.2-g aliquots of leaf blades

were clipped using scissors and homogenized as described in section 2.1. Following

centrifugation, supernatant from each tube was collected and analyzed using the modified ELISA

method or GC/ECD.

Samples analyzed by GC/ECD were promptly delivered to the Wisconsin Department of

Agriculture, Trade, and Consumer Protection (WDATCP) Bureau of Laboratory Services in

Madison, WI, which was approximately 10-min from the site of sample preparation. In addition,

WDATCP analyzed the concentration of each fungicide mixed with water prior to spraying and

the concentration collected from the nozzles during application. These additional analyses

provided baseline concentrations of each fungicide during solution preparation and application.

Mean absorbance, fungicide concentration, and standard error were collected for each method at

each sampling date.

3. RESULTS

3.1 Iprodione concentration

Using the modified SmartAssay® protocol, iprodione concentrations on or within

turfgrass leaves 1-h following the fungicide application ranged from 299.6 mg L-1

to 364.3 mg L-

1 (Table 1). This is approximately twice the concentration detected using GC/ECD, which

ranged from 140.3 mg L-1

to 157.0 mg L-1

. The expected iprodione concentration when applied

22

to turfgrass at 3.1 kg a.i. ha-1

using the EPA Kenaga nomogram method was 234 mg kg-1

. The

standard error calculated within each sampling date was lower in the ELISA method when

compared to the GC/ECD method.

The SmartAssay® ELISA kits from Horiba employ a direct competitive reaction to

obtain quantitative fungicide analysis results. In this reaction, lower absorbance readings are

converted to higher fungicide concentration using the regression of a high (30 µg L-1

) and low

(1.5 µg L-1

) iprodione concentration provided by Horiba (Table 2). The lowest average

absorbance reading (0.082) during the first sampling resulted in the highest average fungicide

concentration (364.3 mg L-1

). The standard error was low within each sampling and never

exceeded 0.026. A difference in absorbance of 0.025 led to a 10 mg L-1

difference between

sampling 2 and 3, showing that relatively minor differences in absorbance results in sizable

differences in fungicide concentration. The absorbance readings from the non-treated samples

were much higher than the treated samples, and only the first sampling had an average value

below 1.0.

3.2 Chlorothalonil concentration

Chlorothalonil concentrations on turfgrass leaves using the modified SmartAssay®

protocol ranged from 827.9 mg L-1

to 1023 mg L-1

(Table 3). Chlorothalonil values analyzed

using GC/ECD ranged from 333.0 mg L-1

to 581.7 mg L-1

. Similar to iprodione analysis, the

chlorothalonil concentrations analyzed using ELISA were nearly twice that determined using

GC/ECD. The chlorothalonil values obtained using the ELISA method were much closer to the

Kenaga nomogram expected initial concentration of 954 mg kg-1

then those obtained using

GC/ECD. The standard error within each sampling date was consistent between the

23

chlorothalonil ELISA and GC/ECD analysis methods, but were two to three times higher than

standard errors calculated for the iprodione assays (Table 3).

The detection limit of chlorothalonil using the GC/ECD method was 60 mg L-1

, and

chlorothalonil was not detected in any of the non-treated samples analyzed via GC/ECD (Table

3). Chlorothalonil was detected on non-treated samples using the ELISA method, however

measurements between samplings and within each sampling varied widely. Within each non-

treated sampling, the standard error calculated was nearly 50% or more of the mean.

Chlorothalonil absorbance values were relatively consistent among treated samples both

within and among sampling dates. Absorbance values from non-treated samples were

significantly higher than treated samples as expected, but values were lower than those measured

with the iprodione SmartAssay® kits. Absorbance values of non-treated samples from the

chlorothalonil SmartAssay® ranged in concentration from 0.670 – 0.841, while those from the

iprodione SmartAssay® ranged in concentration from 0.993 – 1.36. The range in absorbance

values provided by the chlorothalonil standard concentrations was smaller relative to the

iprodione assay, leading to large differences in calculated chlorothalonil concentration from

relatively minor differences in absorbance (Table 4). The difference in mean absorbance

between sampling 1 and 2 was just 0.007 but the difference in mean chlorothalonil concentration

between the two samplings was nearly 130 mg L-1

.

4. DISCUSSION

Three major modifications to the Horiba SmartAssay® protocols were used to increase

potential efficiency and practicality for measuring fungicide residues on golf course turfgrass.

The first modification was to lower the amount of leaf tissue used in the assay from 5-g per

24

sample to a more practical 0.2-g. The second modification was to pulverize and centrifuge the

samples rather than to shake and filter them, which reduced sample preparation time from 30-

min per sample to 10-min for 24 samples and allowed us to quantify fungicide concentration on

and within turfgrass leaves. The third modification was to dilute the extract significantly (10,000

fold for iprodione; 510,000 fold for chlorothalonil) in order to detect high concentrations of each

fungicide. This was necessary because the kits were initially designed to analyze pesticide

concentrations in fresh market produce, while our use of the kits was to measure fungicide

concentrations shortly after application to turfgrass.

The modified ELISA method for both iprodione and chlorothalonil was effective at

detecting both fungicides in an efficient, repeatable manner without the use of specialized

equipment of training. None of the modifications appeared to have a detrimental effect on

fungicide analysis. Chlorothalonil is a contact fungicide that binds tightly to leaf material and is

rather insoluble in methanol with a methanol solubility of 1.7 mg L-1

(Tomlin, 2009). A simple

methanol wash, such as the original Horiba protocol recommends, would likely not dislodge all

the chlorothalonil residues from the outer leaf matrix. Iprodione is a penetrant fungicide that is

absorbed into the leaf apoplast, and a methanol wash would not extract iprodione from within the

leaf (Tomlin 2009). Pulverization and centrifugation of each sample in the modified method

allowed for a more complete detection of fungicide residues from leaf tissue. Steinke and Stier

(2004) previously demonstrated that pulverization of turfgrass leaf blades enhanced the

sensitivity of enzyme-mediated non-structural carbohydrate assays in turfgrass.

The concentration of each fungicide detected using the ELISA method was nearly double

that detected using GC/ECD. Several factors may have contributed to this discrepancy,

including potential loss from degradation during transport, photolysis, and volatilization. In

25

addition, thermal degradation or other loss of fungicide during GC-ECD analysis may have

affected the results. Concentrations obtained of both iprodione and chlorothalonil using

GC/ECD were significantly below the expected initial values calculated using the Kenaga

nomogram. The Kenaga nomogram was produced by the US EPA in the 1970’s as a simple

means for predicting pesticide residues immediately following application on six different plant

categories (Fletcher et al., 1994; Hoerger and Kenaga, 1972). Chlorothalonil residues detected

using GC/ECD were on average half the expected amount of 954 mg L-1

, while the modified

ELISA method provided values 95.5% of the expected value. Iprodione residues detected using

GC/ECD were on average 64.4% of the expected value of 234 mg L-1

, while the modified ELISA

method provided values 137% of the expected values. The additional time and preparation used

to analyze the samples with GC/ECD may allow for potential fungicide breakdown due to pH,

metabolism, or other means (Van Emon, 2001; Watanabe et al., 2006; Watanabe and Miyake,

2007; Wu et al., 2002). Both fungicides can rapidly degrade to their primary metabolites in

alkaline pH, which may have hindered detection of the parent compound (Roberts and Hutson,

1999). The half-life of iprodione at a pH of 7 is 4.7-d, while at a pH of 9 it is 27-min (US EPA

1999). Using the ELISA assays each sample was analyzed within 30-min, which likely limited

breakdown of the fungicide molecules.

Despite effective detection of chlorothalonil and iprodione from treated turfgrass, the

number of false positive results using the modified chlorothalonil SmartAssay® kit was

concerning. The competitive reaction that exists between natural chlorothalonil molecules and

enzyme-labeled chlorothalonil molecules allows for a quantitative analysis of chlorothalonil

residues. One drawback of the competitive reaction, though, is that low absorbance as a result of

low signal activity will be converted to a high chlorothalonil concentration even if chlorothalonil

26

is not present in the sample. The degree of error in chlorothalonil quantitation was also impacted

by low reactivity, likely due to the narrow absorbance window observed with the chlorothalonil

standard concentrations provided by Horiba. Low signal activity is a relatively common problem

in ELISA assays and can be caused by a number of factors. Factors include insufficient washing

of unbound reagent, deterioration of enzyme-labeled reagent, defective signal generation reagent,

inactive or defective antibodies, contamination, and improper incubation temperature (Wild,

2005). In addition, cross-contamination with fungicide metabolites, plant solutes, or

chlorothalonil in the field or in the lab cannot be ruled out due to the sensitive nature of the

chlorothalonil SmartAssay® kit. Despite numerous alterations to the chlorothalonil assay

protocol, false positive results were present in non-treated samples in nearly every sampling date.

False positives still made up the minority of non-treated turfgrass samples within each sampling,

and continued modification of the assay conditions may reduce the number of false positives

further. False positives were not commonly observed with the iprodione assay, so the issue

appears to lie solely with the chlorothalonil SmartAssay® kit or method.

Other research analyzing chlorothalonil and iprodione in plant material has resulted in

variable results based on the plant species, rate of application, and measurement method. One

day following the application of chlorothalonil at 24.5 kg ha-1

to 5 mm tall golf course turfgrass,

Wu et al. (2002) observed concentrations of 230 mg kg-1

using GC/ECD. This is much lower

than our analysis, which averaged approximately 911.2 mg kg-1

following conversion of 1-L of

water to a weight of 1-kg (weight of methanol was not included). Analysis of peanut (Arachis

hypogaea L.) leaf surfaces using GC/MS several hours after the application of chlorothalonil at

1.26 kg ha-1

resulted in a concentration of 5.8 µg cm-2

(Elliott and Spurr, 1993). Lukens and Ou

(1976) analyzed tomato (Lycopersicon esculentum Mill.) leaf surfaces for chlorothalonil 1-h

27

following application at 1.58 kg ha-1

using GC/MS and found concentrations ranging from 7.0 to

20.0 µg cm-2

depending on leaf canopy position. These researchers analyzed chlorothalonil on

the leaf surface by collecting leaf discs and determining chlorothalonil on a per area basis,

making it difficult to directly convert our results in mg L-1

to µg cm-2

for comparison. If it is

assumed that 1-L of fungicide solution covers 12.26 m2 of turf area, then a rough estimate of 7.4

g chlorothalonil cm-2

can be made using our results. This is lower than the previous results when

rate of chlorothalonil application is taken into account, but this conversion underestimates the

chlorothalonil concentration per area by failing to take into account any fungicide loss from the

initial spray application.

Iprodione applied at 1.12 kg ha-1

and analyzed using GC/MS 14-d following application

to lettuce (Lactuca sativa L.) ranged in concentration from 3.0 to 26.0 mg kg-1

(Cheng, 1991).

Using GC/ECD, Mukherjee et al. (2003) analyzed mustard (Brassica juncea (L.) Czern.) leaves

for iprodione applied at 0.5 kg ha-1

and observed concentrations of 16.0 mg kg-1

1-h following

application. Results obtained from both these studies were lower than the values obtained using

our modified ELISA method even after the differences in iprodione application rate were taken

into account. Cheng (1991) analyzed iprodione 14-d following application, likely accounting for

the difference observed. It remains unclear why the residues detected by Mukherjee et al. (2003)

were lower than those obtained in our study.

Iprodione and chlorothalonil concentration in a spray tank prior to application was

analyzed using GC/ECD to provide a comparison to the residues observed on plant material.

Iprodione concentration in the initial fungicide-water mixture was 3635 mg L-1

, which compares

favorably to the expected concentration of 3754 mg L-1

. Chlorothalonil concentration in the

initial fungicide-water mixture was 7330 mg L-1

, though, which was less than half of the 15,487

28

mg L-1

expected. Expected concentrations were determined by calculating the amount of active

ingredient present in each fungicide that would be added to 1-L of water to give the

aforementioned rate of application. The ability of the GC/ECD method to detect only 50% of the

expected chlorothalonil in the spray solution may suggest that it is ineffective at accurately

determining chlorothalonil concentration. It may also signal, though, significant chlorothalonil

degradation in the spray solution prior to analysis.

Concentration of iprodione and chlorothalonil collected directly from the spray nozzle

was 3090 mg L-1

and 6590 mg L-1

, respectively. Using the modified ELISA method, average

iprodione concentrations on turfgrass 1-h following the application were 321.8 mg L-1

, and using

the GC/ECD method were 151.1 mg L-1

. For chlorothalonil, the average concentrations 1-h

following application were 911.2 mg L-1

using ELISA and 467.4 mg L-1

using GC/ECD. In the

short time from mixing to collection from the nozzle, 10 and 15% of chlorothalonil and

iprodione, respectively, was either bound to the spraying equipment or degraded. Iprodione

concentration from the nozzles to the turfgrass 1-h after application was reduced by 90% when

measured with the ELISA method and 95% using GC/ECD. For chlorothalonil, concentrations

were reduced 86% using the ELISA method and 87% using GC/ECD. The majority of the

concentration reduction was likely due to the extremely large surface area covered by a fungicide

application in a turfgrass system. Fungicide applications in turfgrass are often made in 814 L of

water ha-1

, and cultivars of creeping bentgrass can have turfgrass shoot densities ranging from 15

to 50 shoots per cm2 (Jordan et al., 2003). An average putting green, then, might have 10

8

turfgrass shoots that require protection. Other factors that may influence the reduction in

fungicide concentration include pesticide volatilization, particle drift, and transformation of the

pesticide molecule by microbial or abiotic means (Sigler et al., 2000).

29

The modified ELISA method presented here using the Horiba SmartAssay® kits for

the fungicides iprodione and chlorothalonil was more time and cost-effective at analyzing

samples than GC/ECD (Table 5). In Watanabe et al. (2006), the authors showed evidence that

ELISA costs were 10 times less than gas chromatography and the measuring time was reduced

by more than a factor of 10. Our analysis showed significant reductions in time and cost were

indeed achieved using ELISA instead of a GC method. However, we also demonstrated the

overall cost and time per sample using the SmartAssay® kits to be significantly higher than that

calculated in previous research (Watanabe et al., 2006). In our cost analysis, the purchase of the

SmartAssay® kits themselves made up approximately 90% of the cost per sample. The

remaining 10% was made up of supply purchases such as methanol and pipette tips. WDATCP

charged a flat fee of $100 per sample for analyzing pesticide samples using GC/ECD. The time

to analyze one sample via ELISA versus 96 samples in a 96-well plate kit is virtually the same,

with the exception of sample preparation, because the competitive reaction in each well must

react for 1 h regardless of the number of samples analyzed. Washing of unbound reagent and the

chromogenic reaction take an additional 30 min. This can vary slightly based on the number of

samples, but the majority of this time is spent during the chromogenic reaction, which does not

fluctuate based on the number of samples.

Modification of the iprodione and chlorothalonil SmartAssay® protocols was undertaken

to increase the efficiency of analyzing fungicide residues on large numbers of turfgrass samples.

Pulverization and centrifugation of the samples simultaneously cut the sample preparation time

from over 30-min per sample to approximately 10-min per 24 samples. The cost per sample

using the modified ELISA method was still significant, due mostly to the purchase of the

SmartAssay® kits, but was still considerably lower than using an outside agency to perform

30

chromatographic analyses. The modified ELISA method detected fungicide concentrations that

were similar to those predicted by the Kenaga nomogram. Therefore, the modified ELISA is an

efficient, accurate method for determining fungicide concentrations on turfgrass plants without

the need for specialized equipment or additional training. Analysis of fungicide residues on

turfgrass leaf blades in various environments could allow for more precise determination of

fungicide persistence, which may lead to more targeted pesticide applications and a reduction in

overall pesticide usage.

LITERATURE CITED

Baird, J. H., Basta, N. T., Huhnke, R. L., Johnson, G. V., Payton, M. E., Storm, D. E.,

Wilson, C. A., Smolen, M. D., Martin, D. L., Cole, J. T. 2000. Best management

practices to reduce pesticide and nutrient runoff from turf. p. 268-293 in: Fate and

Management of Turfgrass Chemicals, J. M. Clark and M. P. Kenna, eds. ASC

Symposium Series 743, American Chemical Society, Washington DC.

Baris, R. D., Cohen, S. Z., Barnes, N. L., Lam, J., Ma, Q. 2010. Quantitative analysis of over 20

years of golf course monitoring studies. Env. Tox. Chem. 29: 1224 – 1236.

Bruhn, J. A., Fry, W. E. 1982. A mathematical model of the spatial and temporal dynamics of

chlorothalonil residues on potato foliage. Phytopathology. 72: 1306-1312.

Cheng, L. 1991. Section 18 Exemption, Iprodione on Cabbage. US Environmental Protection

Agency. DEB # 7751.

Elliott, V. J., Spurr, H. W. 1993. Temporal dynamics of chlorothalonil residues on peanut

foliage and the influence of weather factors and plant growth. Plant Disease 77: 455-460.

31

Fletcher, J. S., Nellessen, J. E., Pfleeger, T. G. 1994. Literature review and evaluation of the of

the EPA food-chain (Kenaga) nomogram, an instrument for estimating pesticide residues

on plants. Env. Tox. Chem. 13: 1383-1391.

Frederick, E. K., Throssell, C. S., Bischoff, M., Turco, R. F. 1996. Fate of vinclozolin in

creeping bentgrass turf under two application frequencies. Bull. Environ. Contam.

Toxicol. 57: 391-397.

Hoerger, F., Kenaga, E. E. 1972. Pesticide residues on plants: Correlation of representative data

as a basis for estimation of their magnitude in the environment. Pages 9-28 in:

Environmental Quality and Safety: Chemistry, Toxicology, and Technology. Coulston,

F. and Korte, F. eds. Georg Thieme Publishers, Stuttgart, West Germany.

Jordan, J. E., White, R. H., Vietor, D. M., Hale, T. C., Thomas, J. C., Engelke, M. C. 2003.

Effect of irrigation frequency on turf quality, shoot density, and root length density of

five bentgrass cultivars. Crop Science 43: 282-287.

Latin, R. 2011. A Practical Guide to Turfgrass Fungicides. APS Press, St. Paul, MN. p 181-

228.

Lukens, R. J., Ou, S. H. 1976. Chlorothalonil residues on field tomatoes and protection against

Alternaria solani. Phytopathology 66: 1018-1022.

Mukherjee, I., Gopal, M., Chatterjee, S. C. 2003. Persistence and effectiveness of iprodione

against Alternaria blight in Mustard. Bull. Environ. Contam. Toxicol. 70: 586-591.

National Turfgrass Research Initiative, 2003. April 2003.


Roberts, T. R., Hutson, D. H. 1999. Chlorothalonil. Pages 1380-1384 in: Metabolic Pathways

of Agrochemicals, Part II. Royal Society of Chemistry, Cambridge.


32

Sigler, W. V., Taylor C. P., Throssell, C. S., Bischoff, M., Turco, R. F. 2000.





Diseases, 3rd


Steinke, K., Stier, J.C. 2004. Influence of trinexapac-ethyl on cold tolerance and nonstructural

carbohydrates of shaded supina bluegrass. Acta Hort. (ISIS) 661:207-215.











