PREEMERGENCE ACTIVITY OF CHLOROACETAMIDE HERBICIDES …

PREEMERGENCE ACTIVITY OF CHLOROACETAMIDE HERBICIDES ON A MULTIPLE

HERBICIDE-RESISTANT POPULATION OF WATERHEMP (AMARANTHUS

TUBERCULATUS)

BY

SETH ARTHUR STROM

THESIS

Submitted in partial fulfillment of the requirements

for the degree of Master of Science in Crop Sciences

in the Graduate College of the

University of Illinois at Urbana-Champaign, 2018

Urbana, Illinois

Master’s Committee:

Associate Professor Aaron G. Hager, Chair

Professor Dean E. Riechers, Co-Chair

Professor Adam S. Davis

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ABSTRACT

Chloroacetamide herbicides have been an integral part of preemergence (PRE) weed

management programs in corn and soybean since their discovery in the 1950’s. Today they are

applied either alone, or with other active ingredients in herbicide premixes. Known as ‘Old

Chemistries’, their importance is due to the excellent control of annual grasses and small-seeded

broadleaf weeds when applied PRE, and relatively high crop safety. Waterhemp [Amaranthus

tuberculatus (Moq.) Sauer] is a small-seeded, summer annual weed species native to the

Midwest. Waterhemp is dioecious with an ability to evolve resistance to herbicides from various

sites-of-action. This, paired with high reproductive output, prolonged emergence, genetic

diversity, and seed dormancy, has allowed waterhemp to become one of the most problematic

weeds in Midwestern agronomic cropping systems.

Waterhemp has displayed resistance to herbicides from six different site-of-action groups

including: acetolactate synthase (ALS) inhibitors, 5-enolpyruvyl-shikimate-3-phosphate (EPSPS)

inhibitors, protoporphyrinogen oxidase (PPO) inhibitors, synthetic auxins, Photosystem II

inhibitors (PSII), and 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors.

Chloroacetamide herbicides, however, have remained effective. During research on the first

HPPD-resistant population of waterhemp from Mclean County, IL (MCR), significantly less-

than-anticipated PRE control was reported with the chloroacetamide herbicide S-metolachlor.

Similar observations were made on a separate waterhemp population from Champaign County,

IL (CHR) with resistance to HPPD-, ALS-, PSII-, and PPO-inhibitors and 2,4-D. In both cases,

another active ingredient from the same class, acetochlor, remained effective. With such similar

observations on geographically separated waterhemp populations, field research began at the

CHR location in 2016 to investigate this reoccurring anomaly.

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Chapter 1 of this thesis includes a literature review of chloroacetamide herbicides

including their development, mode of action, selectivity, and the environmental interactions of a

specific active ingredient, S-metolachlor. Additionally, a section reviewing waterhemp biology

is included. Chapter 2 highlights field experiments conducted at the Champaign Co. site and

greenhouse dose-response experiments with acetochlor and S-metolachlor. Results from field

experiments demonstrated very poor control with each Group 15 herbicide except non-

encapsulated acetochlor, alachlor, and pyroxasulfone, which provided 75, 67, and 56% control,

respectively, 28 days after treatment (DAT). Greenhouse dose-response experiments with S-

metolachlor revealed a large difference in herbicide effective dose values between populations

with multiple herbicide-resistance, including resistance to HPPD-inhibitors and atrazine, and

sensitive populations. A 17.9 fold difference was documented between progeny of CHR (M6)

and a known sensitive population (WUS) in response to S-metolachlor 21 DAT. The difference

was calculated based on the herbicide dose required to reduce the number of surviving seedlings

by 50% (LD50), and S-metolachlor was not effective in controlling M6 at a field-use rate.

Acetochlor, however, was effective at controlling all populations at, or below, a field-use rate.

Chapter 3 describes growth chamber experiments to examine edaphic interactions as possible

causes of the decreased effectiveness of Group 15 herbicides in the field, although results were

inconclusive. Also included in Chapter 3 is a synopsis of experiments and their implications for

future research.

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ACKNOWLEDGEMENTS

First and foremost, I would like to thank my advisors Dr. Aaron Hager and Dr. Dean

Riechers for the opportunity to conduct research and pursue my Master’s degree in their

programs. Being co-advised has been a great experience and each has given me different

insights to the field of weed science. Coming in as a new graduate student, my research has been

full of trials and tribulations and their expertise has guided me through each scenario and has

helped me develop myself as an aspiring young scientist.

I would also like to thank my third committee member, Dr. Adam Davis, for his

statistical advice and patience with me as I continue to learn data management and statistical

analysis. This by far has been one of my greatest struggles, and Dr. Davis has always been

willing to share his knowledge of R programming. I would also like to thank Dr. Carolyn Butts-

Wilmsmeyer for assistance with SAS programming and the statistical analysis of my data

generated in the field. I am grateful for the opportunity to be a teaching assistant for Dr. Pat

Tranel. Thank you for having faith in me to run the classroom when you are away and allowing

me to be a part in inspiring the next generation of weed scientists.

I would like to acknowledge the herbicide evaluation group: Charlie Mitsdarfer, Lisa

Gonzini, and Doug Maxwell. They keep me on track, and their expertise in conducting field

research has been influential in the success of my experiments. It is truly a pleasure to work with

a team that cares about my research and is always eager to help in any way possible. I would

also like to thank the graduate students and lab members I have been fortunate to work alongside

which include: Lanae Ringler, Sarah O’Brien, Loren Goodrich, Olivia Obenland, Dr. Yousoon

Baek, and Dr. Rong Ma. Thank you for each of your contributions to my research and comic

relief that has made this portion of my graduate education a great experience. In addition, I

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would like to thank Brendan Alexander for his help at the field location and R programming

advice, along with the many undergraduate workers that have helped in the data collection

process. I understand it is not the most glorious aspect of research, but your help is truly

appreciated.

I would like to express my gratitude to Syngenta for funding my project and affording me

many opportunities throughout my education. The opportunity to visit the Vero Beach Research

Center is an experience I will never forget. I would especially like to thank Dave Thomas for his

continued interest in my project and the opportunity to conduct research at the Mclean County

site. In addition, I would like to thank Dr. Joe Wuerffel for his advice as I was struggling in the

greenhouse, and the entire VBRC research team. It has been a pleasure to work with a company

so interested in the science and producing quality products for growers around the world.

Finally, I would like to thank my family. At the end of the day, family comes first and

without them, I would not be here today. I would like to thank my parents Jeff and Victoria

Strom for raising me to be the person I am today. Although my dad is unfortunately not here

today, I know he has been watching over me the entire time and I strive to make him proud.