United States Environmental Protection Agency, 2011. 2006-2007 Pesticide Market Estimates.

Available: February 17, 2011. http://www.epa.gov/opp00001/pestsales/.


23-27.

Van Emon, J. M. 2001. Immunochemical applications in environmental science. Journal of

AOAC International 84:125-133.

http://www.epa.gov/opp00001/pestsales/

33

Vincelli, P., Dixon, E. 2003. Summer fungicide spray programs for creeping bentgrass greens.

Golf Course Management 71: 87-90.

Watanabe, E., Miyake, S., Ito, S., Baba, K., Eun, H., Ishizaka, M., Endo, S. 2006. Reliable

enzyme immunoassay detection for chlorothalonil: Fundamental evaluation for residue

analysis and validation with gas chromatography. J. Chromatography A 1129: 273-282.

Watanabe, E., Miyake, S. 2007. Immunoassay for iprodione: Key estimation for residue

analysis and method validation with chromatographic technique. Ana Chem Acta 583:

370-376.

Wild, D. 2005. Immunoassay troubleshooting guide. Pages 483-519 in: The Immunoassay

Handbook, 3rd

edition. D. Wild ed. Elsevier Ltd, Oxford, UK.

Wu, L., Liu, G., Yates, M. V., Green, R. L., Pacheco, P., Gan, J., Yates, S. R. 2002.

Environmental fate of metalaxyl and chlorothalonil applied to a bentgrass putting green

under southern California climactic conditions. Pest Manage. Sci. 58: 335-342.

34

Table 1. Iprodione concentration as calculated using a modified Horiba SmartAssay® ELISA method and a gas

chromatography/electron capture detection (GC/ECD) method. ELISA absorbance values at 450 nm were converted to ELISA

fungicide concentrations using the equation of the linear regression of the absorbance of standard iprodione concentrations provided

by Horiba. All turfgrass sampling was completed 1 h following iprodione application on creeping bentgrass (Agrostis stolonifera

‘Penncross’) maintained at a 1.2 cm height.

Iprodione Concentration (mg L

-1)

ELISA Absorbancea ELISA Method

b GC/ECD Method

c

Sampling date (n=6) Treatedd Nontreated Treated

d Nontreated Treated

d Nontreated

19 November 2009 0.082 ± 0.006c

0.993 ± 0.212 364.3 ± 1.71 103.4 ± 56.63 150.3 ± 12.6 < 30.0

19 May 2010 0.158 ± 0.026 1.36 ± 0.033 306.5 ± 8.75 < 15.0 140.3 ± 8.86 < 30.0

2 February 2012 0.183 ± 0.018 1.23 ± 0.056 316.9 ± 3.46 < 15.0 157.0 ± 16.4 < 30.0

22 February 2012 0.256 ± 0.023 1.28 ± 0.018 299.6 ± 7.37 < 15.0 156.8 ± 17.2 < 30.0

aAbsorbance measured at 450 nm.

bEnzyme-linked immunosorbent assay (ELISA) performed using Iprodione SmartAssay® Analysis Kit from Horiba, Ltd.

cn = 6.

cGas chromatography/Electron capture detection (GC/ECD) performed by the Wisconsin Department of Agriculture, Trade, and Consumer Protection.

dSamples treated with iprodione at the rate of 3.1 kg a.i. ha

-1.

35

Table 2. Absorbance values for high and low iprodione standard concentrations using the Iprodione Horiba SmartAssay® analysis kit.

The regression equation produced from the high and low standards was used to convert absorbance values from each sample mg of

iprodione per L.

Iprodione Absorbancea

Sampling Date High Standard (30 µg L-1

) Low Standard (1.5 µg L-1

) Regression equation

19 November 2009 0.291, n = 3 1.212, n = 2 Y = -30.90x + 38.971

19 May 2010 0.183, n = 3 1.004, n = 3 Y = -34.21x + 36.065

2 February 2012 0.235, n = 2 1.092, n = 2 Y = -33.21x + 37.778

22 February 2012 0.256, n = 2 1.145, n = 2 Y = 31.958x + 38.129


36

Table 3. Chlorothalonil concentration as calculated using a modified Horiba SmartAssay® ELISA method and a gas

chromatography/electron capture detection (GC/ECD) method. ELISA absorbance values at 450 nm were converted to ELISA

fungicide concentrations using the equation of the linear regression of the absorbance of standard chlorothalonil concentrations

provided by Horiba. All turfgrass sampling was completed 1 h following chlorothalonil application on creeping bentgrass (Agrostis

stolonifera ‘Penncross’) maintained at a 1.2 cm height.

Chlorothalonil Concentration (mg L-1

)

ELISA Absorbancea ELISA Method

b GC/ECD

Method

c

Sampling date (n = 6) Treatedd Nontreated Treated

d Nontreated Treated

d Nontreated

19 November 2009 0.120 ± 0.014 0.687 ± 0.137 893.3 ± 17.7 282.1 ± 121.1 535.8 ± 30.9 < 60.0

19 May 2010 0.113 ± 0.011 0.837 ± 0.077 1022.6 ± 15.06 125.7 ± 91.34 419.0 ± 7.22 < 60.0

2 February 2012 0.179 ± 0.027 0.841 ± 0.156 827.9 ± 35.40 162.4 ± 162.37 581.7 ± 19.7 <60.0

22 February 2012 0.123 ± 0.017 0.670 ± 0.190 901.1 ± 21.67 332.5 ± 192.16 333.0 ± 50.1 < 60.0


bEnzyme-linked immunosorbent assay (ELISA) performed using Iprodione SmartAssay® Analysis Kit from Horiba, Ltd.

cn = 6.

cGas chromatography/Electron capture detection (GC/ECD) performed by the Wisconsin Department of Agriculture, Trade, and Consumer Protection.

dSamples treated with chlorothalonil at the rate of 12.6 kg a.i. ha

-1.

37

Table 4. Absorbance values of high and low chlorothalonil standard concentrations using the chlorothalonil Horiba SmartAssay®

analysis. The regression equation produced from the high and low standards was used to convert absorbance values for each sample

to mg of chlorothalonil per L.

Chlorothalonil Absorbancea

Sampling Date High Standard (1.5 µg L-1

) Low Standard (0.15 µg L-1

) Regression equation

19 November 2009 0.220, n = 2 0.751, n = 2 Y = -2.539x + 2.058

19 May 2010 0.305, n = 2 0.804, n = 2 Y = -2.684x + 2.307

2 February 2012 0.274, n = 2 0.797, n = 1 Y = -2.571x + 2.083

22 February 2012 0.274, n = 2 0.797, n = 1 Y = -2.571x + 2.083


38

Table 5. Time and cost comparison of ELISA SmartAssay® analysis versus gas chromatographic methods by the University of

Wisconsin and Horiba, Ltd.

Wisconsin Analysis Horiba Analysisa

ELISAb GC/ECD

c ELISA GC/MS

Cost per sample: $11.00 $100.00 $1.10 $12.10

Time per sample: 90 min 2 days 4.5 min 2.4 h aHoriba analysis from Watanabe et al., 2006.

bEnzyme-linked immunosorbent assay performed using Chlorothalonil and Iprodione SmartAssay® Analysis Kits from Horiba, Ltd

cGas chromatography/Electron capture detection performed by the Wisconsin Department of Agriculture, Trade, and Consumer Protection.

39

CHAPTER 2:

Effect of snow cover on the duration of Microdochium patch control provided by

chlorothalonil and iprodione on golf course turfgrass

40

ABSTRACT

Microdochium patch (Microdochium nivale) is the primary low temperature disease of

turfgrass in temperate regions of the world. On intensively-managed golf course turfgrass, one

or two fungicide applications in the fall prior to snowfall are required to suppress disease

development until snowmelt the following spring. Yet during mild winters with limited or no

snow cover, the persistence of fall-applied fungicides throughout the winter remains unclear.

Chlorothalonil and iprodione were applied once prior to snowfall to fairway-height creeping

bentgrass (Agrostis stolonifera L.) in Madison, WI in the winters of 2009-2010, 2010-2011, and

2011-2012. Fungicide treatments were kept under continuous snow cover or kept free of snow

cover the entire winter to determine the effect of snow cover on fungicide persistence and

disease development. Degradation of iprodione and chlorothalonil was not significantly

impacted by the presence or absence of snow cover in all three years of the experiment. Winter

rain events, elevated soil temperature, and melting snow all increased fungicide degradation and

disease development in at least one of the years tested. Increased degradation of both fungicides

at higher soil temperatures indicates that microbial metabolism may play a significant role in

fungicide degradation in a winter environment.

41

1. INTRODUCTION


world is Microdochium patch caused by the fungus Microdochium nivale (Fr.) Samuels & I. C.

Hallett. M. nivale has a relatively wide host range that includes cereals such as wheat, barley,

and oats and is a common pathogen of many turfgrasses (Couch, 1995). The disease is observed

in temperate climates around the world but is most prevalent in the consistently cool, wet regions

of the North American Pacific Northwest, United Kingdom, and northern Europe. In these areas,

Microdochium patch is the most common turfgrass disease (Mann and Newell, 2005).

Symptoms of Microdochium patch vary depending on the environmental conditions. The

disease is most severe under prolonged snow cover, where circular patches of tan or bleached

turf 30 to 60 cm in diameter occur. The perimeter of each patch can develop a pinkish hue in

response to sunlight due to the production of sporodochia. When snow cover is absent and

temperatures range from 10 to 20C, symptoms initially appear as small, reddish or rust-colored

spots less than 5-cm in diameter. Under persistent moisture, symptoms may develop in a linear

fashion due to dispersal of conidia by surface water flow or mechanical traffic. Spots may also

coalesce to form larger patches, but individual foci rarely expand beyond 20 cm in the absence of

snow cover (Smiley et al., 2005).

Although cultural practices can reduce disease severity, fungicides are often required to

maintain suppress Microdochium patch on intensively-managed golf course turfgrass.

Suppression of Microdochium patch during the winter months in the northern United States is

most often achieved with one or two fungicide applications in the fall prior to snowfall. One,

two, or even three different active ingredients are simultaneously applied during each application

in areas that receive heavy snowfall (Hsiang et al., 1999; Koch and Kerns, 2011; Koch and

42

Kerns, 2012). These applications are expected to suppress Microdochium patch and other snow

mold diseases until snowmelt in the spring.

Iprodione (3-(3,5-dichlorophenyl)-N-isopropyl-2,4-dioxoimidazolidine-1-carboximide) is

one of the most effective fungicides used for managing Microdochium patch (Latin, 2011).

Iprodione is a localized penetrant fungicide that was first registered in the United States in 1979

(US EPA, 1998). It belongs to the dicarboximide class of fungicides along with other active

ingredients vinclozolin and procymidone. In addition to turfgrass, iprodione is also commonly

used on almonds, berries, grapes, lettuce, ornamentals, peaches, peanuts, potatoes, and rice (US

EPA, 1998). Its primary biochemical mode of action is the disruption of mitogen-activated

protein histidine kinase, which interferes with mitotic cell division and prevents the germination

of fungal spores and growth of mycelium (Tomlin, 2009).

Iprodione persistence in soil is variable, with half-life estimates ranging from 7 to 171

days (Garcia-Cazorla and Xirau-Vayreda, 1998; Klose et al., 2010; Leistra and Matser, 2004).

Microbial metabolism is the primary mechanism for the breakdown of iprodione in soil.

Pseudomonas spp. and Zygosaccharomyces spp. have been identified as organisms that readily

metabolize iprodione to its primary metabolite; 3, 5 dichloroaniline (Mercadier et al., 1997;

Wang et al., 2004; Zadra et al., 2006). A number of studies suggest that repeated applications of

iprodione may lead to increased degradation rates in the soil, presumably due to the buildup of

organisms that rapidly metabolize the parent compound (Garcia-Cazorla and Xirau-Vayreda,

1998; Mercadier et al., 1997; Klose et al., 2010, Walker 1987). Enhanced iprodione

degradation, however, was not observed on turfgrass leaf blades (Sigler et al., 2002). Iprodione

is prone to photodegradation, which may be the primary means of degradation on turfgrass leaf

blades because of lower microbial populations found on the leaf surface when compared to the

43

soil (Hustert and Moza, 1997; Schwack et al., 1995; Sigler et al., 2002). Iprodione solubility in

water is 13 mg L-1

, making the fungicide moderately water-soluble and prone to washing off the

leaf surface (Haith and Rossi, 2003; Tomlin, 2009).

Chlorothalonil (tetrachloroisophtalonitrile) is another fungicide commonly used to

manage Microdochium patch and is the most widely used conventional pesticide in the world

(Latin, 2011; US EPA, 2011). Chlorothalonil is a broad-spectrum, contact fungicide that was

first registered for use in the United States in 1966 (US EPA, 1999). It is registered for use on

numerous horticultural and agronomic crops and is effective against a wide range of foliar fungal

pathogens including Alternaria, Sclerotinia, and Colletotrichum species. Its biochemical mode

of action is through high-affinity binding to thiols, primarily glutathione. Glutathione

conjugation rapidly depletes levels within the fungal cell and inhibits glutathione-dependent

reactions involved in oxidative stress, glycolysis, and mitochondrial metabolism (Baier-

Anderson and Anderson, 2000; Parsons, 2001; Raman, 2005; Suzuki et al., 2004, Tomlin, 2009).

Chlorothalonil is rapidly metabolized by bacteria in the soil, with soil half life estimates

ranging from 3.5 to 20 days (Potter et al., 2001; Singh et al., 2002). In contrast to iprodione,

some evidence suggests that repeated chlorothalonil applications lead to decreased soil

degradation rates. This may be due to the widely toxic effects of the primary chlorothalonil

metabolite, 4-hydroxychlorothalonil, which is more toxic then the parent compound and may

reduce microbial activity (Singh et al., 2002). Chlorothalonil is insoluble in water (0.81 mg L-1

)

and not considered susceptible to washing off the leaf blade once the product has dried on the

leaf surface (Tomlin, 2009; US EPA 1999). The 4-hydroxy metabolite, however, is more water-

soluble which can lead to ground or surface water contamination and is of toxicological concern

(US EPA, 1999).

44

Six primary physical and chemical processes affect the fate of pesticides in the

environment. They are solubility-based movement in water, sorption and desorption to plant and

soil surfaces, volatilization, plant uptake, biotic degradation through microbial metabolism, and

abiotic degradation through photodegradation or pH activity (Sigler et al., 2000). Fungicides are

not commonly applied in late fall to control winter diseases in other agronomic or horticultural

crops, hence relatively little is known about how the aforementioned processes impact fungicide

persistence in a winter environment. Low winter temperatures may reduce fungicide degradation

caused by temperature-influenced processes such as volatilization, plant uptake, and microbial

metabolism. Conversely, extreme temperature swings, melting snow, and prolonged exposure to

sunlight may promote more rapid fungicide degradation. Further complicating the situation is

how a deep, insulating snow cover impacts fungicide degradation. Mild temperatures across the

northern half of the United States in recent years has resulted in limited snow cover during the

winter months, and future climate change may result in winters with limited snow cover to

become more common. Periods of exposed turfgrass during the winter may lead to increased

rates of fungicide degradation due to photodegradation and is of major concern to turfgrass

managers. How pesticides degrade in the phyllosphere under a range of winter environmental

conditions is poorly understood, yet plays a significant role in winter disease management.

Investigating the effect of snow cover and other winter conditions on the persistence of

chlorothalonil and iprodione on turfgrass leaves will provide insights into an area of research that

has to date received little attention. In addition to contributing to the general understanding of

fungicide persistence in the environment, knowledge of fungicide degradation in a winter

environment may aid turfgrass managers in suppressing Microdochium patch and other winter

turfgrass diseases in a more precise, efficient manner. Specifically, this research would clarify

45

whether fungicide reapplications following periods of limited snow cover are required to

maintain acceptable Microdochium patch suppression.

The primary objectives of this study were to determine the persistence of iprodione and

chlorothalonil on golf course turfgrass under continuous snow cover and in the absence of snow,

and to determine the concentration of each fungicide that adequately suppresses Microdochium

patch in the growth chamber. We hypothesize that exposure to sunlight and other winter

elements in non-snow covered turfgrass will increase the rate of fungicide degradation compared

to snow-covered turf, resulting in the rapid increase of Microdochium patch symptom

development.


2.1 Fungicide application and sample collection

The study was conducted during the winters of 2009-2010, 2010-2011 and 2011-2012 at

the OJ Noer Turfgrass Research Facility in Verona, WI on a stand of creeping bentgrass

(Agrostis stolonifera ‘Penncross’) maintained at a height of 1.25 cm. The field design was a

strip-split plot with four replications. The main plot was the presence or absence of snow and the

sub plots were the fungicide treatments. Snow-covered fungicide treatments were randomized

along the outer edges of the plot and the non-snow fungicide treatments were randomized on the

inside of the plot (Figure 1). The fungicide treatments consisted of a non-treated control,

chlorothalonil, iprodione, and a combined tank mixture of both chlorothalonil and iprodione.

Chlorothalonil was applied as Daconil WeatherStik® (Syngenta Crop Protection, Greensboro,

NC) at the rate of 12.6 kg active ingredient (a.i.) ha-1

and iprodione was applied as Chipco

26GT® (Bayer Crop Science, Kansas City, MO) at the rate of 3.1 kg a.i. ha-1

. All fungicides

46

were applied at a nozzle pressure of 276 kPa using a CO2 pressurized boom sprayer equipped

with two XR TeeJet 8004 VS nozzles (TeeJet, Wheaton, IL). Both fungicides were applied in

814 L water ha-1

. The applications were made one day prior to the first significant snowfall of

each year: 6 Dec 2009; 3 Dec 2010, and 28 Dec 2011. Within 24 h of each snow event, snow

was removed from the non-snow covered plots with a shovel and placed onto the adjacent snow-

covered plots to ensure a minimum snow cover of 10 cm for the duration of the trial.

Approximately one hour following the initial fungicide application, two 10-cm diameter

cores were taken from each plot using a power drill with hole-saw attachment. One core from

each plot was taken to the lab for fungicide analysis using commercially-available enzyme-

linked immunosorbent assay (ELISA) kits, and the second core was taken to the growth chamber

for inoculation with M. nivale. Repeat samplings were conducted every one or two weeks for 87

days following application in 2009-2010, 119 days following application in 2010-2011, and 84

days following application in 2011-2012 depending on the length of snow cover in each year.

Surface temperature, soil temperature at a 5-cm depth, relative humidity, dew point, and solar

radiation between 300 and 1100 nm were collected hourly throughout each winter using sensors

and data loggers from Spectrum Technologies® (Spectrum Technologies, Plainfield, IL).

2.2 Fungicide Analysis

Chlorothalonil and iprodione concentration on and within turfgrass leaves were

determined using chlorothalonil and iprodione SmartAssay ELISA kits purchased from Horiba,

Ltd (Kyoto, Japan). The kits utilize the direct competitive ELISA method and are able to

quantitatively measure fungicide concentration. Each kit contains a 96-well plate coated with

anti-chlorothalonil or anti-iprodione antibodies, lyophilized fungicide labeled with

47

horseradishperoxidase (HRP), lyophilized standard concentrations of each fungicide,

tetramethylbenzidene to act as a chromogenic reagent, 10% sulfuric acid to act as a stop reagent,

and concentrated phosphate buffered saline with tween (PBST) to use as a washing reagent.