Overall, the support and encouragement from everyone has been tremendous and as one chapter

of my graduate education ends, I cannot wait for the new opportunities in the coming future.

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TABLE OF CONTENTS

CHAPTER 1: LITERATURE REVIEW....................................................................................1

1.1 Group 15 Herbicides: Development Timeline of Select Compounds..........................1

1.2 Group 15 Herbicides: What they control, how they control, and where they

inhibit...................................................................................................................................3

1.3 Group 15 Herbicides: Selectivity, Metabolism, and Implications for

Resistance............................................................................................................................5

1.4 S-metolachlor and the Environment..............................................................................7

1.5 Waterhemp Biology, Distribution, and Agronomic Importance.................................10

1.6 Research Objectives.....................................................................................................12

1.7 Literature Cited............................................................................................................15

CHAPTER 2: DIFFERENTIAL RESPONSE OF A MULTIPLE HERBICIDE-

RESISTANT WATERHEMP (AMARANTHUS TUBERCULATUS) POPULATION

TO CHLOROACETAMIDE HERBICIDES............................................................................25

2.1 Abstract........................................................................................................................25

2.2 Introduction..................................................................................................................26

2.3 Materials and Methods.................................................................................................29

2.4 Results and Discussion................................................................................................34

2.5 Source of Materials......................................................................................................43

2.6 Tables and Figures.......................................................................................................44


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CHAPTER 3: SOILLESS ASSAY TO CHARACTERIZE THE RESPONSE OF

MULTIPLE HERBICIDE-RESISTANT WATERHEMP (AMARANTHUS

TUBERCULATUS) TO CHLOROACETAMIDE HERBICIDES..........................................63

3.1 Abstract........................................................................................................................63

3.2 Introduction..................................................................................................................64

3.3 Materials and Methods.................................................................................................66

3.4 Results and Discussion................................................................................................69

3.5 Research Summary and Concluding Remarks.............................................................72

3.6 Source of Materials......................................................................................................79

3.7 Table and Figures.......................................................................................................80


APPENDIX A: SUMMARY DATA AND FIGURES FROM INITIAL

CHLOROACETAMIDE DOSE-RESPONSE EXPERIMENTS............................................87

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CHAPTER 1

LITERATURE REVIEW

1.1 Group 15 Herbicides: Development Timeline of Select Compounds

The development of Group 15 herbicides began in the early 1950s by Monsanto. It was

discovered in 1952 that certain α-chloroacetamide compounds provided excellent activity on

annual grasses and several broadleaf weed species. More importantly, these compounds were

safe in important crops such as corn and soybean. This was revolutionary, as farmers already

had an option for selectively controlling broadleaf weed species in corn (2,4-D) but grasses were

nearly unmanageable. By 1956, the first commercially produced α-chloroacetamide (CDAA)

was sold (Hamm 1974). The discovery of CDAA was exiting with Jaworski (1956) reporting,

“It will destroy giant foxtail and pigweed in either corn or soybean fields without injuring the

crop.”

Overall, CDAA had limited success. It was expensive, provided varying levels of control

depending on soil type, and caused skin irritation if contacted. This led Monsanto to further

develop this class of herbicides with formulation alterations and additions that improved

broadleaf activity and reduced skin irritation. Propachlor followed CDAA, but skin irritation

was not resolved. The issue was finally solved with the addition of an aniline group. Research

then switched to the α-chloroacetanilide compounds with alachlor being released in 1969 and

butachlor in 1971 for use in rice. These acetanilide compounds had a much broader spectrum of

activity, consistency across soil types, and no skin irritation (Hamm 1974). The α-

chloroacetanilide class has been a cornerstone segment of research and development conducted

by Monsanto, with acetochlor receiving EPA registration in 1994.

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Other companies also were investing in α-chloroacetanilide development. Ciba-Geigy

discovered the active ingredient metolachlor. Wide-scale production of this unique compound

commenced in 1978. It was sterically hindered with two chiral elements: a chiral axis and a

stereogenic center (Blaser and Spindler 1997). Due to these characteristics, metolachlor exists in

four stereoisomers (aSS; aRS; aSR; aRR) (Muller et al. 2001). It was discovered that the (1’S)-

diastereomers (aSS; aRS) were responsible for the majority of the herbicidal activity (Moser et

al. 1983). The difference in activity led to the search for enriched formulations of S-isomers.

After the innovation of an efficient iridium catalyst that could enantioselectively hydrogenate

imines, and years of optimization (Bader and Blaser 1997), large-scale production of S-

metolachlor (90% purity) began in 1996 with commercialization in the USA in 1997 (Blaser et

al. 1999).

Other Group 15 active ingredients have been discovered with the most recent being

pyroxasulfone. Pyroxasulfone belongs to the pyrazole family of herbicides and was discovered

by Kumia Chemical Industry Company and marketed in the U.S. by BASF. It was assumed to

have the same site of action (SOA) as the chloroacetamide herbicides due to the inhibition of

shoot growth and absence of effects on germination of sensitive seedlings (Tanetani et al. 2009).

Lack of incorporation of fatty acids into very long chain fatty acids initially proved the SOA

theory (Tanetani et al. 2009). Further research confirmed this by demonstrating the inhibition of

FAE1 (Tanetani et al. 2011), similar to observations made on the chloroacetamides (Böger

2003). Pyroxasulfone targets the same spectrum of weeds as the chloroacetamides, but controls

more broadleaf weed species. It also is active at much lower rates (g ha-1 versus kg ha-1) with

lower water solubility and less risk of decomposition when compared to other Group 15 active

ingredients due to being hydrolytically stable at all soil pH values (Nakatani et al. 2016).

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1.2 Group 15 Herbicides: What they control, how they control, and where they inhibit

Very-long-chain fatty acids (VLCFAs) are essential to plant function and consist of an

acyl carbon chain in excess of 18. VLCFAs are derived from 16 or 18 carbon atoms, and are

elongated through sequential additions of two carbon atoms in the endoplasmic reticulum by

elongase enzymes and malonyl-CoA. VLCFAs are diverse and vary in their degree of

unsaturation, function, and structure. They can be found in lipid seed reserves, signaling

molecules, and are main components of cellular membranes and cuticle waxes (Bach and Faure,

2010).

Group 15/K3 herbicides are old chemistries that are still important today for soil-residual

control of annual grass and small-seeded dicot weeds (Fuerst et al. 1987). Dating back to their

initial release in the 1950s (Hamm 1974), little was actually known about their mode of action

(MOA) until recently. Many observations have been made on plant processes effected by

chloroacetamides. Early reports indicated that cellular respiration was affected during

germination and ultimately must be connected to growth inhibition (Jaworski 1956).