The iprodione and chlorothalonil SmartAssay ELISA kits produced by Horiba were

developed for use on fresh market produce (Watanabe et al., 2006; Watanabe and Miyake,

2007). Significant alterations to the Horiba method were made to increase practicality and

efficiency prior to analyzing turfgrass samples (Koch et al., submitted). In brief, 0.2-g of leaf

tissue was clipped from each sample using a scissors and placed in a 2-ml ‘Lysing Matrix D’

microcentrifuge tube containing 200 1.4-mm ceramic spheres (MP Biomedicals, Solon, OH).

One ml of 100% methanol was added to each tube and an additional 20-µl of 50% phosphoric

acid was added to each chlorothalonil tube to prevent alkaline hydrolysis of the chlorothalonil

molecule during the assay. Each tube was pulverized for 40-s at 6.0 m/s using an MP

Biomedical FastPrep-24 Tissue Homogenizer and centrifuged (Eppendorf, Hamburg, Germany)

for 2-min at a relative centrifugal force of 2348 x g. From each tube, 200-l of supernatant was

extracted and placed in a glass test tube with 1.5-ml of autoclaved, deionized water. Each

iprodione sample was then diluted 200 fold in 10% methanol to adjust the range of the diagnostic

kit from 0.075 mg L-1

- 1.5 mg L-1

to 75 mg L-1

- 300 mg L-1

. Each chlorothalonil sample was

diluted an additional 10,000 fold in 10% methanol to adjust the range of the kit from 0.0075 mg

L-1

- 0.075 mg L-1

to 75 mg L-1

– 750 mg L-1

. Equal volume (150 µl) extract and HRP-labeled

fungicide was placed in a glass test tube and mixed vigorously for 5-s. From this test tube 100-

l of the mixture was placed in a single well containing the anti-chlorothalonil or anti-iprodione

antibody and sealed at 22C for 1-h to allow for competitive reaction.

48

Following the competitive reaction, the contents of each well were removed by eight-

channel pipette and discarded. Each well was washed three times using 100-l PBST washing

solution, discarding the unbound antigen between each wash. The wells were then tapped dry on

sterile paper towel and 100-µl of chromogenic reagent was added to each well and allowed to

react with bound HRP-labeled fungicide molecules for 10-min. Following the chromogenic

reaction, 100-l of stop solution was added to halt further reaction. Light absorbance at 450 nm

of each well was analyzed within 15-min of the stop reaction using a microplate reader

(Labsystems Original Multiskan Plus, Helsinki, Finland). The absorbance reading was converted

to a fungicide concentration using the equation of the regression line formed from the standard

fungicide concentrations. Two standard concentrations of iprodione (1.5 µg L-1

and 30 µg L-1

)

and chlorothalonil (0.15 µg L-1

and 1.5 µg L-1

) were provided by Horiba and used to calculate

the regression line for each respective assay.

Fungicide concentration values were subjected to analysis of variance using PROC

MIXED (Version 9.1; SAS Institute, Cary, NC). Random variables were replication, replication

by snow treatment, and replication by snow treatment X fungicide. Lsmeans were calculated for

each sampling date and pair-wise comparisons between snow and non-snow covered treatments

made based on Tukey’s adjusted p-value.

2.3 Bioassay Analysis

Prior to inoculation, the cores were placed in a growth chamber maintained at a day:night

temperature of 12:4°C with 80% fluorescent light and a 10-h photoperiod. Each core was placed

in a plastic container with a damp paper towel and sealed with clear plastic wrap to ensure high

relative humidity (near 100%) while still allowing light penetration. Prior to sealing the

49

containers, each core was inoculated with M. nivale isolates BH7 and BH8, which were isolated

in the fall of 2009 from Blackhawk Country Club in Madison, WI. Inoculum was prepared by

macerating four two week old cultures of M. nivale (two BH7, two BH8) grown on Difco

(Becton, Dickinson, and Company, Sparks, MD) potato dextrose agar (PDA) in 120-ml

deionized water. Following maceration, 2-ml of mycelial solution was pipetted onto the center

of each core. Disease was assessed weekly for four weeks by measuring the radial spread of

infection with a ruler in two perpendicular directions. The total area affected with disease was

divided by the total area of the core to determine disease severity (%).

Disease severity values were subjected to analysis of variance using PROC MIXED

(Version 9.1; SAS Institute, Cary, NC). Lsmeans were calculated for each sampling date and

pair-wise comparisons between snow and non-snow covered, single active-ingredient and tank-

mixture treatments were made based on Tukey’s adjusted p-value.

2.4 Fungicide solubility in melting snow

A study was implemented in the spring of 2012 at the OJ Noer Turfgrass Research

Facility in Verona, WI to determine the effect of melting snow on fungicide degradation. On 16

Apr and again on 30 Apr, chlorothalonil was applied as Daconil WeatherStik® at the rate of 12.6

kg a.i. ha-1

and iprodione was applied as Chipco 26GT® at the rate of 3.1 kg a.i. ha-1

to creeping

bentgrass turf maintained at a height of 1.25 cm. One hour following application, 40 10-cm

cores were taken from chlorothalonil-treated turf, 40 were taken from iprodione-treated turfgrass,

and 40 were taken from non-treated turf and transported in sealed plastic containers to the

laboratory approximately 20-min away from the field site.

50

Upon arrival at the laboratory, 0.2-g of leaf tissue was immediately clipped from each

core and placed in 30-ml of melted snow in a plastic Petri dish for 0, 1, 6, 24, or 96 hours. The

melted snow was collected in Madison, WI on 14 Feb 2012 and stored at 4°C and had a pH of

7.24. Half of the samples from each fungicide were placed in melted snow that was autoclaved

to eliminate microbial activity, while the other half was placed in melted snow that was not

autoclaved. Each dish was stored in a dark growth chamber set at 2°C until fungicide

concentration was determined. After 0, 1, 6, 24, and 96 h in melted snow, leaf tissue was

removed from the water, blotted dry using sterile paper towels, and stored at -80°C until 1-d after

the 96-h samples were collected. Each sampling date was analyzed simultaneously on either the

chlorothalonil or iprodione SmartAssay® ELISA kit using the method described previously.

Fungicide concentration values were subjected to analysis of variance using PROC

MIXED (Version 9.1; SAS Institute, Cary, NC). Random variables were replication, replication

by autoclave treatment, and replication by autoclave treatment X fungicide treatment. Lsmeans

were calculated at each analysis and pair-wise comparisons between autoclaved and non-

autoclaved treatments made based on Tukey’s adjusted p-value.

2.5 Bacterial quantification

Bacterial populations were quantified twice during the spring of 2012. On 21 Feb and

again on 6 Mar, one 10-cm core was taken from each snow and fungicide treatment within the

fungicide degradation experimental area and transported in sealed plastic containers to the

laboratory 20-min away. At the lab, 0.08-g of leaf tissue from each core was placed into a 2-ml

microcentrifuge tube with 0.5-ml autoclaved, deionized water. Each sample was pulverized

using a handheld power drill with plastic drill bit until the sample was homogenous. Samples

51

were diluted 10,000 fold in sterile water and plated onto nutrient agar in 10-cm Petri plates using

an Autoplate 4000 spiral plater (Advanced Instruments, Boston, MA). Plates were allowed to

dry for 15-min and placed in the dark at 28°C for 48-h.

Following incubation, colony forming units (CFUs) were counted using a template

(Figure 2). Diagonal sections of either A or B were used, and if 30 or more CFUs were observed

in segment 8 on opposite sides of the plate then no further counting was required. If less than 30

CFUs were observed, counting continued into additional segments moving towards the center of

the plate until 30 CFUs were reached. The number of segments affected the volume constant

used to convert the number of CFUs to CFUs g-1

leaf tissue-1

. The volume constant for one

segment was 2.428 µl, for two segments was 5.936 µl, and for the full plate was 50.030 µl.

These were the only volume constants used to quantify bacteria in our analysis. The number of

CFUs was converted into CFUs g-1

tissue-1

through the following equation:

3. RESULTS

3.1 Growth chamber inoculations

Microdochium patch severity values from the growth chamber inoculations in 2009-

2010, 2010-2011, and 2011-2012 were evaluated independently. In 2009-2010 the effects of

iprodione, chlorothalonil, and days after the fungicide application (DAA) significantly impacted

disease severity (Table 1). The presence or absence of snow cover was significant at the 90%

confidence interval level, but not the 95% confidence interval. An interaction did exist between

iprodione and snow cover but not between chlorothalonil and snow cover. Disease severity

# Colonies X 500 µl X 10,000

Volume Constant X 0.08 g

tissue

52

increased rapidly in early January 30 DAA regardless of fungicide treatment or snow cover

(Figure 3). Disease severity for both fungicides increased from baseline levels of 0-10% in the

first 30 DAA to 25-50% disease during the next 10-15 days. Disease severity on treated turf

remained lower than non-treated turf for 90 days following the initial fungicide application.

Disease developed more gradually on plots treated with a tank mixture of iprodione and

chlorothalonil on both snow and non-snow covered plots than on plots treated with either

fungicide alone. Soil temperature under snow-covered plots remained relatively constant

between 0-2°C, but under non-snow covered plots fluctuated greatly and dropped as low as -

10°C in late December (Figure 4).

In 2010-2011 the effects of iprodione, chlorothalonil, and DAA all impacted disease

severity while snow cover did not (Table 2). Disease developed rapidly 60 DAA on both

chlorothalonil and iprodione-treated turfgrass, regardless of snow cover (Figure 5). Disease

severity on treated turf was lower than non-treated turf at each sampling date until the final date

120 DAA. As in 2009-2010, disease development was more gradual on turf treated with the tank

mixture than either fungicide applied alone. Soil temperature under snow cover remained

relatively constant between 0-2°C until snow melt in late March. Without snow cover, soil

temperatures fluctuated between -10°C and 0°C until mid-February. In mid-February, soil

temperatures warmed rapidly and remained constant between 0-5°C for the duration of the

experiment (Figure 6).

Disease severity in 2011-2012 was only recorded through 21 DAA due to an absence of

disease development in samples collected following 21 DAA. Disease severity remained low

throughout the 21 day period on chlorothalonil-treated turfgrass, but increased rapidly 14 DAA

on iprodione-treated turfgrass (Figure 7). Differences in disease severity were not observed

53

between chlorothalonil applied alone or in the tank mixture, but substantial reductions in disease

severity were observed between the tank mixture and iprodione applied alone. Soil temperature

on both snow and non-snow plots remained relatively constant between 0-4°C until late January

when temperatures fell below 0°C regardless of snow cover (Figure 8).


Analysis of chlorothalonil in all three years was inconsistent and the data is not presented

here. Analysis of iprodione concentrations in 2009-2010 was inconsistent and is also not

presented here. Iprodione concentrations in 2010-2011 and 2011-2012 were analyzed separately.

In 2010-2011, DAA and fungicide treatment significantly impacted iprodione concentration

while snow cover did not (Table 4). Iprodione applied with chlorothalonil did not affect

iprodione concentration compared to iprodione applied alone so their results were combined for

analysis. Iprodione concentration in 2010-2011 remained between 250-300 mg L-1

until early

February regardless of snow cover (Figure 9). Iprodione concentration began to decline in early

February. By March iprodione concentration had fallen to 150 mg L-1

and by early April

concentration was beyond the limit of detection. Iprodione was detected from non-treated

samples on 27 Dec, 14 Feb, and 24 Mar.

In 2011-2012, results from 19 Jan, 16 Feb, and 7 Mar were highly variable and not

included in the analysis. Snow significantly impacted iprodione concentration in 2011-2012, as

did fungicide treatment and DAA (Table 5). Differences in iprodione concentration from plots

sprayed with iprodione alone or with the tank mixture were again not observed and their results

were combined for analysis. Initial iprodione concentration in 2011-2012 was approximately

200 mg L-1

regardless of snow cover, which was much lower than previous initial analyses and

54

lower than the approximate 350 mg L-1

measured 7 d later. Iprodione concentration declined 14

DAA to 150 mg L-1

in the snow-covered plots and to 250 mg l-1

in the non-snow covered plots

(Figure 10). Following this rapid early drop, concentration declined gradually for the remainder

of the study regardless of snow cover. Iprodione was detected from non-treated samples on Jan

5 and Feb 1.

3.3 Fungicide solubility

No differences in iprodione concentration were observed between the two runs and the

results were combined for analysis. Fungicide treatment (p-value = 0.0062) and hours after

initiation (p-value = 0.0186) significantly impacted iprodione concentration, but autoclaved

water did not (p-value = 0.9531). At the time of this writing, only one chlorothalonil run had

been completed. Fungicide treatment significantly impacted chlorothalonil concentration (p-

value = 0.0167), but autoclaved water (p-value = 0.8627) and hours after initiation did not (p-

value = 0.6899).

Iprodione concentration declined from an initial concentration of 300 mg L-1

to

approximately 150 mg L-1

within the first 6 h of placement into melted snow (Figure 11).

Following this initial drop, concentration remained near 150 mg L-1

the remainder of the

experiment. Differences in iprodione degradation between autoclaved melted snow and non-

autoclaved melted snow were not observed. Chlorothalonil concentration declined from an

initial concentration of 550 mg L-1

to 300 mg L-1

in non-autoclaved melted snow, but only

declined from 550 mg L-1

to 500 mg L-1

in autoclaved melted snow (Figure 12). Chlorothalonil

persistence was greater in both autoclaved and non-autoclaved melted snow relative to iprodione.

55

3.4 Bacterial quantification

Bacterial populations on and within turfgrass leaves from sampling dates in Feb and Mar

of 2012 were similar and combined for analysis. Bacterial populations from snow-covered turf

were 1 - 2 X 109

colony forming units (CFU) g-1

dry tissue-1

, which was approximately half the 2

-3 X 109 CFU g

-1 dry tissue

-1 observed on non-snow covered plots (Figure 13). Fungicide

treatment did not affect bacterial populations (Figure 13).

4. DISCUSSION

Winter weather conditions in Wisconsin varied considerably in each of the three years of

the study, which profoundly impacted the duration of Microdochium patch suppression and the

rate of iprodione degradation. In 2009-2010, Microdochium patch severity increased rapidly on

both chlorothalonil and iprodione-treated turfgrass 30 DAA. The environmental conditions

varied throughout the winter, but changes in the 5-cm soil temperature correlated precisely with

increases in disease severity. In early January, approximately 30 DAA, soil temperature from

non-snow covered plots rose from -10°C to approximately 0°C. This rapid thaw was likely

caused by a 2.5-cm rainfall on 25 Dec 2009. On snow-covered plots, soil temperature remained

constant near 0°C both before and after the rainfall. Although a 15-cm snowfall occurred just

10-d later, much of the chlorothalonil and iprodione likely degraded or was displaced during the

rainfall and subsequent thaw. Consequently, plants were no longer protected from M. nivale

infection in the growth chamber.

In contrast to 2009-2010, the winter of 2010-2011 had one of the highest snowfall totals

ever recorded in Madison, WI. Snow fell in early December and did not melt until February. In

mid-February, soil temperature in non-snow covered plots increased from -8°C to 0°C in a span

56

of approximately 7-d. No major rain events were recorded during this period, but daily high

temperatures in Madison, WI remained between 2-6°C from 14 Feb to 22 Feb 2010. The impact

of this thaw on disease severity was similar to that observed following rainfall in 2009-2010.

Microdochium patch severity was low with both fungicide treatments, regardless of snow cover,

until mid-February. In mid-February, disease severity in the growth chamber increased

dramatically on both iprodione and chlorothalonil-treated turfgrass regardless of snow cover. In

addition, iprodione concentration remained constant until mid-February before decreasing

rapidly on both snow and non-snow covered plots. The dramatic increase in disease severity and

decrease in iprodione concentration coincided with the winter thaw and suggests that soil

temperature influences fungicide degradation in a winter environment.

The winter of 2011-2012 had below average snowfall and was one of the warmest

winters on record for Madison, WI. The first snowfall did not occur until late December, and

very warm temperatures in early January made it difficult to retain snow on the snow-covered

plots. Soil temperatures in both the presence and absence of snow remained above 0°C until

early January. Soil temperatures on snow-covered plots were similar to those from non-snow

covered plots due to the shallow snow depth throughout the winter. Chlorothalonil suppressed

Microdochium patch in the presence or absence of snow 21 DAA. Conversely, iprodione limited

Microdochium patch development for the first 7 DAA but failed to suppress disease

development after 14 DAA. Coinciding with the rapid increase in disease, iprodione

concentration rapidly declined within the first 14 DAA. Iprodione was more persistent in the

absence of snow than in the presence of snow in 2011-2012.

A potential factor in the rapid drop in iprodione concentration in the presence of snow in

2011-2012 was the impact of melting snow. Warm January temperatures made it difficult to

57

maintain snow cover on plots during the first 14 DAA of the experiment. Thus, snow was

collected from surrounding snow piles to maintain snow cover. After placement onto the snow-

covered plots, snow quickly melted and more snow had to be collected and applied to maintain

cover. The melting snow in the first 14 DAA led to an abundance of water in the turfgrass

canopy. The impact of melting snow on the degradation of each fungicide was investigated

further in the laboratory, and iprodione was affected more than chlorothalonil. Iprodione is more

water soluble than chlorothalonil, making it more susceptible to degradation or displacement

during periods of melting snow or winter rainfall (Tomlin, 2009). Concentration of both

fungicides declined in the first 6-h in water but remained relatively constant for the remainder of

the experiment. This suggests that dislodgable foliar residues are susceptible to displacement or

degradation in water, while the remaining residues persist for a longer period.

Melting snow and winter rainfall likely account for a portion of fungicide degradation in

a winter environment. The rapid decrease in iprodione concentration in 2010-2011 in the

absence of snow, when no rain events occurred, suggest other factors contribute to fungicide

degradation as well. It is well-established that iprodione is rapidly degraded by soil

microorganisms, which can lead to enhanced soil degradation following repeated iprodione

applications (Klose et al., 2010; Mercadier et al., 1997; Wang et al., 2004; Walker, 1987; Zadra

et al., 2006). Chlorothalonil is also metabolized in the soil, although more slowly and without

enhanced degradation following repeated applications (Motonaga et al., 1998; Singh et al., 2002;

US EPA, 1999). Limited research has been conducted exploring the impact of phyllosphere

communities on pesticide degradation. Sigler et al., (2002) concluded that photodegradation and

leaf sorption played a larger role than microbial metabolism in the degradation of iprodione,

triadimefon, and metalaxyl on turfgrass leaf blades in the summer. Frederick et al., (1996), on

58

the other hand, determined microbial metabolism was the primary means of vinclozolin

degradation in a turfgrass leaf blade. Research investigating chlorothalonil persistence on

tomato (Lycopersicon esculentum Mill.) and potato (Solanum tuberosum L.) leaves concluded

that leaf growth and volatilization, respectively, were the primary degradative influences (Bruhn

and Fry, 1982; Lukens and Ou, 1976).