Chloroacetamides could also interfere with gibberellic acid induced α-amylase production in

germinating seeds, resulting in inhibition of growth (Jaworski 1969). Protein synthesis is

inhibited by chloroacetamides (Duke et al. 1975; Mann et al. 1965) and Jaworski (1969)

reasoned that these herbicides use a variety of mechanisms that lead to death of sensitive plant

species.

Lipid synthesis and the formation of cuticle waxes were found to be inhibited by

chloroacetamides (Ebert 1982; Mann and Pu 1968). Studies starting at the University of

Konstanz (Weisshaar and Böger 1987) eventually led to the discovery of the target site and

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MOA. The first clue was a lack of formation of plasma membrane materials (Weisshaar and

Böger 1987). It was concluded that chloroacetamides inhibit the elongation of C16 or C18 long

chain fatty acids into VLCFAs at very low concentrations. This depletion of VLCFAs is what

causes the phytotoxic effects (Böger 2003). Plants that are deficient in VLCFAs have unstable

cells that subsequently lyse, which leads to the death of the affected plant (Matthes et al. 1998).

The MOA results from the chloroacetamides targeting the VLCFA synthase, encoded by

the FAE1 gene, in the VLCFA complex located within the endoplasmic reticulum (Böger 2003).

VLCFA synthase is a condensing enzyme and relies on a reactive cysteinyl sulfur (Ghanevati

and Jaworski 2002) to perform a nucleophilic attack on either the natural substrate or herbicide

(Böger et al. 2000; Götz and Böger 2004). This is an irreversible process, and once the

inhibiting herbicide binds it cannot be displaced (Götz and Böger 2004). The binding of the

herbicide at the VLCFA synthase consequently limits the 4-step process of C2 elongation of long

chain fatty acids to very long chain fatty acids through sequential incorporations of malonyl-CoA

(Böger 2003). Even though this is the primary site of action (SOA) and MOA, it is important to

note that many of the other findings in earlier research might be valid but could result from

secondary responses elicited by higher herbicide concentrations (Böger et al. 2000).

Chloroacetamides and related compounds inhibit the emerging seedling. Germination,

however, is not inhibited. They are effective at controlling annual grasses, small-seeded

broadleaves, and perennial nutsedge (Fuerst 1987). Sensitive species generally fail to emerge or

remain in an arrested state of growth after emerging (Deal and Hess 1980; Dhillon and Anderson

1972; Pillai et al. 1979). Grasses that emerge may exhibit distorted growth with characteristic

“buggy whipping” symptomology due to the leaves being unable to unroll naturally, while injury

to dicot species can resemble leaf cupping or crinkling (Fuerst 1987; Shaner 2014). These active

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ingredients are absorbed by both the roots and shoots of emerging seedlings (Pillai et al. 1979),

with shoot uptake being more important in grasses (Knake et al. 1967; Pillai et al 1979).

Inhibition of growth can occur to both parts of the affected plant (Pillai et al 1979). These

herbicides are capable of both xylem and phloem translocation, but xylem transport is

predominant (Armstrong et al. 1973; Chandler et al. 1974; Hamill and Penner 1973).

1.3 Group 15 Herbicides: Selectivity, Metabolism, and Implications for Resistance

The utility of the chloroacetamides lies in their ability to selectively control annual

grasses, small-seeded broadleaves, and nutsedge without injuring important crops such as corn,

soybean, and sorghum (Hamm 1974). Selectivity is achieved in tolerant crops through enhanced

herbicide metabolism (Jaworski 1969). Metabolism of the chloroacetamides is predominately

accomplished in phases II and III of plant metabolism (Gronwald 1989). Tolerant species are

more efficient at metabolizing the inhibitor through conjugation to glutathione (GSH) or

homoglutathione (hGSH) (Breaux 1987; Joblankai and Dutka 1985) and keep levels of the

herbicide below what is needed for phytotoxic effects (Jaworski 1969). Once conjugated, the

herbicide is no longer toxic (Shimabukuru et al 1978).

Conjugation to GSH or hGSH can occur enzymatically (catalyzed by glutathione S-

transferases (GSTs)) or non-enzymatically (Frear and Swanson 1970; Gronwald 1989). Higher

relative GST activities in tolerant crops versus sensitive weed species in response to

chloroacetamides allows tolerant crops to conjugate the herbicide to GSH or hGSH more

efficiently (Hatton et al. 1996). In certain grass species, such as corn, sorghum, and cereal

grains, enhanced tolerance to chloroacetamide herbicides can be achieved using a herbicide

safener (Davies and Casely 1999). Herbicide safeners induce herbicide detoxification by

6

inducing GSTs that catalyze the conjugation reactions (Hatzios and Hoagland 1989; Riechers et

al. 2005, 2010). GSTs are localized to shoot coleoptile tissues of emerging grasses (Riechers et

al. 2003). Coincidentally, this is where chloroacetamides predominately enter the plant (Knake

et al. 1967; Pillai et al 1979). This common location of herbicide entry and detoxifying catalyst

allows for rapid detoxification at or near the site of herbicide entry, which promotes crop safety

(Kreuz et al., 1989; Riechers et al., 2003, 2010).

Resistance to Group 15 herbicides is rare. Worldwide, only five species of grasses have

been documented as resistant. Only one of these grasses, Italian ryegrass (Lolium perenne ssp.

multiflorum), has been reported resistant in the United States (Heap 2017). This may partially be

explained by the nature of their application. Group 15 herbicides are soil-applied and have

residual activity. Residual activity allows Group 15 active ingredients to provide an extended

duration of weed control, which allows selection pressure to occur over a long period of time.

Levels of the herbicide will decrease over time, however, resulting in low selection intensity

when compared to most post emergence applications. In addition, if an emerging weed is

resistant, it must survive subsequent post emergence herbicides in order to pass resistance genes

to the next generation (Somerville et al. 2017).

Several mechanistic explanations of why resistance to the VLCFA inhibitors has been

slow to develop have been outlined (Böger 2003). First, the target site contains a highly reactive

center that is essential for both substrate and inhibitor binding. An alteration to this site would

result in a fitness penalty, and a functional enzyme specific to normal substrates is unlikely.

Second, detoxification of these herbicides requires an efficient GSH system that requires specific

GST isoforms that may not be present in weed species (Böger 2003; Sommer and Böger 1999;

Riechers 2003). Lastly, P450 monoxygenase-mediated detoxification is likely too slow, and a

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replacement of VLCFAs by greater levels of normal long chain fatty acids in higher plants is

unlikely (Böger 2003).