None of those studies, however, investigated the impact of phyllosphere communities on

pesticide degradation in a winter environment. At colder temperatures and under snow cover it

was not apparent whether bacterial communities would be large enough to have an impact. Our

analysis showed that bacterial populations on and within a turfgrass leaf blade were

approximately 109 CFU g

-1 tissue

-1. This is consistent with bacterial quantification from other

research on turfgrass in a summer environment (Sigler et al., 2002), and suggests that the winter

environment does not significantly impact bacterial numbers. Pseudomonas spp. isolated from

alpine soil was metabolically active at 3°C (Meyer et al., 2004), although the ability of the

bacteria in the phyllosphere to metabolize pesticides at temperatures around 0°C is unknown and

warrants further research. Bacterial numbers were twice as large in the absence of snow

compared to the snow-covered plots during the two samplings in February and March,

presumably due to warmer canopy temperatures resulting from exposure to sunlight. The larger

population in the absence of snow, however, did not result in increased degradation of either

fungicide. Moreover, differences in microbial counts were not observed between fungicide

treatments. Bacterial quantification occurred 60 DAA, however, indicating that any population

decrease following the application may have recovered once quantification was performed.

Despite the uncertainty surrounding the precise mechanisms behind fungicide

degradation in a winter environment, it is clear from our work that photodegradation has a minor

59

impact. Fungicide photodegradation in the absence of snow cover was thought by many growers

to be the primary driver of fungicide degradation on turfgrass in the winter months (Koch,

personal communication). Our hypothesis stated that fungicide degradation would increase in

the absence of snow cover due primarily to photodegradation. This was based on presumed low

microbial activity, volatilization, and plant uptake during the winter months. Research done

during the summer months with vinclozolin on turfgrass and chlorothalonil on potato and tomato

leaves supported our conclusion that photodegradation does not significantly impact fungicide

degradation on the leaf surface (Bruhn and Fry, 1982; Lukens and Ou; Frederick et al., 1996).

However, Sigler et al., (2002) did determine that photodegradation did significantly impact

iprodione, triadimefon, and metalaxyl degradation on a turfgrass leaf surface during the summer

months. This suggests that the influence of photodegradation on fungicide persistence during the

summer may be fungicide-dependent. Our study, however, found no impact of photodegradation

on either iprodione or chlorothalonil during the winter.

One of the primary objectives of this research was to determine minimum concentrations

of iprodione and chlorothalonil required to suppress Microdochium patch. In 2010-2011,

iprodione concentration dropped rapidly in February from 250 mg L-1

to less than 100 mg L-1

in

a matter of weeks. Microdochium patch severity increased rapidly during the same time period,

indicating that 100 mg L-1

may be an approximate minimum concentration required for

acceptable suppression. In 2011-2012, iprodione concentration fell rapidly from 350 mg L-1

to

100 mg L-1

in snow-covered plots and 200 mg L-1

in non-snow plots in just 14-d. Disease

severity increased on both snow treatments over this period, indicating that the minimum

iprodione concentration required to suppress Microdochium patch is likely closer to 200 mg L-1

.

Chlorothalonil residues were not obtained in the winter degradation experiment. Further

60

research is warranted with both fungicides to precisely determine the minimum fungicide

concentration level required to suppress Microdochium patch and other common turfgrass

diseases.

Suppression of Microdochium patch in the bioassays was extended when the plots were

sprayed with a tank mixture of both iprodione and chlorothalonil compared to single fungicide

applications. In addition, suppression of Typhula blight (Typhula incarnata) in the field plot

increased 30 to 40% when treated with a tank mixture compared to either fungicide applied alone

(data not shown). Under intense snow mold pressures, multiple active ingredients are required

for acceptable snow mold management (Koch and Kerns, 2011; Koch and Kerns 2012).

Differences in iprodione degradation were not observed when applied alone or in tank mixture

with chlorothalonil, thus increased disease control is not the result of altered or reduced

fungicide degradation. Rather, increased control with multiple active ingredients likely results

from a broader spectrum of suppression of numerous snow mold pathogens present under heavy

disease pressure (Jung et al., 2008). In addition, application of multiple active ingredients may

have a greater impact on the initial inoculum level of Typhula fungi. Increased suppression of

inoculum prior to snowfall would likely reduce the level of disease severity observed under

prolonged snow cover.

Fungicide degradation in a winter environment is complex and impacted by many

variables. Three different winters led to three different impacts on fungicide degradation, each

uniquely influencing disease development. The results obtained here have demonstrated that soil

temperature plays a key role in the degradation of fungicides on the leaf surface, potentially due

to microbial activity. Winter rain events and melting snow also significantly impact the

persistence of iprodione and chlorothalonil, likely through fungicide displacement or hydrolysis.

61

For a turfgrass manager these results suggest that as long as soil temperatures stay below 0°C,

and there are no rain or snow melt events, there is no need to reapply fungicides for acceptable

snow mold suppression. In addition, these results provide crucial information on the overall

behavior of certain fungicides in a winter environment, which is an area of limited research.

Additional research is warranted on the impact of winter conditions on other commonly-used

fungicide classes such as the demethylation inhibitors (DMIs) and Quinone outside inhibitors

(QoIs). Building on this research will lead to a better understanding of the impacts different

environmental variables have on fungicide persistence, and lead to more precise and efficient

means of managing snow mold diseases on turfgrass.

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chlorothalonil in striped bass (Morone saxatilus) macrophages: the role of cellular

sulfhydryls and oxidative stress. Aq. Tox. 50: 85-96.


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fungicide residues in soils. J. Agric. Food Chem. 46: 2845-2850.

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Haith, D. A., Rossi, F. S. 2003. Risk assessment of pesticide runoff from turf. J. Env. Quality

32: 447-455.

Hsiang, T., Matsumoto, N. Millett, S. M. 1999. Biology and management of Typhula snow

molds of turfgrass. Plant Dis. 83: 788-798.



Jung, G., Chang, S., Chang, T., Koch, P., Abler, S. 2008. Minimum fungicide rates for species-

specific snow mold control: Knowing the optimal fungicide rate for controlling a

particular species of fungus allows superintendents to reduce inputs and expenses. Golf

Course Management 76: 99-102.

Kim, Y. M., Park, K., Joo, G. J., Jeong, E. M., Kim, J. E., Rhee, I. K. 2004. Glutathione-

dependent biotransformation of the fungicide chlorothalonil. J. Agric. Food Chem. 52:

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Koch, P. L., Kerns, J. P. 2011. Preventative fungicide applications for the control of snow mold

on creeping bentgrass, 2009-2010. Plant Disease Management Reports 5: T032.

Koch, P. L., Kerns, J. P. 2012. Preventative fungicide applications for the control of snow mold

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Motonaga, K., Takagi, K., Matumoto, S. 1998. Suppression of chlorothalonil degradation in

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Diego, CA.

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65














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370-376.


66



Chem. 54: 4734-4739.

67

TABLES AND FIGURES

Table 1. Analysis of variance (ANOVA) of Microdochium patch for turfgrass cores sprayed

with iprodione and chlorothalonil and sampled from snow and non-snow covered plots at weekly

or biweekly intervals during the winter of 2009-2010 in Verona, WI.

Source DF DF F-value p-value

Iprodione 1 21 84.39 <0.001

Chlorothalonil 1 21 132.96 <0.001

Iprodione*Chlorothalonil 1 21 16.27 0.001

Snow 1 21 3.68 0.069

Iprodione*Snow 1 21 10.72 0.004

Chlorothalonil*Snow 1 21 0.05 0.820

Iprodione*Chlorothalonil *Snow 1 21 1.64 0.214

Days After Application (DAA) 10 237 79.48 <0.001

Iprodione*DAA 10 237 5.42 <0.001

Chlorothalonil*DAA 10 237 6.72 <0.001

Iprodione*chlorothalonil*DAA 10 237 6.37 <0.001

Snow*DAA 10 237 0.70 0.721

Iprodione*Snow*DAA 10 237 1.13 0.340

Chlorothalonil*Snow*DAA 10 237 0.33 0.971

Iprodione*Chlorothalonil*Snow*DAA 10 237 0.88 0.551

68

Table 2. Analysis of variance (ANOVA) of Microdochium patch for turfgrass cores sprayed

with iprodione and chlorothalonil and sampled from snow and non-snow covered plots at weekly

or biweekly intervals during the winter of 2010-2011 in Verona, WI.


Iprodione 1 21 122.42 <0.001

Chlorothalonil 1 21 409.29 <0.001

Iprodione*Chlorothalonil 1 21 49.25 <0.001

Snow 1 21 2.96 0.100





Iprodione*DAA 12 288 8.68 <0.001

Chlorothalonil*DAA 12 288 39.67 <0.001

Iprodione*chlorothalonil*DAA 12 288 8.33 <0.001

Snow*DAA 12 288 2.15 0.014




69

Table 3. Analysis of variance (ANOVA) of Microdochium patch severity for turfgrass cores

sprayed with iprodione and chlorothalonil and sampled from snow and non-snow covered plots

at weekly or biweekly intervals during the winter of 2011-2012 in Verona, WI.


Iprodione 1 21 3.30 0.084

Chlorothalonil 1 21 0.00 1.00

Iprodione*Chlorothalonil 1 21 0.00 1.00

Snow 1 21 0.00 1.00





Iprodione*DAA 3 72 1.36 0.262

Chlorothalonil*DAA 3 72 0.00 1.00

Iprodione*chlorothalonil*DAA 3 72 0.00 1.00

Snow*DAA 3 72 0.00 1.00




70

Table 4. Analysis of variance (ANOVA) of iprodione concentration from turfgrass cores

sprayed with iprodione and sampled from snow and non-snow covered plots at weekly or

biweekly intervals during the winter of 2010-2011 in Verona, WI.


Snow 1 3 3.31 0.167

Fung 2 12 323.98 <0.001

Fung*Snow 2 12 1.35 0.296

Days after application (DAA) 11 198 19.57 <0.001

Snow*DAA 11 198 1.64 0.0891

Fung*DAA 22 198 8.96 <0.001

Table 5. Analysis of variance (ANOVA) of iprodione concentration from turfgrass cores

sprayed with iprodione and sampled from snow and non-snow covered plots at weekly or

biweekly intervals during the winter of 2011-2012 in Verona, WI.


Snow 1 3 9.83 0.052

Fung 2 12 32.95 <0.001

Fung*Snow 2 12 0.76 0.491

Days after application (DAA) 8 144 30.67 <0.001

Snow*DAA 8 144 2.44 0.017

Fung*DAA 16 144 1.94 0.021

71

FIGURES

Figure 1. Experimental design of the winter fungicide degradation study at the OJ Noer

Turfgrass Research Facility in Verona, WI. Treatments 1-4 are a non-treated control,

chlorothalonil, iprodione, and a tank mixture of both fungicides under snow cover, respectively.

Treatments 5-8 are the same fungicide treatments kept free of snow cover. Fungicide treatments

are randomized within snow treatment in replications 2-4.

4 1 3 2

3 1 2 4

5 6 7 8

5 8 6 7

Rep 3 Rep 4

5 6 7 8

6 7 8 1

1 2 3 4

4 2 1 3

Rep

1

Rep

2

Snow

Covered

Non-snow

covered

72

Figure 2. Template used to count colony forming units (CFUs) on a 10 cm diameter Petri dish.

CFUs were counted from either the diagonal A or B sections, beginning at segment 8. If less

than 30 CFUs were observed in segment 8, then CFUs in segment 9 were counted as well, and so

on until 30 colony forming units were counted.

73

Figure 3. Severity of Microdochium patch as affected by fungicide treatment and days after

application in 2009-2010. Individual points represent average disease severity values taken

every 7 d up to 90 d following fungicide application. Error bars indicate standard errors of the

means. A – Chlorothalonil-treated turfgrass from snow-covered plots; B – Chlorothalonil-treated

turfgrass from non-snow covered plots; C – iprodione-treated turfgrass from snow-covered plots;

D – iprodione-treated turfgrass from non-snow covered plots.

0 20 40 60 80 100

-20

0

20

40

60

80

100

Nontreated

Chlorothalonil

Tank Mixture

0 20 40 60 80 100

Mic

rodochiu

m p

atc

h s

everity

(%

)

-20

0

20

40

60

80

100

Days after fungicide application

0 20 40 60 80 100

-20

0

20

40

60

80

100

Nontreated

Iprodione

Tank Mixture

Days after fungicide application

0 20 40 60 80 100

Mic

rodochiu

m p

atc

h s

everity

(%

)

-20

0

20

40

60

80

100

A

DC

B

74

Figure 4. Soil temperature from snow and non-snow covered plots at the OJ Noer Turfgrass

Research Facility during the winter of 2009-2010. Soil temperature was recorded hourly at a 5

cm depth from Nov 20, 2009 through Mar 18, 2010 using a Spectrum Technologies®

thermometer and Watchdog® data logger.

Date

Nov Dec Jan Feb Mar Apr

Tem

pera

ture

(C

)

-15

-10

-5

0

5

10

15

20

25

Snow

No snow

75



every 7-14 d up to 119 d following fungicide application. Error bars indicate standard errors of

the means. A – Chlorothalonil-treated turfgrass from snow-covered plots; B – Chlorothalonil-

treated turfgrass from non-snow covered plots; C – iprodione-treated turfgrass from snow-

covered plots; D – iprodione-treated turfgrass from non-snow covered plots.

12/1/2

010

1/1/2

011

2/1/2

011

3/1/2

011

4/1/2

011

0

20

40

60

80

100

Nontreated

Chlorothalonil

Tank Mixture

12/1/2010

1/1/2011

2/1/2011

3/1/2011

4/1/2011

Mic

rodochiu

m p

atc

h s

everi

ty (

%)

0

20

40

60

80

100

12/1/2

010

1/1/2

011

2/1/2

011

3/1/2

011

4/1/2

011

Mic

rodochiu

m p

atc

h s

everity

(%

)

0

20

40

60

80

100

12/1/2

010

1/1/2

011

2/1/2

011

3/1/2

011

4/1/2

011

0

20

40

60

80

100

Nontreated

Iprodione

Tank Mixture

A

C D

B

76



cm depth from Nov 30, 2010 through Apr 7, 2011 using a Spectrum Technologies® thermometer

and Watchdog® data logger.

Date

Nov Dec Jan Feb Mar Apr May

Tem

pera

ture

(C

)

-15

-10

-5

0

5

10

15

20

25

Snow

No snow

77



every 7 d up to 21 d following fungicide application. Error bars indicate standard errors of the

means. A – Chlorothalonil-treated turfgrass from snow-covered plots; B – Chlorothalonil-treated

turfgrass from non-snow covered plots; C – iprodione-treated turfgrass from snow-covered plots;

D – iprodione-treated turfgrass from non-snow covered plots.

12/26/2

011

12/30/2

011

1/3/2

012

1/7/2

012

1/11/2

012

1/15/2

012

1/19/2

012

0

20

40

60

80

100

Nontreated

Chlorothalonil

Tank Mixture

12/26/2

011

1/2/2

012

1/9/2

012

1/16/2

012

1/23/2

012

Mic

rodochiu

m p

atc

h s

everi

ty (

%)

0

20

40

60

80

100

12/26/2

011

12/30/2

011

1/3/2

012

1/7/2

012

1/11/2

012

1/15/2

012

1/19/2

012

0

20

40

60

80

100

Nontreated

Iprodione

Tank Mixture

12/26/2

011

12/30/2

011

1/3/2

012

1/7/2

012

1/11/2

012

1/15/2

012

1/19/2

012

Mic

rod

ochiu

m p

atc

h s

eve

rity

(%

)

0

20

40

60

80

100

A

C D

B

78



cm depth from Nov 29, 2011 through Mar 18, 2012 using a Spectrum Technologies®

thermometer and Watchdog® data logger.

Date

Nov Dec Jan Feb Mar Apr

Tem

pera

ture

(C

)

-10

-5

0

5

10

15

Snow

No snow

79

Figure 9. Concentration of iprodione as affected by snow cover and days after application in

2010-2011. Individual points represent average iprodione concentration taken every 7-14 d up to

119 d following fungicide application. Error bars indicate standard errors of the means.

Date

12/1/10 1/1/11 2/1/11 3/1/11 4/1/11

Ipro

dio

ne C

oncentr

ation (

mg l

-1)

0

50

100

150

200

250

300

350

Nontreated

Snow

No Snow

80

Figure 10. Concentration of iprodione as affected by snow cover and days after application in

2011-2012. Individual points represent average iprodione concentration taken every 7-14 d up to

84 d following fungicide application. Error bars indicate standard errors of the means.

Date

12/1/11 1/1/12 2/1/12 3/1/12 4/1/12

Ipro

dio

ne C

oncentr

ation (

mg l

-1)

0

100

200

300

400

500

Nontreated

Snow

No Snow

81

Figure 11. Concentration of iprodione as affected by placement in autoclaved or non-autoclaved

melted snow and hours kept in melted snow in 2011-2012. Individual points represent average

iprodione concentration taken 0, 1, 6, 24, or 96 h following placement in melted snow. Error

bars indicate standard errors of the means.

Hours

0 1 6 24 96

Ipro

dio

ne C

oncentr

ation (

mg l

-1)

0

50

100

150

200

250

300

350

Nontreated

Nonautoclaved

Autoclaved

82

Figure 12. Concentration of chlorothalonil as affected by placement in autoclaved or non-

autoclaved melted snow and hours kept in melted snow in 2011-2012. Individual points

represent average chlorothalonil concentration taken 0, 1, 6, 24, or 96 h following placement in

melted snow. Error bars indicate standard errors of the means.

Hours in water

0 1 6 24 96

Chlo

roth

alo

nil c

oncentr

ation (

mg l

-1)

0

200

400

600

800

1000

Nontreated

Nonautoclaved

Autoclaved

83

Figure 13. Bacterial quantification on turfgrass leaf blades treated with chlorothalonil,

iprodione, or a mixture of both fungicides from snow and non-snow covered plots at the OJ Noer

Turfgrass Research and Educational Facility. Cores were sampled on Feb 21 and Mar 6, 2012.

Error bars indicate standard errors of the means.

Fungicide Treatment

Nontreated Chlorothalonil Iprodione Tank Mixture

Bacte

rial C

FU

g-1

Leaf

Tis

sue

0

1e+9

2e+9

3e+9

4e+9

Snow

No Snow

84

CHAPTER 3:

Influence of temperature on chlorothalonil and iprodione degradation and in vitro fungal

sensitivity.

85

ABSTRACT

Temperature plays a critical role in the activity of plant pathogens, yet the influence of

temperature on fungicide persistence and fungal sensitivity to fungicides remains unclear.

Previous research has demonstrated that fungicide persistence on the leaf blade and fungicide

sensitivity can vary with temperature, which could impact disease management. Degradation of

the fungicides iprodione and chlorothalonil at 10, 20, and 30°C was estimated on turfgrass leaf

blades over 4 to 5 weeks in 2010 and 2011. Concentrations of both fungicides declined

gradually at 10°C but more rapidly at 20 and 30°C. These results suggest temperature does

influence the degradation of fungicides on and within turfgrass leaf blades. In addition, in vitro

sensitivity of Sclerotinia homoeocarpa and Microdochium nivale to iprodione and chlorothalonil

was determined at 5, 10, 15, 20, 25, and 30°C. Both fungi were more tolerant of chlorothalonil

at 15°C relative to other temperatures tested. M. nivale was more tolerant of iprodione at higher

temperatures, while temperature did not impact the in vitro sensitivity of S. homoeocarpa to

iprodione. The results presented here suggest that temperature influences both fungicide

persistence on and within turfgrass leaf blades and the sensitivity of certain fungal pathogens to

fungicides. Understanding the influence of temperature on persistence and efficacy of fungicides

may aid in the more precise, efficient use of fungicides in future disease management.