Resistance to VLCFA inhibitors in rigid ryegrass (Lolium rigidum) is an area of

continuing research. Resistance was achieved through cross-resistance or selection by herbicides

with other SOAs in an outdoor environment (Burnet et al. 1994; Busi and Powles 2016). In

general, resistance to VLCFA inhibitors occurs almost exclusively in multiple herbicide-resistant

biotypes (Heap 2017), and, in theory, a general mechanism of resistance, such as metabolism, is

likely involved (Burnet et al. 1994). Resistance to the VLCFA inhibitor pyroxasulfone was

decreased in a multiple herbicide-resistant population of rigid ryegrass following the application

of the insecticide and P450 inhibitor phorate (Busi et al. 2017). This was only a partial reversal,

and the results, along with results from a separate study, suggested that resistance to

pyroxasulfone is likely due to GSTs (Busi et al. 2017; Tanetani et al. 2013). Overall, the VLCFA

inhibitors have been a success story for over six decades, and only time will tell how long their

utility will be maintained as their use becomes more widespread in a world of decreasing

effective chemical weed control options.

1.4 S-metolachlor and the Environment

The primary objective following application of any herbicide is entry into targeted plant

species. Along with plant uptake, soil-applied herbicides can be lost through volatilization,

degradation (chemical, microbial, and photo), movement in surface water, and leaching to

groundwater (Chesters et al. 1989). S-metolachlor is a soil-applied herbicide with residual

activity and due to its widespread use, it is important to understand how S-metolachlor interacts

in the environment.

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If manual incorporation or rainfall does not occur soon after application, S-metolachlor

will remain on the soil surface. This allows photodegradation to take place and is especially a

problem during periods of drought (Shaner 2014). Once in the soil, S-metolachlor is low-to-

moderately adsorbed to soil particles (Shaner 2014). Sorption generally increases as soil organic

matter or clay content increases, making the herbicide less available for plant uptake (Shaner et

al. 2006, Wu et al. 2011). Factors such as soil cation exchange capacity (CEC) positively

correlate to the adsorption of S-metolachlor (Baran and Gourcy 2013; Rice et al. 2002), while the

opposite is true for pH and calcium carbonate levels (Baran and Gourcy 2013).

Many of the factors that influence sorption also influence the biological degradation of S-

metolachlor. In the soil, microbial degradation is a major contributor to the break down or

mineralization of metolachlor and S-metolachlor (Ma et al. 2006; Zemolin et al. 2014). Some

species can even use metolachlor as their sole carbon source (Sanyal and Kulshrestha 1999). In

addition, repeated use of metolachlor can condition the microbial community and lead to

enhanced degradation (Baily and Coffey 1986; Sanyal and Kulshrestha 1999), similar to

observations made with atrazine (Shaner and Henry 2007). Like sorption, degradation is

increased in soils with high levels of organic matter, leading to decreased herbicide persistence

(Rice et al. 2002; Shaner et al. 2006). Degradation also increases as soil temperature and

moisture increases (Long et al. 2014; Rice et al. 2002). A larger microbial community in high

organic matter surface soils could explain this observation (Rice et al. 2002; Wu et al. 2011). As

soil depth increases, S-metolachlor sorption decreases while the persistence increases (Accinelli

et al. 2001; Bedmar et al. 2011). This is due to subsurface soils having decreased organic matter

with depth (Alletto et al. 2011) and different microbial communities than surface soils (Federle

et al. 1986).

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Transport away from the application zone through runoff, volatilization, or leaching are

other ways in which S-metolachlor can move. Runoff is the movement of the herbicide from the

soil in rain or irrigation water (Wu et al. 1983). This process is thought to be the leading

contributor to surface water contamination (Krutz et al. 2005) with chloroacetamide herbicides

(Scribner et al. 2000). Even with the inherent chemical properties of high water solubility and

low-to-moderate sorption, losses of S-metolachlor to leaching is generally minor (Shaner 2014).

The herbicide can still move, however, especially once the herbicide moves below the surface

soil horizon (Bedmar et al. 2011). Chloroacetamide herbicides, including metolachlor, are

frequently detected in groundwater (Bedmar et al. 2011). Groundwater contamination is

troublesome because it does not have the same biological cleansing mechanisms as surface water

(McCarty et al. 1981). In general, the greater the amount of rainfall, the greater probability S-

metolachlor will leach and potentially reach groundwater (Inoue et al. 2010; Zemolin et al.

2014).

Volatilization is the movement of a herbicide into the atmosphere from the soil surface or

plant tissues in gaseous form (Bedos et al., 2002). S-metolachlor has a relatively low Henry’s

Law constant (2.4 x 108 atm m3/mole at 25°C) and vapor pressure (1.73 x 10-3 Pa at 20°C) which

afford the molecule low volatility (Shaner 2014). Volatilization of metolachlor has been studied

and the process occurs under certain environmental conditions that depend on meteorological,

chemical, and soil properties (Prueger et al. 2005). In general, volatilization of metolachlor is

more frequent in warm soils with high moisture contents (Gish et al. 2009; Prueger et al. 2005).

Dry soils are not conducive to volatilization of metolachlor (Gish et al. 2009; Prueger et al.

2005), which may be due to a greater affinity of the herbicide to adsorb to soil colloids and the

requirement of the herbicide to desorb before entering the atmosphere (Prueger et al. 2005). The

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greatest losses of metolachlor occur during daylight hours and losses can range from 5–63% of

the herbicide applied (Gish et al. 2011; Prueger et al. 2005). Overall, loss of metolachlor through

volatilization is greater than through surface runoff (Gish et al. 2011).

1.5 Waterhemp Biology, Distribution, and Agronomic Importance

Waterhemp [(Amaranthus tuberculatus (Moq) Sauer] is a small-seeded, summer annual

broadleaf weed species. It is native to the Midwestern United States and is one of the ten

dioecious Amaranthus species unique to North America (Sauer 1955, 1957). Over time it has

spread across much of the continent, overlapping with other species belonging to the

Amaranthaceae family. Naturally, waterhemp occurred in unstable environments such as

lakeshores and streambanks, which allows it to excel in agronomic fields frequently disturbed by

man. This is due to its ability to complete its lifecycle at any size given the required photoperiod

(Sauer 1957).

Waterhemp can be distinguished from other Amaranthus species by its generally glabrous

stems and oblong to lanceolate leaves that measure 2–10 cm long and 1–3 cm wide with petioles

shorter than the leaves (Sauer 1955). It is a morphologically diverse species; stem color can

range from shades of green to red, and plant shape can range from prostrate to erect. A vigorous

grower, waterhemp can easily reach heights over two meters tall (Horak and Loughin 2000;

Sauer 1955). Waterhemp has male staminate and female pistillate flowers on separate plants

(Murray 1940; Sauer 1955). The plant generates inflorescences that arise from the apical

meristem and tips of branches that can range from 3–35 cm (Horak et al. 1994; Sauer 1955;

Steckel 2007). Female plants are prolific seed producers and have the capability to produce up

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to 1x106 seeds that are viable as early as nine days after pollination (Bell et al. 2010; Hartzler et

al. 2004; Sellers et al. 2003; Steckel et al. 2003).

Waterhemp seeds are small (1.0–1.5 mm) and emergence is greater in no tillage systems

where seeds remain closer to the soil surface (Sauer 1955; Steckel et al. 2007). The absolute

number of seeds combined with seed dormancy allows waterhemp to persist in the soil seed bank

and germinate in several emergence events throughout the growing season (Buhler et al. 2001;

Buhler and Hartzler 2001; Hartzler et al. 1999). Extended emergence creates a problem for

growers as soil-applied residual herbicides may not provide an adequate duration of control and

plants may emerge after foliar-applied herbicides (Hartzler et al. 1999). The use of sequential

applications of residual herbicides in combination with foliar treatments is necessary along with

non-chemical practices in order to prevent female plants from surviving and further contributing

to the soil seed bank (Steckel et al. 2002)

Waterhemp also challenges growers through the evolution of herbicide resistance. The

natural obligation to outcross provides the species with a high amount of genetic variability. A

single female plant may be pollinated by multiple males and combine genetic information (Hager

et al. 1997). Waterhemp can also cross among other monecious and dioecious Amaranthus

species (Murray 1940). Sharing genetic information through outcrossing allows herbicide

resistance genes to diffuse among geographically separated populations. Currently waterhemp

has developed resistance to herbicides from six sites of action (SOA), with multiple herbicide-

resistance increasing in frequency (Heap 2017). To date, populations with multiple resistance to

three, four, and five SOAs within a single plant have been documented (Bell et al. 2013; Evans

2016; Patzoldt et al. 2005).

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All of the traits that make waterhemp a successful weed make it troublesome for growers.

Waterhemp is one of the most problematic weeds for soybean producers and has been reported to

reduce yield up to 43 % (Hager et al. 2002). It is also a problem in corn especially early in the

season. The greatest yield losses are documented if competition between waterhemp and corn is

allowed before, and up to, the V6 stage of growth (Steckel and Sprague 2004) making early-

season control important. Waterhemp will undoubtedly continue to be a problem for farmers in

the future. As populations evolve resistances to multiple SOAs, an integrated approach utilizing

a variety of best management practices, including nonchemical options (Hager et al. 1997) and

applying multiple effective SOAs per season (Evans et al. 2016), will be essential in controlling

the species and maintaining optimum yields (Hager et al. 1997).

1.6 Research Objectives

The chloroacetamide herbicides have been a long-term success story. Developed over 60

years ago (Hamm 1974), they remain an effective tool for weed control in modern agriculture.

To date, only five species of grasses worldwide have developed resistance, and resistance in a

dicot species has yet to be reported (Heap 2017). Their mode of action was a mystery until

researchers at the University of Konstanz were finally able to conclude that the herbicides inhibit

the elongation of long-chain fatty acids into VLCFAs (Böger 2003). This development gave rise

to the term VLCFA inhibitors when referencing this class of herbicides.

In the Midwest, arguably the most important weeds to control include waterhemp

(Amaranthus tuberculatus) and Palmer amaranth (Amaranthus palmeri). The VLCFA inhibitors

or Group 15 herbicides are an essential component in integrated management systems to combat

these species due to their effective preemergence (PRE) control (Loux et al. 2017; Shaner 2014).

13

During research conducted in Mclean County, IL on the first HPPD-inhibitor resistant population

of waterhemp (MCR), PRE control with the VLCFA-inhibitor S-metolachlor was less than

traditionally expected (Hausman et al. 2013). A similar observation was made on a

geographically separated population of waterhemp from Champaign County, IL (CHR) (Evans

2016). Both populations are multiple herbicide-resistant, including resistance to HPPD-

inhibitors and atrazine, and in each scenario another VLCFA-inhibitor, acetochlor, remained

effective (Evans 2016; Hausman 2012; Hausman et al. 2013).

Chapter 2 describes field and greenhouse experiments conducted in 2016 and 2017.

Experiments were conducted to investigate previous observations made by Evans (2016) at the

CHR location. Experiments included a comparison study to identify the range of activity with

various Group 15 active ingredients and a rate titration study to compare three Group 15 active

ingredients at increasing rates. Greenhouse experiments included dose-response studies to

compare a resistant-by-resistant (RxR) cross from CHR (M6) to a derivative of the MCR

population (NH40) and two HPPD-sensitive populations (ACR, WUS). The chloroacetamide

herbicides, acetochlor and S-metolachlor, were applied PRE at increasing rates on a base 3.16

logarithmic scale.

Chapter 3 highlights experiments conducted in the growth chamber to compare M6 to

several waterhemp populations (WUS, ACR, and NH40) in the absence of soil. Included is an

experiment that compared radicle growth for three days following the application of both S-

metolachlor and acetochlor in agarose. Results were not as anticipated, and also included is a

brief explanation of what might have occurred. Chapter 3 concludes with the importance of this

research and the objectives of future Group 15 herbicide research within the Weed Science group

14

at the University of Illinois. Lastly, Appendix A includes summary data from initial dose-

responses of M6 and WUS in response to PRE applied acetochlor and S-metolachlor.

15

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25

CHAPTER 2

DIFFERENTIAL RESPONSE OF A MULTIPLE HERBICIDE-RESISTANT

WATERHEMP (AMARANTHUS TUBERCULATUS) POPULATION TO

CHLOROACETAMIDE HERBICIDES

2.1 Abstract

Field experiments were conducted in 2016 and 2017 at a site in Champaign County, IL

containing a population of waterhemp (Amaranthus tuberculatus (Moq.) Sauer) (CHR)

previously characterized resistant to 4-hydroxyphenylpyruvate dioxygenase (HPPD)-,

photosystem II (PSII)-, acetolactate synthase (ALS)-, and protoporphyrinogen oxidase-inhibiting

herbicides and 2,4-D. Two field experiments, including a comparison of active ingredients at

labeled use rates and a rate titration experiment, were designed to investigate previous

observations regarding the efficacy of Group 15 herbicides. Waterhemp density and control

were evaluated at 28 and 42 d after treatment (DAT). Among active ingredients, non-

encapsulated acetochlor, alachlor, and pyroxasulfone provided the greatest control of CHR (56–