86

1. INTRODUCTION

The most common disease of golf course turfgrass in temperate climates is dollar spot,

caused by the fungus Sclerotinia homoeocarpa F. T. Bennett (Walsh et al., 1999). S.

homoeocarpa has a wide host range among turfgrass species, but is most problematic on

creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua L.) putting greens,

tees, and fairways. Leaf symptoms initially appear as small, straw-colored lesions with a

reddish-brown border. When conditions are most favorable for dollar spot development,

multiple lesions may coalesce and blight the entire leaf blade (Smiley et al., 2005). The fungus

spreads locally through contact with surrounding leaf tissue, forming distinct silver dollar-sized

bleached patches 3 to 5 cm in diameter on low-cut turfgrass (Endo, 1963).

Efforts to culturally or biologically manage dollar spot have been largely ineffective

(Walsh et al., 1999; Goodman and Burpee, 1991). As a result, dollar spot management relies on

repeated fungicide applications. In the upper Midwest, where dollar spot can develop from May

to November, 4 to 12 fungicide applications may be required annually to manage the disease

(Walsh et al., 1999). Consequently, dollar spot is the most economically important turfgrass

disease with respect to fungicide expenditures (Vargas, 1994).

The primary low temperature disease of golf course turfgrass in temperate climates is

Microdochium patch caused by the fungus Microdochium nivale (Fr.) Samuels & I. C. Hallett

(Mann and Newell, 2005). Symptoms of Microdochium patch vary depending on the

environmental conditions. The disease is most severe under prolonged snow cover, where

circular patches of tan to bleached turf 30 to 60 cm in diameter occurs. In response to sunlight,

the perimeter of patches may appear pink due to the production of sporodochia. When

temperatures are between 10 and 20C with prolonged periods of leaf wetness, symptoms

87

initially appear as small, rust-colored spots less than 5 cm in diameter. Symptoms occasionally

develop in a linear pattern due to dispersal of conidia by surface water flow or mechanical

traffic. Spots may coalesce to form larger patches, but individual foci rarely expand beyond 20

cm (Smiley et al., 2005). Although cultural methods can reduce disease severity, the primary

method for managing Microdochium patch on golf courses is with chemical fungicide

applications.

Despite frequent fungicide applications, Microdochium patch and dollar spot still develop

in the winter and summer months, respectively. Latin (2011) identifies three primary factors that

can affect fungicide performance and lead to disease development. The first factor is disease

pressure, which relates to the aggressiveness of the pathogen and the susceptibility of the host.

The second factor is fungicide deposition, which relates to the fungicide application itself and

can include improper fungicide rates, extended fungicide reapplication intervals, or improper

fungicide coverage. The third factor is the depletion of fungicides and fungicide protection,

which to date has been difficult to quantify and is rarely considered by diagnosticians when

investigating potential factors in disease development.

Of the six processes affecting fungicide degradation identified in Fate and Management

of Turfgrass Chemicals (Sigler et al., 2000), four are influenced by temperature. They are

volatilization, plant uptake, biotic degradation, and abiotic degradation. Previous research has

demonstrated that temperature plays a key role in the degradation of pesticides. Increased

degradation of chlorothalonil was detected at higher temperatures on potato (Solanum tuberosum

L.) foliage (Bruhn and Fry, 1982). In the soil, the fungicides triadimefon and iprodione and the

fumigant 1,3-dichloropropene were shown to degrade faster under warmer temperatures due to

increased microbial activity (Dungan et al., 2001; Singh et al., 2002; Wang et al., 2004).

88

Conversely, other research has shown little or no effect of temperature on the degradation of

pesticides from peanut (Arachis hypogaea L.), tomato (Lycopersicon esculentum Mill.), and

creeping bentgrass foliage (Elliot and Spurr, 1993; Frederick et al., 1996; Lukens and Ou, 1975;

Sigler et al., 2002).

Conflicting reports from the literature make it difficult to determine the primary agents of

fungicide degradation on plant surfaces and how they are influenced by temperature. Currently,

turfgrass managers reapply fungicides based on the fungicide manufacturer’s label

recommendations. These recommendations do not vary based on environmental conditions such

as temperature. Measuring the persistence of fungicides at varying temperatures may show

increased or decreased degradation rates, suggesting that chemical disease management based on

environmental conditions may be a more effective, efficient means of managing plant disease.

Degradation of specific fungicides is likely influenced strongly by fungicide chemistry,

mode of action, and phytomobility. Chlorothalonil (tetrachloroisophtalonitrile) is the most

commonly-applied conventional pesticide in the world (US EPA 2011). Chlorothalonil is a

persistent, highly insoluble (water solubility = 0.81 mg L-1

) fungicide that is resistant to many

forms of environmental degradation (Tomlin, 2009). Chlorothalonil resides on the outer surface

of the leaf and is exposed to photodegradation, microbial degradation, and volatilization.

Microbial degradation and volatilization are influenced by temperature, and changes in

temperature may significantly affect the persistence of chlorothalonil on the turfgrass leaf

surface. Despite residing on the leaf surface, chlorothalonil can also induce plant detoxification

mechanisms, although it is unclear whether this plays a significant role in chlorothalonil

degradation (Kim et al., 2004; Wang et al., 2010)

89

Iprodione (3-(3,5-dichlorophenyl)-N-isopropyl-2,4-dioxoimidazolidine-1-carboximide) is

a commonly-applied foliar fungicide registered in the United States in 1979 (US EPA, 1998).

Iprodione is a penetrant fungicide that is absorbed into the plant apoplast and is more water

soluble (water solubility = 13.0 mg L-1

) than chlorothalonil (Tomlin, 2009). Absorption into the

turfgrass plant may shield the fungicide molecule from photodegradation, volatilization, and

significant portions of bacterial communities that may contribute to degradation of the fungicide

molecule. But absorption into the turfgrass plant may also expose iprodione to plant metabolic

reactions, including general plant defense pathways (Marrs, 1996; Van Eerd et al., 2003).

Changes in temperature may alter the rate of iprodione degradation by these plant defense

mechanisms, and could affect the duration of disease suppression provided by iprodione.

Temperature may influence disease management not only through altered fungicide

degradation, but also through altered fungal sensitivity to fungicides. Fungi can resist the effects

of fungicides through either pharmacodynamic or pharmacokinetic means. Pharmacodynamic

resistance is the result of weak or absent binding of the pesticide molecule to a specific receptor

inside the fungal cell or the inability of the fungicide molecule to penetrate the cell membrane.

Resistant fungi often mutate at a particular receptor and develop pharmacodynamic resistance to

a particular fungicide (Burpee, 1997). Pharmacokinetic resistance is the result of low fungicide

concentrations reaching the target site, either through metabolism or excretion of the fungicide

molecule (Brown, 1990). Full or partial resistance through either mechanism to one or several

fungicides can lead to a loss of disease control.

One method of pharmacokinetic resistance in fungi and other organisms is through the

activity of transport proteins. Transport proteins exist in all organisms and aid in excretion of

both endogeneous and exogeneous toxins, including pesticides. The most common and

90

researched class of transport proteins is the ATP-binding cassette (ABC) transporters. ABC

transporters play a large role in detoxifying the cell, and in fungi are capable of actively

transporting both endogeneously produced toxins as well as exogeneously produced plant

defense proteins (Del Sorbo et al., 2000). ABC transporters have also been shown to transport

fungicide molecules outside of the fungal cell in filamentous fungi, increasing the level of

fungicide resistance in those particular species (Del Sorbo et al., 1997). Temperature has been

shown to alter resistance to certain insecticides through alteration of ABC transporter activity in

C. elegans (Vinuela et al., 2011). Similar results in plant pathogenic fungi may provide insight

into the relationship of temperature and fungicide resistance and may partially explain increased

disease development at certain temperatures.

The primary objectives of this experiment were to (i) measure concentration of the

fungicides chlorothalonil and iprodione at 10, 20, and 30°C for 28 or 35 days following

application and to (ii) determine in vitro sensitivity of Microdochium nivale and S. homoeocarpa

to chlorothalonil and iprodione at 5, 10, 15, 20, 25, and 30°C. We hypothesize that degradation

of both fungicides will increase at higher temperatures, and that in vitro sensitivity to each

fungicide will be lowest at optimal growth temperatures for each fungus.


2.1 Fungicide Application and Sampling

Fungicides were applied to creeping bentgrass (Agrostis stolonifera L. ‘Penncross’)

maintained at 1.25 cm grown on a native silt loam at the OJ Noer Turfgrass Research Facility in

Verona, WI. The four fungicide treatments were a non-treated control, iprodione, chlorothalonil,

and a tank mixture of both fungicides. The experimental design was a randomized complete

91

block with four replications, and fungicides were applied on 21 Jun 2010; 14 Jun 2011; and 2

Aug 2011. Chlorothalonil was applied as Daconil WeatherStik® (Syngenta Crop Protection,

Greensboro, NC) at the rate of 12.6 kg active ingredient (a.i.) ha-1

and iprodione was applied as

Chipco 26GT® (Bayer Crop Science, Kansas City, MO) at the rate of 3.1 kg a.i. ha-1

. The tank

mixture was a combination of both chlorothalonil and iprodione applied at 12.6 kg a.i. ha-1

and

3.1 kg a.i. ha-1

, respectively. All fungicides were applied at a nozzle pressure of 276 kPa using a

CO2 pressurized boom sprayer equipped with two XR Teejet 8004 VS nozzles (Teejet

Technologies, Wheaton, IL). Both fungicides were applied in 814 L water ha-1

Approximately 1 h following application, four 5-cm cores were taken from each plot on

21 Jun 2010 and transported 20 min for placement in a 10, 20 or 30oC growth chamber at the

University of Wisconsin - Madison Biotron Growth Chamber Facility. Temperature was held

constant in each growth chamber with a 12 h photoperiod and constant 75% relative humidity.

Cores were kept in 4-cm of water to keep plants hydrated and transported to the laboratory 5 min

away for fungicide analysis 0, 7, 14, and 21 d post application. Fungicide was still present 21 d

following application in 2010, so in 2011 six cores were taken from each plot and fungicide

concentration analyzed 0, 7, 14, 21, 28, and 35 d after the application. At each sampling date in

2011, two additional samples were taken from fungicide treated plots in the field and

immediately analyzed in the laboratory to compare fungicide concentration under field

conditions to plants in the growth chamber.


Both iprodione and chlorothalonil were analyzed using SmartAssay® ELISA kits

purchased from Horiba, Ltd (Horiba, Kyoto, Japan) [Watanabe et al., 2006; Watanabe and

92

Miyake, 2007]. The kits were designed for use on fresh produce, and the experimental procedure

was modified for use on golf course turfgrass (Koch et al., submitted). In brief, 0.2-g of

turfgrass leaf tissue was clipped from each core and placed in a 2-ml microcentrifuge tube (MP

Biomedicals, Solon, OH) containing approximately 200 1.4-mm diameter ceramic spheres

designed to pulverize leaf tissue (Lysing matrix D). One ml of 100% methanol was added to

each tube, and 20-µl of 50% phosphoric acid was added to only the chlorothalonil samples to

prevent alkaline hydrolysis. Tubes were then placed in an MP Biomedical FastPrep-24 Tissue

Homogenizer for 40-s at a speed of 6.0 m/s. Following homogenization each tube was

centrifuged (Eppendorf, Hamburg, Germany) for 2:00 min at a relative centrifugal force of 2348

X g to settle the plant solids and 200-l of supernatant was removed and placed in 1.5-ml of

purified water. Further dilution of the extract in 10% methanol was needed to increase the upper

limit of detection of the SmartAssay® kit. For iprodione, each sample was diluted 200-fold

following placement in 1.5-ml water in order to detect concentrations between 15 and 300 mg L-

1. For chlorothalonil each sample was diluted an additional 10,000-fold following placement in

1.5-ml water in order to detect concentrations between 75 and 750 mg L-1

.

Following dilution, 150-l of each sample was combined with 150-l of either iprodione

or chlorothalonil conjugated to horseradish peroxidase (HRP). 100-l of this mixture was then

placed into an antibody-coated well, sealed, and allowed to react for 1 h at 22C. Following the

1 h reaction time, each well was washed 3 times with 100-l of phosphate buffered saline with

Tween (PBST) to remove unbound antigen and 100-l of tetramethylbenzidene was added as a

chromogenic reagent and allowed to react for 10 min. Following the chromogenic reaction, 100-

l of a 5% sulfuric acid stop solution was added and the light absorbance in each well was

93

measured at 450 nm using a Labsystems Original Multiskan Plus (Labsystems, Helsinki,

Finland). The absorbance reading was then converted to fungicide concentration using the

equation of the regression line formed from standard fungicide concentrations provided by

Horiba. Two standard concentrations of iprodione (1.5 µg L-1

and 30 µg L-1

) and chlorothalonil

(0.15 µg L-1

and 1.5 µg L-1

) were used to calculate the regression line for each respective assay.

Mean iprodione and chlorothalonil concentrations were analyzed independently.

Chlorothalonil results from 2010 were inconsistent and not included in the results. Iprodione

concentration was measured through 21 d following application in 2010 and through 35 d in both

2011 analyses. Because of this, iprodione results through 21 d from 2010 and both 2011

analyses were analyzed independently of iprodione results obtained through 35 d in both the

2011 analyses. Fungicide concentration values at each temperature and date of analysis were

subjected to analysis of variance using PROC MIXED in SAS (Version 9.1; SAS Institute, Cary,

NC). Lsmeans were calculated for each sampling date and pair-wise comparisons between

fungicide concentrations were performed using Tukey’s adjusted p-value in SAS. Non-treated

controls were not included in the fungicide analysis.

2.3 Temperature influence on fungicide sensitivity

The effective concentration to inhibit 50% of growth (EC50) was measured on two fungal

species at five different temperatures. Two isolates of Sclerotinia homoeocarpa collected from

the OJ Noer Turfgrass Research and Education Facility in Verona, WI and two isolates of

Microdochium nivale collected from Blackhawk Country Club in Madison, WI were used in the

assay.

94

Six concentrations of iprodione and chlorothalonil were used to determine the EC50 of

each fungus. For S. homoeocarpa, chlorothalonil concentrations were 0, 1, 2, 5, 10, and 25 mg

L-1

and the iprodione concentrations were 0, 0.1, 1, 2, 4, and 8 mg L-1

. For M. nivale, the

chlorothalonil concentrations were 0, 1, 5, 10, 50, and 100 mg L-1

and the iprodione

concentrations were 0, 1, 2, 5, 10, 25 mg L-1

. Technical grade fungicide active ingredient was

obtained from ChemService (ChemService, West Chester, PA) and dissolved in 10% w/v

acetone solution. The dissolved fungicide solution was diluted to the proper concentration by

adding the proper amount of fungicide solution to cooled (≈50°C) liquid Difco (Becton,

Dickinson, and Company, Sparks, MD) potato dextrose agar (PDA) following autoclaving.

One 5-mm plug of M. nivale or S. homoeocarpa was subcultured from one week old

cultures grown on PDA and placed upside down in the center of 10-cm Petri plates filled with

fungicide-amended media. Each fungicide concentration was tested in triplicate and the entire

study was replicated three times for each fungus. Plates were transferred immediately to dark

growth chambers set at constant temperatures of 10, 15, 20, 25, and 30°C for S. homoeocarpa

and 5, 10, 15, 20, and 25°C for M. nivale.

Radial mycelial growth was measured in two perpendicular directions beginning 48 h

after initiation of the experiment. Repeat measurements were taken every 24 h until growth in

the non-amended media of each temperature reached the edge of the Petri dish. Relative growth

(RG) for each fungicide concentration was then calculated by dividing the average radial growth

of mycelia in the fungicide-amended media versus the average radial growth of mycelia in the

non-amended media. The EC50 for each isolate and temperature was estimated through linear

regression (PROC REG in SAS) of the probit-transformed relative inhibition value (RI = 1 –

RG) on log10-transformed fungicide concentration (Kerns et al., 2009).

95

3. RESULTS

3.1 Iprodione Analysis

Iprodione concentration 21 days after application (DAA) in all 3 analyses (Table 1) was

analyzed independently of iprodione concentration 35 DAA in both the 2011 analyses (Table 2).

In both situations, iprodione concentration was influenced by temperature and DAA and a

temperature X DAA interaction was also observed.

Differences in iprodione concentration were not observed between cores treated with

iprodione alone and in tank mixture with chlorothalonil. As a result, iprodione concentrations

from cores treated with iprodione alone and in the tank mixture were combined. Overall,

iprodione concentration dropped most rapidly at 30°C, followed closely by 20°C, with

concentration in both chambers falling below 100 mg L-1

by 21 DAA (Figure 1). Concentration

in the 10°C growth chamber dropped more gradually, remaining above 200 mg L-1

35 DAA.

Differences in iprodione concentration among cores from each growth chamber were apparent

beginning 14 DAA (Table 3, 4). In the 21 day analysis in 2010 and 2011, differences in

iprodione concentration were observed between cores in the 10 and 20°C and 10 and 30°C

growth chambers at 14 and 21 DAA (Table 3). In the 35 day analysis in 2011, differences in

iprodione concentration were observed between cores in the 10 and 20°C and 10 and 30°C

growth chambers 14 DAA but not from cores in the 20 and 30°C growth chambers (Table 4).

Iprodione concentration from field samples fell rapidly from an initial concentration of 325 mg

L-1

, to 125 mg L-1

7 DAA, to 0 mg L-1

14 DAA (Figure 2).

96

3.2 Chlorothalonil analysis

Chlorothalonil results from both 2011 analyses were combined. Differences were not

observed in chlorothalonil concentration between cores treated with chlorothalonil alone and in

tank mixture with iprodione and their results were also combined. Chlorothalonil concentration

was impacted by both temperature and DAA and a DAA X temperature interaction was observed

(Table 5).

Initial chlorothalonil concentration for all three temperature treatments was

approximately 1000 mg L-1

(Figure 3). Concentration fell most rapidly on cores in the 30°C

growth chamber, falling to approximately 500 mg L-1

14 DAA and to 200 mg L-1

28 DAA.

Chlorothalonil concentration dropped more gradually at 20°C, falling to 600 mg L-1

14 DAA

before dropping more rapidly to 200 mg L-1

28 DAA. Concentration fell least rapidly at 10°C,

dropping to 800 mg L-1

14 DAA and 400 mg L-1

28 DAA. Chlorothalonil concentration at all

three temperatures fell in a linear fashion over the 28 d experiment. Differences between

chlorothalonil concentration from the 10 and 30°C growth chambers were observed 14 and 21

DAA but not 28 DAA (Table 6). No differences in chlorothalonil concentration amongst cores

from the 20 and 30°C growth chambers were observed throughout the experiment.