75%) at 28 DAT while metolachlor, S-metolachlor, dimethenamid-P, and encapsulated

acetochlor provided less than 27% control. In the rate titration experiment, non-encapsulated

acetochlor controlled CHR more than equivalent rates of S-metolachlor. Subsequent dose-

response experiments with S-metolachlor and acetochlor preemergence (PRE) were conducted in

the greenhouse and included three multiple-resistant waterhemp populations: M6 (progeny from

CHR), NH40 (progeny obtained from Mclean Co., IL), and ACR (Adams Co., IL), in

comparison with a known sensitive population (WUS). Both M6 and NH40 contain resistances

to HPPD-, PSII-, and ALS-inhibitors and demonstrated higher survival rates (LD50) to S-

metolachlor and acetochlor than ACR and WUS. Based on biomass reduction (GR50), resistant-

26

to-sensitive (R/S) ratios were 7.5 and 12.9 with S-metolachlor for M6 and NH40, respectively,

and with acetochlor were 6.1 and 6.8 for M6 and NH40, respectively. Complete control of all

populations was achieved at, or below, a field use rate of acetochlor. Field studies demonstrated

CHR is not controlled by various Group 15 herbicides. Greenhouse experiments supported this

finding and indicate that both multiple herbicide-resistant populations from Illinois with

resistance to HPPD- and PSII-inhibitors demonstrated reduced sensitivity to Group 15

herbicides, with S-metolachlor ineffective at a field use rate.

2.2 Introduction

Chloroacetamide herbicides have been utilized for preemergence (PRE) control of grass

and small-seeded dicot weeds since their discovery and commercialization in the 1950s (Hamm

1974). Active ingredients from this family belong to the Group 15 class of herbicides and

control sensitive species by inhibiting the very-long-chain fatty acid (VLCFA) elongase complex

(Böger 2003). Inhibition of the VLCFA elongase results in depletion of very-long-chain fatty

acids (Böger 2003), which consist of acyl chains in excess of eighteen carbons (Bach and Faure

2010). This leads to gradual depletion of lipids needed to form cellular membranes and cuticle

waxes (Böger 2003). Plants deficient in VLCFAs have unstable cells that subsequently become

leaky, leading to death of the affected seedling (Matthes et al. 1998). Sensitive dicot weed

seedlings either fail to emerge or remain in an arrested state of growth soon after cotyledon

expansion (Deal and Hess 1980; Dhillon and Anderson 1972; Fuerst 1987; Pillai et al. 1979).

Waterhemp (Amaranthus tuberculatus (moq.) J. D. Sauer) (Sauer 1955) a small-seeded,

summer-annual weed species, is controlled by most Group 15 herbicides (Loux et al. 2017),

which is important since waterhemp is one of the most problematic weed species for Midwest

27

corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) growers. The species is capable of

producing thousands of seeds per female plant under less than optimal conditions (Steckel et al.

2003) that can be viable as early as nine days after pollination (Bell and Tranel 2010). These

seeds contain high levels of dormancy and seedlings emerge continually throughout the growing

season (Buhler and Hartzler 2001; Harzler et al. 1999). High reproductive output and prolonged

emergence make residual chemical control essential for waterhemp management (Steckel et al.

2002).

More troublesome is the inherent ability of waterhemp to evolve resistance to herbicides

from various site-of-action (SOA) groups. Waterhemp is dioecious and an obligate outcrossing

species (Murray 1940; Sauer 1955), which increases intraspecific genetic variability compared

with monoecious Amaranthus species. This high degree of variability allows weediness traits,

including herbicide resistance, to be spread among and within populations. To date, waterhemp

is resistant to herbicides from six SOAs, including herbicides that inhibit 4-

hydroxyphenylpyruvate dioxygenase (HPPD), photosystem II, acetolactate synthase (ALS),

protoporphyrinogen oxidase (PPO), and 5-enolpyruvylskikimate-3-phosphate synthase (EPSPs)

and the synthetic auxin 2,4-D (Heap 2017). In addition, waterhemp is able to stack herbicide

resistances with populations containing individual plants resistant to herbicides across three,

four, and five SOAs reported (Bell et al. 2013; Evans 2016; Patzoldt et al. 2005).

The biology of waterhemp makes it well suited for competition with summer annual

crops such as corn, soybean, and sorghum (Sorghum bicolor (L.) Moench) (Steckel 2007). In

corn, the greatest yield losses are documented if competition occurs up to the V6 growth stage,

with the potential for over 50% yield loss (Steckel and Sprague 2004). In total, 74% yield loss in

corn is possible if season-long competition is allowed (Steckel and Sprague 2004). Waterhemp

28

interference can cause over 40% yield reduction if allowed to compete with soybean (Hager et al.

2002). As the frequency of populations with resistance to herbicides from multiple SOAs

increases, integrated management strategies will be essential for control (Hager 1997).

Incorporating multiple effective SOAs each season is a strategy to reduce the frequency of

resistant plants that survive and further contribute to the soil seedbank (Evans et al. 2016).

Group 15 herbicides are labeled for use in many crops and remain an effective way to

incorporate an additional SOA into integrated management programs.

Resistance to Group 15 herbicides is a relatively rare occurrence. To date, only five

species of grasses worldwide are resistant to herbicides from this class, with resistance in dicot

weed species yet to be documented (Heap 2017). The low level of resistance to these PRE

herbicides could be explained by naturally less intense selection pressure and the inability of

surviving weeds to overcome subsequent postemergence (POST) herbicides (Somerville et al.

2017). Mutations to the target site of chloroacetamides are unlikely, as any change in the target

site would alter the ability of normal substrates to bind (due to competitive inhibition kinetics)

and, more likely, multiple enzymatic detoxification processes must align in order to confer

resistance (Böger 2003). In nearly all cases, resistance to Group 15 herbicides occurs in multiple

herbicide-resistant populations potentially through cross-resistance mechanisms, or indirect

selection through the use of herbicides from other SOAs (Burnet et al. 1994).