Chlorothalonil concentration from field samples fell rapidly from an initial concentration of 1000

mg L-1

to 200 mg L-1

14 DAA to 0 mg L-1

21 DAA (Figure 4)

3.3 In vitro fungicide sensitivity

Differences in EC50 among isolates of S. homoeocarpa isolates S10 and 2F92 were not

observed in either iprodione or chlorothalonil-amended media and the results were combined for

analysis (Figure 5). The iprodione EC50 values for S. homoeocarpa did not fluctuate with

97

temperature and remained constant between 1.5 and 2.0 mg L-1

. Conversely, S. homoeocarpa

EC50 values were between 2.0 and 6.0 mg L-1

on chlorothalonil-amended media grown at 10, 15,

25, and 30°C, but increased to 12.0 mg L-1

at 20°C.

Differences in EC50 between M. nivale isolates BH7 and BH8 were not observed in either

fungicide-amended media and the results were combined for analysis. The M. nivale EC50

values steadily increased on iprodione-amended media with increasing temperature, from 2.0 mg

L-1

at 5°C to over 10.0 mg L-1

at 25°C (Figure 6a). M. nivale EC50 values were higher overall on

chlorothalonil-amended media compared to iprodione and varied with temperature. EC50 values

ranged from 25-50 mg L-1

at 5, 10, and 25°C and were approximately 250 mg L-1

at 15 and 20 °C

(Figure 6b).

4. DISCUSSION

Both iprodione and chlorothalonil concentration on turfgrass leaf blades fell most rapidly

at temperatures of 20 and 30°C. Iprodione concentration at 20 and 30°C dropped slowly for the

first 7 DAA, then rapidly declined between 7 and 14 DAA before declining gradually during the

remainder of the experiment. The delayed degradation rate may be the result of several factors,

one of which is likely the delayed absorption of fungicide into the plant. Iprodione is a localized

penetrant fungicide, and as such is absorbed into the leaf apoplast (Latin, 2011). Research has

shown that fungicides applied to leaf surfaces can take up to 7 days to fully absorb into the leaf

surface (Godwin et al., 1999). Even then, upwards of 50% of the fungicide may remain bound to

the lipid layers and accumulate on the leaf surface (Latin, 2011). Once absorbed into the leaf,

numerous plant defense responses may rapidly degrade iprodione. Though specific iprodione

detoxification mechanisms within the plant leaf are not fully understood, research has shown that

98

plant cells will release reactive oxygen species or other highly reactive enzymes into the apoplast

to counter environmental stressors or pathogen attack (Baker et al., 2002; Baker et al., 2005; Van

Eerd et al., 2003). These enzymes may also be released following exposure to iprodione and

degrade the parent molecule through oxidative reactions. The enzymatic processes present in the

apoplast may be more active at higher temperatures, providing a potential explanation for the

increased degradation rate at higher temperatures observed with iprodione.

Ahough the rate of chlorothalonil degradation increased at higher temperatures, the rate

of decrease within each temperature was linear across all 28 days. A linear decrease in

chlorothalonil concentration suggests that the primary agent of degradation on the leaf surface

remains stable over time, but can increase in activity at higher temperatures. Thus, the most

likely mechanism influencing chlorothalonil degradation on the leaf surface may be bacterial

metabolism. Bacterial populations on a leaf surface may remain relatively stable within each

temperature during the course of the experiment, but the metabolic activity of each population

would likely increase with increasing temperature. Previous research has demonstrated the

importance of microbial activity on the degradation of chlorothalonil in a soil environment

(Motonaga et al., 1998; Singh et al., 2002; US EPA, 1999), and other research has indicated

bacterial degradation is critical in the degradation of fungicides on a turfgrass leaf blade

(Frederick et al., 1996).

Plant and bacterial metabolism are not the only factors contributing to the degradation of

iprodione and chlorothalonil, respectively. Although iprodione is a penetrant fungicide, much of

the iprodione applied accumulates on the leaf surface (Latin, 2011) and is likely prone to

degradation by volatilization and bacterial metabolism. Iprodione is known to degrade rapidly in

the soil in the presence of large bacterial populations, and there is little doubt that bacterial

99

degradation on and within the leaf occurs (Klose et al., 2010; Mercadier et al., 1997; Walker,

1987; Wang et al., 2004; Zadra et al., 2006). Previous research on turfgrass leaves has

demonstrated the importance of bacterial metabolism on the degradation of vinclozolin, a

fungicide in the same chemical class as iprodione (Frederick et al., 1996). Despite being a

contact fungicide that resides primarily on the leaf surface, chlorothalonil has been shown to

induce plant detoxification responses on leaf surfaces (Kim et al., 2004). It remains unclear,

however, what role plant detoxification mechanisms play in chlorothalonil degradation on the

leaf surface. Other factors such as leaf growth, rainfall, and volatilization have also been shown

to impact chlorothalonil degradation on potato, tomato, and creeping bentgrass foliage (Bruhn

and Fry, 1982; Lukens and Ou, 1976; Sigler et al., 2002).

Concentration of iprodione and chlorothalonil in the field were compared to

concentrations collected from cores in the growth chambers during both 2011 analyses. Average

daily temperature in the field during both analyses ranged from 15-25°C, considerably lower

than the constant 30°C found in the warmest growth chamber. Despite warmer temperatures in

the growth chambers, iprodione and chlorothalonil concentrations declined more rapidly from

field samples than from cores in the growth chamber. Photodegradation is one potential

explanation for the increased degradation rate in the field. Photodegradation, however, has a

minimal effect on fungicide degradation on the leaf surface and a larger effect on fungicide

degradation when fungicides are present in solution or with soil constituents (Burrows et al.,

2002; Hustert and Moza, 1997). The primary factor in the increased loss of both iprodione and

chlorothalonil in the field is believed to be from physical removal by mowing. Turfgrass grows

primarily from the base of the plant, meaning that fungicides applied to the leaf blade will move

upwards with the growing leaf blade and eventually be removed by mowing (Beard, 1973). The

100

results presented here suggest that at temperatures optimal for turf growth, the majority of

fungicide will be physically removed by mowing and not by a specific fungicide degradation

mechanism.

If the primary factor in fungicide loss from a turfgrass system is removal by mowing,

then reduction in the amount of leaf area removed during each mowing could prolong fungicide

persistence and disease suppression. Plant growth regulators such as paclobutrazol and

trinexipac-ethyl are used regularly on golf courses to reduce vertical plant growth and increase

stress tolerance of creeping bentgrass plants (Xu and Huang, 2010). Extended fungicide efficacy

in turfgrass has been observed where fungicides have been applied in combination with a plant

growth regulator (Burpee et al., 1996; Putman and Kaminski, 2011). Extended fungicide

efficacy when applied with plant growth regulators is likely due to reduced fungicide removal by

mowing, and not due to any direct fungicidal effect of plant growth regulators. The relationship

between extended fungicide efficacy and plant growth regulators warrants further investigation

to determine the precise influence on pesticide persistence and its potential impact on the number

or rate of fungicide applications required annually.

In addition to the role of fungicide persistence in disease management, sensitivity of

fungal pathogens to fungicides may change in different environments and affect their

management. Estimated concentration to inhibit 50% of fungal growth (EC50) varied between

fungicide, fungus, and temperature. EC50 values of M. nivale on iprodione-amended media

increased steadily with increasing temperature, suggesting that M. nivale becomes more tolerant

of iprodione at higher temperatures. S. homoeocarpa growth on iprodione-amended media was

not altered in response to temperature. M. nivale was highly tolerant of chlorothalonil at 10 and

15°C, and much more susceptible at 5, 20, and 25°C. S. homoeocarpa had much lower EC50

101

values on chlorothalonil-amended media than M. nivale. This evidence suggests that fungi can

become more or less sensitive to different fungicides at different temperatures, which may

significantly impact disease management. The relationship between fungicide-sensitivity and

temperature appears to be unique to each fungus and fungicide and should not be widely

correlated to other pathogen systems without further research.

One potential mechanism for the temperature-induced resistance is the activity of ATP-

binding cassette (ABC) transporter proteins. ABC transporter proteins in fungi and other

organisms have been shown to increase resistance to fungicides and other pesticides through

transport of fungicide molecules out of the cell (Del Sorbo et al., 1997; Del Sorbo et al., 2000).

In addition, activity of ABC transporter proteins has been shown to vary in response to

temperature, which in turn could alter the organism’s tolerance to a pesticide at different

temperatures (Vinuela et al., 2011). ABC protein activity is highly complex and it remains

unclear if ABC proteins can impact the fungicide-sensitivity of common turfgrass pathogens.

The impact on disease management could be significant and further investigation is warranted.

While pharmacokinetic resistance through rapid excretion of fungicide active ingredient

is a relatively recent area of study, pharmacodynamic fungicide resistance has been widely

documented in turfgrass (Burpee, 1997; Cole et al., 1968; Golembiewski et al., 1995; Jo et al.,

2006). Disease control failures are often observed near the end of a reapplication interval and

during periods of hot, humid weather conducive for disease development. Golf course

superintendents often assume fungicide resistance as the reason for fungicide failures (Koch et

al., 2009), yet fungicide resistance in the population at that site is rarely assessed in the

laboratory. We contend that under these conditions, nearing the end of a re-application interval

102

and in hot, humid conditions, accelerated fungicide degradation may be a more common factor in

fungicide failures than fungicide resistance.

Disease management in a turfgrass environment is a complex system that is influenced by

host resistance, pathogen aggressiveness, environmental conditions, and the presence of

fungicides. The activity and persistence of fungicides on the leaf blade is a critical component in

effective disease management, but one that has remained unclear. Temperature clearly plays a

larger role in disease management than just pathogen aggressiveness or host susceptibility. The

impact of temperature on fungicide persistence may influence future fungicide reapplication

intervals. Rather than simply using the recommended reapplication interval regardless of the

environmental conditions present, future turfgrass managers may consider temperature and other

factors when deciding when to apply fungicides. This may result in more effective disease

management at higher temperatures, and extended reapplication intervals at lower temperatures.

Considering environmental variables such as temperature when planning a fungicide program

will lead to more effective, efficient use of fungicides without sacrificing turfgrass quality.

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109

TABLES AND FIGURES

Table 1: Analysis of variance (ANOVA) of iprodione concentration from turfgrass clippings

collected from cores sampled at the OJ Noer Turfgrass Research Facility in Verona, WI. Study

was performed once during the summer of 2010 and replicated twice during the summer of 2011.

Turfgrass cores were sprayed with either iprodione alone or iprodione mixed with chlorothalonil

and placed immediately in a 10, 20, or 30°C for 0, 7, 14, or 21 days.

Source DF F Value p-value

Fungicide 1 0 0.9984

Temperature 2 36.8 <.0001

Fungicide*Temperature 2 0.37 0.6907

Days after application (DAA) 3 99.26 <.0001

Days (DAA)*Fungicide 3 0.11 0.9534

Days (DAA)*Temperature 6 7.89 <.0001

Days (DAA)*Fungicide*Temperature 6 0.57 0.7562

110

Table 2: Analysis of variance (ANOVA) of iprodione concentration from turfgrass clippings

collected from cores sampled at the OJ Noer Turfgrass Research Facility in Verona, WI. Study

was replicated twice during the summer of 2011. Turfgrass cores were sprayed with either

iprodione alone or iprodione mixed with chlorothalonil and placed immediately in a 10, 20, or

30°C for 0, 7, 14, 21, 28, or 35 days.


Fungicide 1 1.09 0.2977




DAA*Fungicide 5 0.39 0.8555

DAA*Temperature 10 6.79 <.0001

Days (DAA)*Fungicide*Temperature 10 0.26 0.988

111

Table 3: Pair-wise comparison of iprodione concentration analyzed from turfgrass clippings

collected from cores at 10, 20, and 30°C within each analysis date. Cores were analyzed at 0, 7,

14, and 21 days following the iprodione application. P-value represents Tukey’s adjusted p-

value.

Days (Temp) vs Days (Temp) p-value Days (Temp) vs. Days (Temp) p-value

0 (10) vs 0 (20) 1.00 14 (10) vs 14 (20) 0.0013

0 (10) vs 0 (30) 1.00 14 (10) vs 14 (30) <.0001

0 (20) vs 0 (30) 1.00 14 (20) vs 14 (30) 0.0145

7 (10) vs 7 (20) 1.00 21 (10) vs 21 (20) <.0001

7 (10) vs 7(30) 0.391 21 (10) vs 21 (30) <.0001

7 (20) vs 7 (30) 0.805 21 (20) vs 21 (30) 0.9214

112

Table 4: Pair-wise comparison of iprodione concentration analyzed from turfgrass clippings


14, 21, 28, and 35 days following the iprodione application. P-value represents Tukey’s adjusted

p-value.


0 (10) vs 0 (20) 1.00 21 (10) vs 21 (20) <.0001

0 (10) vs 0 (30) 1.00 21 (10) vs 21 (30) <.0001

0 (20) vs 0 (30) 1.00 21 (20) vs 21 (30) 1.00

7 (10) vs 7 (20) 0.999 28 (10) vs 28 (20) <.0001

7 (10) vs 7(30) 0.881 28 (10) vs 28 (30) <.0001

7 (20) vs 7 (30) 1.00 28 (20) vs 28 (30) 1.00

14 (10) vs 14 (20) <.0001 35 (10) vs 35 (20) <.0001

14 (10) vs 14 (30) <.0001 35 (10) vs 35 (30) <.0001

14 (20) vs 14 (30) 0.546 35 (20) vs 35 (30) 1.00

113

Table 5: Analysis of variance (ANOVA) of chlorothalonil concentration from turfgrass

clippings collected from cores sampled at the OJ Noer Turfgrass Research Facility in Verona,

WI. Study was replicated twice during the summer of 2011. Turfgrass cores were sprayed with

either chlorothalonil alone or chlorothalonil mixed with iprodione and placed immediately in a

10, 20, or 30°C for 0, 7, 14, 21 or 28 days.


Fungicide 1 3.88 0.0503




DAA*Fungicide 4 1.57 0.1833

DAA*Temperature 8 2.00 0.0488

DAA*Fungicide*Temperature 8 1.64 0.1148

114

Table 6: Pair-wise comparison of chlorothalonil concentration analyzed from turfgrass clippings


14, 21, and 28 days following the chlorothalonil application. P-value represents Tukey’s

adjusted p-value.


0 (10) vs 0 (20) 1.00 21 (10) vs 21 (20) 0.753

0 (10) vs 0 (30) 1.00 21 (10) vs 21 (30) 0.009

0 (20) vs 0 (30) 1.00 21 (20) vs 21 (30) 0.888

7 (10) vs 7 (20) 1.00 28 (10) vs 28 (20) 0.194

7 (10) vs 7(30) 0.471 28 (10) vs 28 (30) 0.427

7 (20) vs 7 (30) 0.937 28 (20) vs 28 (30) 1.00

14 (10) vs 14 (20) 0.823

14 (10) vs 14 (30) 0.016

14 (20) vs 14 (30) 0.877

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Figure 1: Iprodione concentration as affected by temperature and days following fungicide

application on turfgrass clippings collected from cores during the summer of 2010 and twice

during the summer 2011. Cores were immediately placed in growth chambers at 10, 20, or 30°C

following the fungicide application. Concentration was analyzed weekly for 3 weeks during the

summer of 2010 and 5 weeks during both 2011 analyses. Error bars represent standard error for

each temperature at each analysis date. A – Iprodione concentration in both 2011 analyses

through 35 days following the application; B – Iprodione concentration in all 2010 and 2011

analyses runs through 21 days following the application.

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Days After Application

0 7 14 21 28 35

Ipro

dio

ne

Co

nce

ntr

atio

n (

mg

l-1

)

0

50

100

150

200

250

300

350

Nontreated

10C Growth Chamber

20C Growth Chamber

30C Growth Chamber


0 7 14 21

Ipro

dio

ne C

oncentr

ation (

mg l

-1)

0

50

100

150

200

250

300

350

Nontreated

10C Growth Chamber

20C Growth Chamber

30C Growth Chamber

A

B

117

Figure 2: Iprodione concentration from turfgrass clippings collected from cores sampled from

the OJ Noer Turfgrass Research Facility during the summer of 2011. Cores were analyzed 0, 7,

and 14 days following the application. Error bars represent standard errors within each analysis

date.


0 7 14

Ipro

dio

ne

Co

nce

ntr

atio

n (

mg

l-1

)

0

50

100

150

200

250

300

350

118

Figure 3: Chlorothalonil concentration as affected by temperature and days following fungicide

application on turfgrass clippings collected from cores twice during the summer 2011. Cores

were immediately placed in growth chambers at 10, 20, or 30°C following the fungicide

application and concentration analyzed weekly for 4 weeks. Error bars represent standard error

for each temperature at each analysis date.

Days after application

0 5 10 15 20 25 30

Ch

loro

tha

lon

il C

on

ce

ntr

atio

n (

mg

l-1

)

0

200

400

600

800

1000

1200

Nontreated

10

20

30

119

Figure 4: Chlorothalonil concentration from turfgrass clippings collected from cores sampled

from the OJ Noer Turfgrass Research Facility during the summer of 2011. Cores were analyzed

0, 7, 14, 21, and 28 days following the application. Error bars represent standard errors within

each analysis date.

Days after application

0 5 10 15 20 25 30

Ch

loro

tha

lon

il c

on

ce

ntr

atio

n (

mg

l-1

)

0

200

400

600

800

1000

1200

120

Figure 5: In vitro fungicide sensitivity of Sclerotinia homoeocarpa on chlorothalonil and

iprodione-amended potato dextrose agar media at 10, 15, 20, 25, and 30°C. Fungicide sensitivity

determined by calculating the estimated concentration to inhibit 50% of fungal growth (EC50) of

2 S. homoeocarpa isolates collected from creeping bentgrass (Agrostis stolonifera) in Madison,

WI. Error bars represent standard errors within each temperature.

Temperature (C)

5 10 15 20 25 30 35

EC

50 (

mg l

-1)

0

2

4

6

8

10

12

14

16

Chlorothalonil

Iprodione

121

Figure 6: In vitro fungicide sensitivity of Microdochium nivale on chlorothalonil and iprodione-

amended potato dextrose agar media at 5, 10, 15, 20, and 25°C. Fungicide sensitivity

determined by calculating the estimated concentration to inhibit 50% of fungal growth (EC50) of

2 M. nivale isolates collected from creeping bentgrass (Agrostis stolonifera) in Madison, WI.

Error bars represent standard errors within each temperature.

122

Temperature (C)

0 5 10 15 20 25 30

EC

50 (

mg l

-1)

0

2

4

6

8

10

12

Iprodione

0 5 10 15 20 25 30

EC

50 (

mg l

-1)

0

50

100

150

200

250

300

350

Chlorothalonil

123

CHAPTER 4:

Impact of novel fungicide timings on the development of snow mold and dollar spot on golf

course turfgrass.

124

ABSTRACT

The primary diseases of golf course turfgrass in the Great Lakes region of the United

States are dollar spot, Typhula blight, and Microdochium patch. Successful management of

these diseases can require 10 or more fungicide applications per year. This study was conducted

to determine whether novel fungicide timings in the fall and spring can delay the onset of dollar

spot, reduce the overall disease severity, and lower the total number of fungicide applications

required for acceptable control compared to a conventional fungicide program. Combinations of

fungicide applications made in early fall, late fall, early spring, and late spring were evaluated in

2009, 2010, and 2011 in Wisconsin for their ability to control Microdochium patch, Typhula

blight, and dollar spot throughout the year. In general, multiple fungicide applications targeting

dollar spot in the spring were the most effective at delaying dollar spot development until July in

2009 and 2010. Early fall applications targeting dollar spot were also effective at reducing dollar

spot the following season, yet the delay in dollar spot development was minor compared to the

effect of springtime fungicide applications. Late fall fungicide applications did not reduce dollar

spot severity, but were critical for management of both Microdochium patch and Typhula blight.

Novel springtime fungicide applications delayed dollar spot onset until mid to late July, which

could eliminate the need for 1 or possibly 2 fungicide applications without sacrificing turfgrass

quality. Even this minor reduction in fungicide usage can have significant financial and

environmental benefits for the golf course manager.

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1. INTRODUCTION

Nearly 50 different fungal diseases can adversely affect turfgrass planted as home lawns,

golf courses, athletic fields, and other settings around the world (Smiley et al., 2005).

Approximately 12 of these are severe enough to require routine or repeated fungicide

applications, most often in intensively-maintained golf course settings (Latin, 2011). In

temperate climates, the number of diseases that require periodic fungicide applications on golf

course turfgrass can be narrowed down to five or fewer. In climates similar to the Great Lakes

region of the United States, the vast majority of all fungicides applied to golf course turfgrass are

applied to manage dollar spot (Sclerotinia homoeocarpa F.T. Bennett), Microdochium patch

(Microdochium nivale (Fr.) Samuels & I. C. Hallett), and Typhula blight (Typhula incarnata

(Fr.); T. ishikariensis Arsvoll and J.D. Smith). Reducing the overall number of fungicide

applications required to manage these three diseases could lead to a significant reduction in

overall fungicide usage, providing environmental, toxicological, and financial benefits to the

turfgrass manager.

Dollar spot is the most common warm-weather disease on golf course turfgrass in

temperate climates (Walsh et al., 1999). The pathogen has a wide host range amongst turfgrass

species, but its primary impact is on creeping bentgrass (Agrostis stolonifera L.) and annual

bluegrass (Poa annua L.) which are commonly used for golf course putting greens, tees, and

fairways. Optimal environmental conditions for dollar spot development are temperatures

between 18 and 30°C and relative humidity greater than 85%. Prolonged periods of optimal

conditions can result in numerous circular patches of bleached turfgrass 2-5 cm in diameter

(Smiley et al., 2005). The marginal effectiveness of cultural or biological controls of dollar spot,

along with the long duration of dollar spot activity, has resulted in more fungicide applications

126

made to control dollar spot than any other turfgrass disease in the United States (Goodman and

Burpee, 1991; Vargas, 1994; Walsh et al., 1999).


world is Microdochium patch. The pathogen can be found in temperate climates around the

world but is most prevalent in the North American Pacific Northwest, United Kingdom, and

northern Europe where cool, humid conditions persist (Mann and Newell, 2005). M. nivale has a

relatively wide host range and is a common pathogen of most turfgrasses, especially bentgrasses

(Agrostis spp.), as well as wheat, oats, and barley (Couch, 1995). Symptoms of Microdochium

patch can vary depending on the environmental conditions. When snow cover is not present and

temperatures remain between 0-8C, symptoms first appear as small, reddish or rust-colored

spots less than 5 cm in diameter. Under prolonged snow cover, larger patches of tan to bleached

turf 30-60 cm in diameter may occur. A thin, pink-colored ring may develop around the

perimeter of the patch due to the production of sporodochia in response to sunlight (Smiley et al.,

2005). As a result, another common name for this disease is pink snow mold. Management of

Microdochium patch often relies on one or two fungicide applications in the fall prior to the

onset of conditions favorable for disease development, although in cool and humid regions

fungicide applications may be required throughout the year (Mann and Newell, 2005).

Typhula blight is an important turfgrass disease in regions that receive significant

snowfall during the winter months. This disease ranked 2nd

in terms of importance among

diseases in a survey of golf course superintendents from the Great Lakes region of the United

States (Hsiang et al., 1999). Where snow cover persists for 2-3 consecutive months, Typhula

blight will develop as circular patches of gray to tan turf 5-100 cm in diameter. Upon snowmelt,

small, spherical sclerotia 1-5 mm in diameter are produced that act as long-term survival

127

structures (Smiley et al., 2005). Management of Typhula blight relies on 1-2 fungicide

applications in the fall prior to snowfall (Hsiang et al., 1999). Unlike Microdochium patch,

repeat fungicide applications are not necessary because Typhula blight requires greater than 60

days of continuous snow cover to develop.

Conventional programs to control dollar spot, Microdochuim patch, and Typhula blight

rely on preventative fungicide applications made shortly before disease onset, and for dollar spot

repeat applications are performed every 14-21 d throughout the growing season. Ten or more

fungicide applications are typically scheduled just to control these three diseases. Repeat

fungicide applications pose significant ecotoxicological risks and can raise a negative social

profile of turfgrass management (Robbins et al., 2001, Alavanja et al., 2005). In addition,

fungicide applications can impose a significant financial burden on most golf facilities, with

some individual fungicide applications on large acreages such as fairways costing in excess of

$5,000 (Koch, personal communication).

Recent research has shown that fungicides applied well before dollar spot symptoms

traditionally appear can delay the onset of dollar spot symptoms and reduce the overall severity

of dollar spot (McDonald and Dernoeden, 2006; Koch et al., 2009). Previous research has also

shown that fungicides applied to control snow molds the previous fall may reduce dollar spot

development the following season (Burpee et al., 1990; Landschoot et al., 2001). The influence

that both fall and early spring fungicide applications have collectively on the development of

dollar spot throughout the following year has not been investigated, despite the fact that many

golf courses throughout the upper Midwest apply fungicides in the fall to control dollar spot and

snow molds. Investigating the degree of dollar spot and snow mold suppression from novel fall

and springtime fungicide applications may allow golf course superintendents to reduce their

128

overall fungicide inputs without sacrificing turfgrass quality. The objectives of this study were

to determine the degree of dollar spot, Microdochium patch, and Typhula blight suppression

obtained with novel spring and fall fungicide timings and to measure the length and degree of

dollar spot control observed the following year.


The study was conducted on two plots at the OJ Noer Turfgrass Research (OJN) and

Educational Facility in Verona, WI and on one plot at Sentryworld Golf Course in Stevens Point,

WI from the fall of 2008 through the summer of 2011. At OJN, the study was conducted on

mature creeping bentgrass (Agrostis stolonifera ‘Penncross’) maintained at a fairway height of

1.27 cm and grown on a Troxel silt loam soil with a pH of 7.2

(http://websoilsurvey.nrcs.usda.gov/app/WebSoilSurvey.aspx). The study was replicated on

mature ‘Penncross’ creeping bentgrass maintained under putting green conditions at 3.175 mm

and grown on a USGA-recommended root zone with a pH of 6.8. At Sentryworld GC the study

was completed on a mature ‘Penncross’ creeping bentgrass nursery maintained at 1.27 cm and

grown on a sand:silt loam mixed soil with a pH of 7.3. At all sites, experimental units measured

0.91 by 3.05 m and were arranged in a randomized complete block design with four replications.

In order to determine the cumulative effect of fungicide applications in subsequent years, the

same experimental layout was used at each plot in each year of the study.

Treatments consisted of six different fungicide timings, a non-treated control, and a

conventional fungicide program. Individual treatment timings were (1) one late fall application;

(2) one late spring; (3) one late fall plus one late spring; (4) one early fall plus one late fall; (5)

http://websoilsurvey.nrcs.usda.gov/app/WebSoilSurvey.aspx

129

one early spring plus one late spring; and (6) two fall plus two spring applications. Specific

fungicide application dates are listed in Table 1. A non-fungicide treatment and a conventional

fungicide program were included as a negative and positive control, respectively. The

conventional program was applied according to typical fungicide programs designed for fairway

height turfgrass by the superintendents at golf courses located in southern or central Wisconsin.

At the southern Wisconsin course the fungicide program consisted of biweekly applications of

chlorothalonil beginning June 1st through mid-July, after which multiple fungicides from the

DMI and QoI chemistry classes were rotated in. At the central Wisconsin course only the snow

mold fungicide program was used, which consisted of a single application of Instrata® fungicide

(Syngenta Crop Protection, Greensboro, NC) applied at the high label rate shortly prior to

snowfall.

Boscalid (3-pyridinecarboximide,2-chloro-N-(4’-chloro(1,1’-biphenyl)-2-yl) was applied

as Emerald (BASF, Research Triangle Park, NC) at the rate of 0.4 kg a.i. ha-1

and was used for

the early fall and late spring fungicide applications because of its efficacy against dollar spot. A

tank mixture of iprodione (3-(3,5-dichlorophenyl)-N-(1-methylethyl)-2,4-dioxo-1-

imidazolidinecarboximide) applied as Chipco 26GT® (Bayer Crop Science, Kansas City, MO) at

the rate of 3.1 kg a.i. ha-1

and chlorothalonil (tetrachloroisophtalonitrile) applied as Daconil

WeatherStik® (Syngenta Crop Protection, Greensboro, NC) at the rate of 12.6 kg a.i. ha-1

was

used for the late fall and early spring timings because of its efficacy against Microdochium

patch. Treatments were applied using a CO2 - pressurized boom sprayer at 276 kPa equipped

with two XR Teejet 8004 VS nozzles. All fungicides were agitated by shaking and were applied

in the equivalent of 814 L of water ha-1

.

130

Snow mold severity was visually assessed each spring as a percent area of the plot

affected with snow mold. Dollar spot severity was assessed by counting individual foci per plot

every other week throughout the summer. In addition, turfgrass quality was visually assessed on

a 1-9 scale with 6 being acceptable. Mean disease severity and turfgrass quality were assessed

separately by location and year. Disease severity values were subjected to analysis of variance

(ANOVA; PROC MIXED) and mean separations using the Waller-Duncan k-ratio t-test (k=100)

in SAS (Version 9.1; SAS Institute, Cary, NC).

3. RESULTS AND DISCUSSION

In general, dollar spot was less severe on the fairway than the putting green plot in both

2009 and 2010 (Fig 1, 2). Since neither site was fertilized for the duration of the study, lower

nitrogen levels on the putting green plot as a result of clipping collection may explain the

observed differences in dollar spot severity. On both the fairway and putting green plots dollar

spot severity was greater for a more prolonged period in 2009 than 2010, likely due to more

consistent periods of high humidity in 2009 compared to 2010. Dollar spot severity in 2011 was

very low on both the fairway and putting green plots and consequently the results are not

included here.

On the putting green plot in 2009, all fungicide treatments including the traditional

fungicide program reduced dollar spot severity compared to the NTC at each rating date until 11

Aug (Fig 1A). On the 22 Jun and 6 Jul dates, those treatments containing springtime fungicide

applications suppressed dollar spot longer than those containing only fall fungicide applications.

Treatment 5, containing both an early and late fall fungicide application, reduced dollar spot

severity on 22 Jun and 6 Jul when compared to the NTC but was no longer distinguishable from

131

the NTC by 11 Aug. Treatment 2, which contained only a late fall application, did not suppress

dollar spot compared to the NTC. Dollar spot severity increased rapidly in late July and early

August with the onset of favorable conditions for disease development. The traditional fungicide

program relied heavily on biweekly chlorothalonil applications beginning around 1 Jun, and

minor to moderate dollar spot breakthrough was observed with this program during periods of

heavy disease pressure.

Results from the 2010 putting green plot mirrored those from 2009 (Fig 1B). In general,

treatments containing springtime fungicide applications were more effective at delaying dollar

spot and reducing its overall severity than those treatments containing only fall fungicide

applications. Significant dollar spot reductions with all fungicide timing treatments were still

being observed on the 2 Aug rating date when compared to the NTC.

Turfgrass quality in 2009 and 2010 on the putting green plots was closely correlated with

dollar spot severity (data not shown). An acceptable turfgrass quality rating of 6 or higher was

never achieved with the NTC in 2009 or 2010. In 2009, treatments 4, 6, and 7 were the only

treatments to maintain acceptable turfgrass quality on 22 Jun and all contained one or two

springtime fungicide applications. Only treatment 7 was able to maintain acceptable turfgrass

quality on 6 Jul, and no treatments provided acceptable turfgrass quality on 27 Jul or later. In

2010, those treatments containing springtime fungicide applications also provided acceptable

turfgrass quality until 28 Jun or 8 Jul.

All fungicide treatments reduced dollar spot severity on the OJN fairway in 2009

compared to the NTC on both the 22 Jun and 6 Jul rating dates (Fig 2). Dollar spot severity

increased rapidly on all treated plots near the end of July, and no treatments reduced dollar spot

severity compared to the NTC on the 27 Jul rating date. Disease pressure was quite low in 2010

132

on the fairway plot, and no differences between fungicide treatment timings were observed (data

not shown).

Snow mold was not observed on the putting green plots at OJN in 2009, 2010, or 2011.

Gray snow mold (Typhula incarnata) was observed on the OJN fairway plots following the

winters of 2009-2010 and 2010-2011 (Figure 3), and speckled snow mold (T. ishikariensis) was

observed at Sentryworld GC following the winters of 2008-2009 and 2009-2010 (Fig 4). At both

sites and in both years, only those treatments containing a late fall fungicide application provided

acceptable control of both gray and speckled snow mold. Treatments containing only springtime

fungicide applications did not affect snow mold development compared to the NTC. Only the

traditional program, containing a 3 way fungicide mixture, provided acceptable control of snow

mold under the extreme snow mold pressures observed at Sentryworld GC in 2010. Inclusion of

a fungicide from the demethylation inhibitor (DMI) class of fungicides in the traditional program

likely provided an extra level of protection over the two way fungicide mixture applied in the

study’s late fall fungicide application.

The importance for controlling snow mold in the Great Lakes region is evident when

looking at the results from Sentryworld GC in central Wisconsin. Snow mold damage was

significant on treatments containing only springtime fungicide applications, and this damage was

still evident in late May in the spring of 2009 and into June in the spring of 2010 (Fig 4).

Turfgrass quality on those plots damaged by snow mold also remained below acceptable levels

well into June in both years. While these plots were not fertilized in the spring to stimulate

turfgrass recovery, it signals the importance of controlling snow mold in the Great Lakes region

to the health of golf course turfgrass not only in the spring but also well into the summer months.

133

This study also clearly demonstrates that springtime fungicide applications have no effect on

Typhula blight once it has developed.

Past research has shown that fungicide applications targeting dollar spot made in late

spring, well in advance of the traditional first fungicide application targeting dollar spot, can

delay the onset of dollar spot incidence and decrease its overall severity (McDonald and

Dernoeden, 2006; Koch et al., 2009). The results presented here support and build upon that,

suggesting that an additional springtime fungicide made 3-4 weeks prior can provide further

reductions in dollar spot severity months later. In addition, if this early spring fungicide

application is made with a broad-spectrum fungicide that targets common springtime diseases

such as leaf spot (Drechslera) and Microdochium patch (Microdochium nivale) the benefits of

this application timing increase significantly.

As expected, our results show a late fall fungicide application is required for acceptable

control of snow mold in the Great Lakes region of the United States. It has been postulated that

fungicides applied to control snow mold in the fall may affect dollar spot development the

following summer. Burpee et al. (1990) demonstrated that fall applications of triadimefon and

propiconazole significantly reduced dollar spot severity the following summer, and Landschoot

et al. (2001) showed that multiple fall applications of pentachloronitrobenzene (PCNB) at high

label rates also reduced dollar spot development the following year. Our research provides

support for that hypothesis, as dollar spot severity was only reduced following a single late fall

fungicide application of chlorothalonil and iprodione at the OJN fairway in 2009. Treatment 5,

which contained both an early and late fall fungicide application, reduced dollar spot severity the

following summer compared to the NTC in both years and at both locations. In addition, this

treatment reduced dollar spot severity compared to the late fall only fungicide application on the

134

OJN putting green plot in 2010 but not 2009. The fungicides applied during the late fall

fungicide application are efficacious against dollar spot, suggesting that the timing of the

fungicide application and not the active ingredients themselves, reduce dollar spot severity the

following summer.

In general, treatments that delayed dollar spot onset in 2009 also delayed dollar spot

onset in 2010. Dollar spot severity on the NTC was higher in 2010 than in 2009, but dollar spot

severity was quicker to rebound following loss of fungicide protection in 2009 than in 2010.

Though it’s unclear the reason for this, the answer likely lies in the environmental conditions

present during the growing season in both 2009 and 2010. In 2010, conditions were warm and

relatively humid throughout much of the summer. In 2010, conditions were warm and very

humid for much of the first half of the summer before cooling considerably in the second half.

This emphasizes the impact of environment on the development of disease, and shows that no

matter the timing of fungicide applications, their efficacy will be determined in large part by the

environmental conditions present throughout the growing season.

The primary impact of implementing novel fungicide timing programs will likely be on

golf course fairways. Although excellent results were achieved on golf course putting greens as

well, the small acreage and high value of golf course putting greens give superintendents little

incentive to reduce fungicide applications to their putting surfaces. Fairways, however,

encompass a much larger area of the golf course and elimination of even one fungicide

application would result in several thousand dollars worth of savings. Spraying large acreages of

fairways can also be time consuming, so the reduction of even one or two fungicide applications

in the summer months may free up valuable labor for other pressing golf course needs and

reduce the fuel costs required to power the application equipment. Pesticide applications to golf

135

course fairways also increase the area of environmental exposure compared to putting greens,

with increased risk for exposure to the environment and an increased risk for environmental

damage. Reducing pesticide applications to golf course fairways by one or two per year would

result in a significant reduction in pesticide exposure to the environment.

The results presented here show that properly-timed, novel fungicide applications do

have a significant effect on the overall development of the primary diseases affecting golf course

turfgrass in the Great Lakes region of the United States. Multiple springtime fungicides, applied

well before traditional dollar spot fungicide applications are made, can delay the onset of dollar

spot into July. This can result in the savings of 1-2 fungicide applications that would normally

be made in a traditional dollar spot control program without sacrificing turfgrass quality. Along

with the inclusion of proper cultural practices associated with integrated pest management,

significant reductions in pesticide usage on large acreages of golf course turfgrass in the Great

Lakes region of the United States can be achieved immediately without conversion to disease-

resistant turfgrasses or sacrificing turfgrass quality. These reductions have both financial and

environmental benefits that can aid superintendents in times of financial distress and lessen the

environmental impact of golf course management.

LITERATURE CITED

Alavanja, M. C., Bonner, M. R. 2005. Pesticides and human cancers. Cancer Investigation 23:

700-711.

136

Burpee, L. L., Mueller, A. E., Hannusch, D. J. 1990. Control of Typhula blight and pink snow

mold of creeping bentgrass and residual suppression of dollar spot by triadimefon and

propiconazole. Plant Dis. 74: 687-689.



FL. p. 65-69.





Koch, P. L., Kerns, J. P., Stier, J. C. 2009. Spring time fungicide applications delay and reduce

dollar spot disease of turfgrass. Int. Turf. Res. Jnl. 11: 241-252.