Research results from a population of waterhemp resistant to HPPD-inhibiting herbicides

in Mclean County, IL (Hausman et al. 2011) indicated that S-metolachlor provided significantly

less PRE control than anticipated (Hausman et al. 2013). This population (designated MCR) was

subsequently characterized as resistant to HPPD-, ALS-, and PSII-inhibiting herbicides

(Hausman et al. 2011; Hausman et al. 2013; Hausman et al. 2016). During research conducted

29

on a separate population from Champaign County, IL with resistances to HPPD-, ALS-, PSII-,

and PPO-inhibitors and 2,4-D (designated CHR), similar observations in regards to less-than-

expected control were made with S-metolachlor (Evans 2016). In both cases, another herbicide

from the same class, acetochlor, remained effective (Evans 2016; Hausman et al. 2013). Based

on both occurrences and similarities between populations, experiments were designed to explore

the reoccurring anomaly of PRE control with acetochlor and S-metolachlor. The objectives of

this research were to investigate the CHR site to better characterize the response of the multiple

herbicide-resistant waterhemp population to Group 15 herbicides, as well as specifically compare

acetochlor and S-metolachlor at different rates. Greenhouse experiments were subsequently

initiated to compare CHR to other populations, including a derivative from the MCR population

where the initial field observations had been made (Hausman et al. 2013).

2.3 Materials and Methods

2.3.1 Responses of a Multiple Herbicide-Resistant Waterhemp Population to

Chloroacetamide Herbicides under Field Conditions

2.3.1.1 General Field Methods

Field experiments were conducted in 2016–2017 at the location where the CHR

waterhemp population had been characterized as resistant to HPPD-, PPO-, PSII-, and ALS-

inhibiting herbicides plus the synthetic auxin 2, 4-D (Evans 2016). The soil at the site is a

Flanagan silt loam (fine, smectitic, mesic Aquic Argiudolls) with a pH of 5.5 and 4.8% organic

matter. The soil was tilled prior to herbicide application to control existing vegitation and

experiments were established in nonplanted stale-seedbeds. Individual plots measured 3 by 7.6

m and were arranged in a randomized complete block design with four replications in 2016 and

30

three replications in 2017. Cumulative precipitation during field experiments in 2016–2017 is

presented in Table 2.1.

Two field experiments included a Group 15 herbicide comparison and a herbicide rate

titration. Eight commercially available Group 15 herbicides were selected and compared at 1X

doses based on manufacturers’ labeled recommendations for the soil type (Table 2.2) for the

herbicide comparison experiment. The rate titration experiment included three Group 15

herbicides (non-encapsulated acetochlor, S-metolachlor, and pyroxasulfone) each applied at ½, 1,

2, and 4X doses based on the 1X manufacturer recommended rate (Table 2.2). Treatments were

applied May 23, 2016, and June 14, 2017 with a pressurized CO2 backpack sprayer calibrated to

deliver 187 L ha-1 at 276 kPa with a 3-m boom consisting of six AI110025VS nozzles1 spaced 51

cm apart.

Visual ratings of percent waterhemp control were recorded 28 and 42 d after treatment

(DAT) using a scale of 0 (no control) to 100% (complete control). Ratings considered

waterhemp injury, biomass reduction, and emergence compared with a nontreated control.

Waterhemp density was recorded within two 0.25 m2 quadrats 28 and 42 DAT. Quadrats were

randomly placed in the center of each plot and counts were taken within the same area both

times. Waterhemp biomass was harvested from each quadrat 42 DAT, samples combined and

dried in a forced air dryer at 65°C, and dry biomass recorded.

2.3.1.2 Statistical Analysis

Statistical analysis was conducted with SAS 9.42. Biomass, density, and control ratings

were analyzed by ANOVA in PROC MIXED. Waterhemp density measurements were analyzed

as a repeated measure. For the Group 15 herbicide comparison study, treatment was considered

31

a fixed effect, while in the rate titration study, treatment, rate, and their interactions were

considered fixed effects. Year and block within year were considered random effects in both

experiments. Initial analysis revealed a significant treatment by DAT interaction for waterhemp

density in the herbicide comparison study. Mean estimates were separated by LSD using the

SAS macro %pdmix800 (Saxton 1998) with α=0.05. The assumption of normally distributed

residuals was reviewed with PROC UNIVARIATE and homogeneous variance was verified with

PROC GLM. Density values were subject to a square root transformation to meet assumptions,

and back-transformed data are presented as plants m-2.

2.3.2 Acetochlor and S-metolachlor Dose-Response Experiments under Greenhouse

Conditions

2.3.2.1 Waterhemp Populations

Four waterhemp populations were selected to characterize their response to acetochlor

and S-metolachlor. M6 is the progeny of CHR resistant x resistant (R x R) greenhouse crosses.

A previously confirmed HPPD- and atrazine-resistant population (NH40) (Hausman 2012) was

also included for comparison with M6 (Evans 2016). Two known HPPD-sensitive populations

(ACR, WUS) were included to calculate R/S ratios. ACR is resistant ALS-, s-triazine, and PPO-

inhibiting POST herbicides (Patzoldt et al. 2005) while WUS is not resistant to any herbicide.

All seeds were stratified according to methods outlined by Bell et al. (2013) and stored at 4°C for

at least 20 days prior to experiment initiation to improve germination.

32

2.3.2.2 Plant Culture

Plastic 1801 cell-pack inserts (384 cm3 per cell) were filled halfway with growth medium

(1:1:1 mixture of soil, peat, and sand, with a pH of 6.4 and 3.5% organic matter) and slow-

release fertilizer3 was added. Each cell was then filled to the top, lightly tamped, and then

soaked in water for 12 hr to provide a uniformly moist seedbed. Fifteen seeds from each

population were sown on the soil surface in a 3 by 5 grid with 1 cm between each of the outside

rows and the side of the insert. After sowing, 10 mL of the same growth medium was passed

through a 3.5 mm sieve and spread evenly across the surface. Plants were supplied weekly with

water-soluble fertilizer4 and greenhouse conditions were maintained at 28/22°C day/night with a

16-hr photoperiod. Natural sunlight was supplemented with mercury halide lamps to provide

800 µmol m-2 s-1 photon flux at the soil surface.

2.3.2.3 Herbicide Application

Acetochlor and S-metolachlor were applied PRE at increasing rates on a base 3.16

logarithmic scale. Each population was treated with S-metolachlor at rates ranging 8.4 to 8390 g

ha-1 or acetochlor at rates ranging from 2.5 to 2530 g ha-1. Herbicides were applied utilizing a

compressed air research sprayer5 fitted with a single 80015EVS nozzle1 46 cm above the medium

surface and calibrated to deliver 187 L ha-1 at 275 kPa. After herbicide application, a method

modified from Busi and Powles (2016) was used to add an additional 25 mL of sieved growth

medium on top of the treated medium to simulate mechanical incorporation of the herbicide.

Pots were then returned to the greenhouse beneath an overhead misting system. The mister was

equipped with 0.4 L per minute nozzles6 and programmed to cycle three times daily in order to

maintain adequate soil moisture.