Landschoot, P. J., Park, B. S., Uddin, W. 2001. Nontarget effects of PCNB on putting green

turf. Int. Turf Soc. Res. J. 9: 679-684.


228.


pests and diseases on golf course putting greens in England, Ireland, Scotland, and


McDonald, S. J., Dernoeden, P. H. 2006. Preventive dollar spot control in creeping bentgrass as

influenced by spray volume and a spring application of fungicides, 2005. F & N Tests

61: T017.

Robbins, P., Polderman, A., Birkenholtz, T. 2001. Lawns and toxins; an ecology of the city.

Cities 18: 369-380.

137


Diseases, 3rd



23-27.



138

TABLES AND FIGURES

Table 1. Dates of fungicide application for each treatment in 2009, 2010, and 2011 at the OJ

Noer Turfgrass Research Center in Verona, WI and at Sentryworld Golf Course in Stevens Point,

WI. Applications were made to the fairway and putting green plots at the OJ Noer on the same

date.

139

Figure 1. Mean number of dollar spot foci per plot on the putting green plot at the OJ Noer

Turfgrass Research Center in Verona, WI during the summer of (A) 2009 and (B) 2010. Dates

were analyzed individually, and disease severity values were subjected to analysis of variance

and mean separations using the Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated

control; LF = late fall; LS = late spring; LF/LS = late fall + late spring; EF/LF = early fall + late

fall; ES/LS = early spring + late spring; All = early fall + late fall + early spring + late spring; TP

= traditional program.

140

141

Figure 2. Mean number of dollar spot foci per plot on the fairway plot at the OJ Noer Turfgrass

Research Center in Verona, WI during the summer of 2009. Dates were analyzed individually,

and disease severity values were subjected to analysis of variance and mean separations using the

Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated control; LF = late fall; LS = late

spring; LF/LS = late fall + late spring; EF/LF = early fall + late fall; ES/LS = early spring + late

spring; All = early fall + late fall + early spring + late spring; TP = traditional program.

142

Figure 3. Mean snow mold severity per plot on the fairway plot at the OJ Noer Turfgrass

Research Center in Verona, WI during the springs of 2009, 2010, and 2011. Snow mold severity

was visually assessed as percent area of the plot affected. Dates were analyzed individually, and

disease severity values were subjected to analysis of variance and mean separations using the

Waller-Duncan k-ratio t-test (k=100). NTC = Nontreated control; LF = late fall; LS = late

spring; LF/LS = late fall + late spring; EF/LF = early fall + late fall; ES/LS = early spring + late

spring; All = early fall + late fall + early spring + late spring; TP = traditional program.

143

Figure 4. Mean snow mold severity per plot at Sentryworld Golf Course in Stevens Point, WI

during the springs of 2009 and 2010. Snow mold severity was visually assessed as percent area

of the plot affected. Dates were analyzed individually, and disease severity values were

subjected to analysis of variance and mean separations using the Waller-Duncan k-ratio t-test

(k=100). NTC = Nontreated control; LF = late fall; LS = late spring; LF/LS = late fall + late

spring; EF/LF = early fall + late fall; ES/LS = early spring + late spring; All = early fall + late

fall + early spring + late spring; TP = traditional program.

144

CHAPTER 5:

Resistance of creeping bentgrass cultivars to dollar spot and snow mold

145

ABSTRACT

Numerous creeping bentgrass (Agrostis stolonifera L.) cultivars with improved

characteristics have been released in the past decade. Some, such as Declaration and Memorial,

have shown resistance to dollar spot (Sclerotinia homoeocarpa F.T. Bennett) in university

research trials. Seven modern bentgrass cultivars were compared to Penncross for their

resistance to dollar spot and snow mold in Wisconsin from 2009-2012, and their potential ability

to reduce fungicide usage was determined. Of the eight cultivars tested, Declaration and

Memorial were the only cultivars to exhibit resistance to both dollar spot and Typhula blight

over the length of the study. A-1 exhibited partial resistance to dollar spot and LS-44 exhibited

partial resistance to gray snow mold. None of the cultivars exhibited enough resistance to

suppress gray snow mold or dollar spot to an acceptable level under no or reduced fungicide

usage. This suggests that significant reductions in fungicide usage cannot be achieved solely

through planting current disease-resistant bentgrass cultivars.

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1. INTRODUCTION

Creeping bentgrass (Agrostis stolonifera L.) has long been the preferred species of

turfgrass on most golf courses in temperate climates of the world. The bentgrass cultivar

‘Penncross’ was introduced in 1954 by Dr. Frank Musser at Penn State University and was the

first widely-used seeded type of creeping bentgrass, replacing many of the vegetatively-

propagated bentgrasses that had predominated since the turn of the century (Stier, 2006).

Despite its continued utility, Penncross bentgrass does provide challenges for the modern golf

course superintendent. Penncross can segregate into genetically-distinct clones, producing a

patchy or mottled look over time (Beard, 1973). Penncross is susceptible to thinning when

managed for modern-day putting green expectations, allowing for annual bluegrass (Poa annua)

encroachment (Samaranayake et al., 2008). Penncross is also susceptible to a number of

turfgrass diseases, namely dollar spot (Sclerotinia homoeocarpa F.T. Bennett), requiring

repeated fungicide usage to maintain acceptable quality (Bonos et al., 2006).

A number of bentgrass cultivars have been released in recent years with improved

characteristics, including increased shoot density and drought tolerance (Beard et al., 2001; Liu

and Huang, 2001; Stier and Hollman, 2003). A few cultivars, most notably ‘Declaration’ and

‘Memorial,’ have demonstrated partial resistance to Sclerotinia homoeocarpa, the causal agent

of dollar spot (Bonos et al., 2006). Bentgrass cultivars with improved dollar spot resistance

could potentially reduce fungicide requirements, saving thousands of dollars per year and lower

the environmental impact of golf course management. Yet, the upfront costs of a golf course

renovation can easily exceed $50,000 for the putting greens alone (Koch, personal

communication), and it’s unclear whether choosing a cultivar with disease resistance over

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another modern cultivar will lead to a reduction in fungicide usage substantial enough to justify

the costs of renovation.

The majority of disease resistance breeding efforts have gone towards developing

bentgrass resistance towards summer diseases such as dollar spot, brown patch (Rhizoctonia

solani), and anthracnose (Colletotrichum cereale) [Bonos et al., 2006; Settle and Tisserat, 2001].

For many golf courses in the upper Midwest, though, snow mold management is just as

important as any other turfgrass disease (Hsiang et al., 2001). Differences among bentgrass

cultivars with regards to Microdochium patch (Microdochium nivale) resistance have been

documented, but little information exists for Typhula blight (Typhula incarnata, T. ishikariensis)

(Baldwin, 2010). Without information regarding the level of resistance bentgrass cultivars have

to Typhula blight, golf course superintendents in climates where snow mold is prevalent cannot

make an informed decision about the proper bentgrass cultivar for their site.

Bentgrass cultivars that exhibit significant resistance to a variety of summer and winter

diseases can limit fungicide expenditures and provide a long term strategy towards sustainability

in golf turf management. The objective of this study was to evaluate eight bentgrass cultivars for

their resistance to dollar spot and snow mold, and to determine whether resistance could aid in

reducing fungicide usage.

2. EXPERIMENTAL DESIGN AND PLOT PREPARATION

Eight cultivars of creeping bentgrass were established during the summer of 2009 at the

OJ Noer Turfgrass Research and Education Facility (OJN) in Verona, WI in a randomized

complete block design with 4 replications. The eight cultivars tested were Penncross,

Declaration, Memorial, A-1, A-4, LS-44, Syn-96, and G-1. Individual plots measured 1.5 X 3 m

148

with four replications, and each cultivar was seeded at 48.38 kg ha-1

. The experimental area was

fumigated using dazomet (tetrahydro-3,5,-dimethyl-2H-1,3,5-thiadiazine-2-thione) applied as

Basamid (Certis USA, Columbia, MD) prior to seeding to kill viable annual bluegrass (Poa

annua) seeds. Cultivars were maintained at a fairway height of 1.25 cm and fertilized with

approximately 98.0 kg N ha-1

annually. The experimental area was evaluated for dollar spot and

snow mold resistance through the spring of 2012.

3. FUNIGICIDE APPLICATIONS AND DISEASE RATING

Pesticides were not applied to the experimental area during cultivar establishment or

during the fall of 2009. Monthly applications of propiconazole and chlorothalonil were made to

all plots during June, July, and August in 2010 and 2011 at the rates of 0.5 and 8.03 kg a.i. ha-1

,

respectively. This reduced rate was selected to allow for dollar spot development without the

risk of a total loss of the experimental area to disease. Fall fungicide applications were not made

in 2009, 2010, or 2011 in order to evaluate snow mold severity within each cultivar.

Snow mold severity was visually assessed once each spring as percent area of the plot

affected with snow mold. Dollar spot severity was assessed by counting individual foci per plot

biweekly throughout the summer, and the most severe disease rating from each year is presented

in figure 1. Mean disease severity and turfgrass quality were assessed separately by location and

year. Disease severity values were subjected to analysis of variance (ANOVA; PROC MIXED)

and means separated using Fisher’s protected LSD using PDMIX macro (Saxton, 1998) in SAS

(Version 9.1; SAS Institute, Cary, NC).

149

4. DOLLAR SPOT RESISTANCE

Overall, dollar spot severity was greater in 2011 than both 2010 and 2009 due to

prolonged periods of hot, humid weather (Figure 1). Differences in dollar spot severity were

observed between cultivars. Over the entire 3 year study, dollar spot severity was lowest for

Declaration, Memorial, and A-1 whereas dollar spot severity was greatest for A-4, Syn-96, and

G-2 (Table 1). Penncross generally had increased numbers of dollar spot foci when compared to

Declaration, Memorial, or A-1 but lower numbers when compared to A-4, Syn-96, or G-2.

These results suggest that the cultivars Declaration, Memorial, and A-1 show partial

resistance to the dollar spot pathogen when compared to Penncross and other modern creeping

bentgrass cultivars. Although partially resistant compared to Penncross, the number of dollar

spot foci per plot on the three ‘resistant’ cultivars still approached 50 in 2009 and 2010 and

exceeded 200 in 2011. This infection occurred despite monthly fungicide applications during the

summer. The severity of dollar spot observed during the summer months was not acceptable by

most golf course standards. The number of fungicide applications and amount of fungicide

active ingredient applied in this study was reduced compared to what many golf course

superintendents apply on their fairways during the summer months. If the reduced fungicide

program used in this study could not provide acceptable control of dollar spot, then it remains

doubtful that significant reductions in fungicide usage could be obtained solely through the use

of partially disease-resistant bentgrass cultivars in the Midwest.

5. SNOW MOLD RESISTANCE

Gray snow mold, caused by Typhula incarnata, was the only snow mold observed within

the experimental area in all 3 years. Overall, snow mold severity increased incrementally from

150

2010-2012 (Figure 2). Conditions were not optimal for snow mold development in the winter of

2011-2012, suggesting that the increase in disease severity in each year may be the result of

greater snow mold inoculum from the previous winter’s disease. Differences in snow mold

severity were observed between cultivars (Figure 3). Snow mold was most severe in Penncross,

A-1, A-4, and G-2 over the 3 year period, with disease severity averaging at or above 50% in

2011 and 2012. Declaration, Memorial, and LS-44 had the lowest snow mold severity over the 3

years, averaging approximately 10% disease in 2010 and between 20-40% in 2011 and 2012

(Table 2). This suggests that Declaration, Memorial, and LS-44 exhibit at least partial resistance

to Typhula incarnata infection.

On fairway turfgrass in the upper Midwest, snow mold severity above 5-10% would be

considered unacceptable by most golf course superintendents (Koch, personal communication).

Even under the lower disease pressure experienced in 2010, all three of the ‘resistant’ cultivars

could not provide an acceptable level of disease control. Fungicides were not applied to these

plots to control snow mold, so it remains unclear whether reduced rates of fungicides could be

applied to the partially-resistant cultivars to achieve acceptable snow mold control. Until future

research clarifies the impact of reduced fungicide applications on snow mold control on resistant

bentgrass cultivars, this research suggests that planting resistant bentgrass cultivars will not lead

to appreciable reductions in fungicide usage with regards to gray snow mold management.

6. CONCLUSION

New cultivars of creeping bentgrass released in the past decade have shown varying

levels of resistance to numerous turfgrass diseases. Declaration and Memorial were the only

cultivars to exhibit partial resistance to both dollar spot and gray snow mold in comparison to six

151

other cultivars tested, suggesting that the resistance mechanism is broad and effective against a

range of fungal pathogens. Despite the observed resistance, their efficacy was limited and did

not provide acceptable suppression of dollar spot and gray snow mold in Wisconsin. Thus,

seeding these particular resistant cultivars may not lead to appreciable reductions in fungicide

usage without implementation of other disease suppressive cultural practices.

LITERATURE CITED

Baldwin, C. B. 2010. Creeping bentgrass cultivar response to pink snow mold disease, 2009.

Plant Disease Management Reports 4: T017.

Beard, J. B. 1973. Turfgrass: Science and Culture. Prentice Hall, Englewood Cliffs, NJ. p. 78.

Beard, J. B., Croce, P., Mocioni, M., DeLuca, A., Volterrani, M. 2001. The comparative

competitive ability of thirteen Agrostis stolonifera cultivars to Poa annua. Intl. Turfgrass

Soc. Res. J. 9: 828-831.

Bonos, S. A., Clarke, B. B., Meyer, W. A. 2006. Breeding for disease resistance in the major

cool-season turfgrasses. Ann. Rev. Phytopath. 44: 213-214.



Liu, X., Huang, B. 2001. Seasonal changes and cultivar difference in turf quality,

photosynthesis, and respiration of creeping bentgrass. HortScience 36: 1131-1135.

Samaranayake, H., Lawson, T. J., Murphy, J. A. 2008. Traffic stress effects on bentgrass putting

green and fairway turf. Crop Sci. 48: 1193-1202.

152

Saxton, A.M. 1998. A macro for converting mean separation output to letter

groupings in Proc Mixed. In Proc. 23rd SAS Users Group Intl., SAS Institute,

Cary, NC: 1243-1246.

Settle, D., Fry, J., Tisserat, N. 2001. Dollar spot and brown patch fungicide management

strategies in four creeping bentgrass cultivars. Crop Sci. 41: 1190-1197.

Stier, J. C. 2006. A short history of creeping bentgrass. The Grass Roots. 35(1): 4-9.

Stier, J. C., Hollman, A. B. 2003. Cultivation and topdressing requirements for thatch

management in A and G bentgrasses and creeping bluegrass. HortScience 38:1227-1231.

153

TABLES AND FIGURES

Table 1. Mean number of dollar spot foci per plot from 2009 - 2011. Means followed by the

same letter do not significantly differ. LSD = 70.4.

Cultivar Dollar spot severitya

Penncross 202.17bc

Declaration 29.74d

Memorial 118.25d

A-1 184.83cd

A-4 228.67abc

LS-44 195.33c

Syn-98 265.83ab

G-2 283.42a

154

Table 2. Mean snow mold severity per plot from 2010 – 2012. Means followed by the same

letter do not significantly differ. LSD = 10.99.

Cultivar Snow Mold Severitya

Penncross 35.0abc

Declaration 22.25de

Memorial 18.92e

A-1 37.08ab

A-4 40.0ab

LS-44 24.17cde

Syn-98 30.17bcd

G-2 45.0a

155

Cultivar

Pennc

ross

Dec

lara

tion

Mem

orial

A-1 A-4

LS-4

4

Syn-9

6G-2

Do

llar

sp

ot

foci p

er

plo

t

0

100

200

300

400

500

600

700

9/29/2009

6/21/2010

8/11/2011

Figure 1. Mean number of dollar spot foci per cultivar on September 29, June 21, and August 11

in 2009, 2010, and 2011, respectively, at the OJ Noer Turfgrass Research Center in Verona, WI.

Error bars represent standard error for each cultivar at each rating date.

156

Figure 2. Mean snow mold severity per cultivar on March 18, April 7, and March 18 of 2010,

2011, and 2012, respectively, at the OJ Noer Turfgrass Research Center in Verona, WI. Error

bars represent standard error for each cultivar at each rating date.

Cultivar

Pennc

ross

Dec

lara

tion

Mem

orial

A-1 A-4

LS-4

4

Syn-9

6G-2

Typh

ula

blig

ht

se

ve

rity

(%

)

0

20

40

60

80

100

3/18/2010

4/7/2011

3/18/2012

157

Figure 3. Difference in gray snow mold severity between ‘Penncross’ creeping bentgrass and

‘Declaration’ creeping bentgrass on March 18, 2010 at the OJ Noer Turfgrass Research Facility

in Verona, WI.

158

CONCLUSION

159

The research presented here clearly demonstrates the impact of varying environmental

conditions on the activity and persistence of turfgrass fungicides. In a winter environment,

degradation of both iprodione and chlorothalonil was primarily affected by temperature, winter

rains, and snow melt. Increased temperature may have increased microbial metabolism of both

fungicides, while rainfall and snow melt may have removed fungicide residues through physical

removal or degraded the parent molecule through hydrolysis. Photodegradation did not have an

effect on the persistence of either fungicide. In a summer environment, higher temperatures led

to significantly increased rates of fungicide degradation. Plant and microbial metabolism may be

the primary factors influencing the degradation of iprodione and chlorothalonil, respectively, in a

summer environment. In addition, removal by mowing was shown to be a significant contributor

to the removal of fungicide from the turfgrass environment.

Strategies for reducing fungicide usage without sacrificing turfgrass quality were also

investigated. Alternative fungicide application timings in the spring well before symptom onset

delayed and reduced the overall severity of dollar spot, potentially eliminating the need for 1 to 2

fungicide applications per season. Fall fungicide applications did reduce dollar spot the

following season, but only to a minor degree. Modern cultivars of creeping bentgrass with

potential dollar spot resistance were tested for their ability to reduce fungicide applications.

While the cultivars ‘Declaration’ and ‘Memorial’ did reduce disease severity of both dollar spot

and Typhula blight, the level of reduction was not enough to eliminate or significantly reduce

fungicide applications for either disease.

The activity and persistence of fungicides applied to manage turfgrass diseases is an area

that has received attention. The continued reliance on fungicides for the management of many

turfgrass diseases makes further research in this area critical. Using the methods developed here,

160

a greater understanding of the interaction between fungicides and the numerous factors that make

up the turfgrass ecosystem can be explored. Research building upon the results obtained here

can investigate specific interactions between the microbial community and fungicides on the leaf

surface, the impact of plant metabolism on fungicide degradation, the activity of other fungicide

chemistries on the leaf surface, the activity of other pesticides such as herbicides and

insecticides, and many other possibilities. Eventually the knowledge obtained from these

research studies will enable turfgrass managers to make targeted fungicide applications based not

on recommendations from the manufacturer label, but on a variety of factors that include the

activity of the pathogen, the susceptibility of the host, the environmental conditions, and the

degree of fungicide remaining from previous applications. This will lead to more efficient

disease management without reducing turfgrass quality, and increase the sustainability of

turfgrass management for future generations.

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