33

2.3.2.4 Data Collection and Statistical Analysis

In all experiments, each treatment by population combination consisted of three

replications. Dose-response experiments to acetochlor and S-metolachlor were conducted

simultaneously and repeated twice. At 21 DAT, surviving seedlings were counted and

aboveground biomass was harvested. Harvested plants were placed in a forced air dryer set at

65°C for seven days and dry biomass was recorded. Statistical analysis was performed using R

software 3.4.2. Pooled biomass and survival data were then analyzed using non-linear regression

in the ‘drc’ package in R (Knezevic et al. 2007). Data derived from plant population effects

within acetochlor and S-metolachlor herbicide treatments were analyzed separately. The logistic

dose-response function was fitted utilizing the following equation:

𝑦 = 𝑐 +𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[log(𝑥)−log(𝐿𝐷50/𝐺𝑅50)]} [1]

The logistic function consists of four-parameters: b is the slope of the curve, c is the

lower asymptote, d is the upper asymptote, and LD50/GR50 is the 50% reduction in seedling

survival and plant biomass, respectively. Initially LD50 and GR50 values were calculated for each

individual experimental run. Effective dose values were then analyzed by ANOVA via a general

linear mixed effects model in the ‘nlme’ package in R to test the main effects of treatment,

population, and their interactions. Experiment run was considered a random effect in order to

test the significance of main effects across both experimental runs.

34

2.4 Results and Discussion

2.4.1 Responses of a Multiple Herbicide-Resistant Waterhemp Population to

Chloroacetamide Herbicides under Field Conditions

2.4.1.1 Group 15 Herbicide Comparison

Waterhemp control was 75% or less 28 DAT for all herbicides (Table 2.3). Non-

encapsulated acetochlor, alachlor, and pyroxasulfone provided the greatest control of the CHR

population, providing 75, 67, and 56% control, respectively. Control did not exceed 27% for all

other treatments. In addition, non-encapsulated acetochlor, alachlor, and pyroxasulfone provided

the greatest density reduction 28 DAT (12, 21, and 34 plants m-2, respectively) which

corresponds with visual estimations of control. Waterhemp densities among other treatments

were not different than nontreated plots.

No treatment exceeded 42% control 42 DAT (Table 2.3). Control with non-encapsulated

acetochlor was 42%, while alachlor and pyroxasulfone provided 31 and 21% control,

respectively. All other treatments provided less than 10% control. Plots treated with non-

encapsulated acetochlor, alachlor, and pyroxasulfone provided the greatest density reduction 42

DAT (14, 26, and 36 plants m-2, respectively), similar to results 28 DAT. Waterhemp densities

among other treatments were not different than nontreated plots. Only two treatments (non-

encapsulated acetochlor and alachlor) reduced biomass more than the nontreated control 42

DAT. Biomass from plots treated with non-encapsulated acetochlor and alachlor was 135 and

241 g, respectively.

The divergence in control of CHR between non-encapsulated acetochlor and

encapsulated acetochlor could be due to the extended release characteristics of the encapsulated

formulation. Initially, emerging seedlings in plots treated with encapsulated acetochlor were

35

likely exposed to less of the active herbicide than those in plots treated with non-encapsulated

acetochlor, resulting in less control and higher plant densities 28 and 42 DAT. Pyroxasulfone is

a pyrazole and was included in experiments due to having the same SOA and target weed

spectrum as chloroacetamide herbicides (Nakatani et al. 2016; Tanetani et al. 2011; Tanetani et

al. 2009).

2.4.1.2 Group 15 Rate Titration

Non-encapsulated acetochlor provided the greater control of CHR 28 DAT when

compared to 0.5 or 1X rates of pyroxasulfone or any rate of S-metolachlor (Table 2.4). A 1X

rate of non-encapsulated acetochlor controlled CHR 67%, slightly less than control reported for

the comparison study. The treatments providing the highest levels of control were non-

encapsulated acetochlor at 2X (85%) and 4X (94%) rates and pyroxasulfone at 2X (63%) and 4X

(74%) rates. S-metolachlor, regardless of rate, did not provide greater than 45% control of CHR.

Waterhemp density at 28 DAT is presented in Figure 2.1. In general, waterhemp density

(plants m-2) decreased as herbicide rate increased. Densities in plots treated with non-

encapsulated acetochlor were 4–73 plants m-2. Pyroxasulfone-treated plots had densities ranging

from 32–117 plants m-2 and plots treated with S-metolachlor had plant densities ranging from

52–204 plants m-2. Selected 1 degree of freedom contrasts between increasing rates of non-

encapsulated acetochlor and a 4X rate of S-metolachlor are presented (Table 2.5). Waterhemp

densities in plots treated with 0.5, 1, and 2X rates of non-encapsulated acetochlor were not

significantly different from plots treated with a 4X rate of S-metolachlor 28 DAT.

All treatments, regardless of rate, provided less control of the CHR population by 42

DAT (Table 2.4). Overall the highest levels of control were achieved with non-encapsulated

36

acetochlor or pyroxasulfone at 2X and 4X rates. S-metolachlor at a 4X rate provided 23%

control 42 DAT, and all other rates provided less than 10% control.

Waterhemp density at 42 DAT is presented in Figure 2.2. In general, waterhemp density

(plants m-2) decreased as herbicide rate increased. Densities in plots treated with non-

encapsulated acetochlor were 7–71 plants m-2. Pyroxasulfone-treated plots had densities ranging

from 31–118 plants m-2 and plots treated with S-metolachlor had plant densities ranging from

56–137 plants m-2. Selected 1 degree of freedom contrasts between increasing rates of non-

encapsulated acetochlor and a 4X rate of S-metolachlor are presented (Table 2.5). Waterhemp

densities in plots treated with 0.5, 1, and 2X rates of non-encapsulated acetochlor were not

significantly different from plots treated with a 4X rate of S-metolachlor 42 DAT.

Dry biomass (g m-2) 42 DAT is presented in Figure 2.3. In all treatments, biomass

decreased in response to 1–4X rates of all herbicide treatments. Biomass from plots treated with

non-encapsulated acetochlor ranged from 356–38 g and pyroxasulfone ranged from 393–104 g as

rates increased. Overall, reduction in plant biomass was variable and S-metolachlor treated plots

had biomass ranging from 417–285 g as rates increased. Surprisingly, 1X rates of all treatments

had slightly greater biomass than plots treated with 0.5X rates. Plots treated with 1X rates had

lower waterhemp densities than 0.5X rates (Figure 2.2), so this observation may be explained by

lower intraspecific competition, varying organic matter and subsequent herbicide dosage, or

potentially hormesis. Selected 1 degree of freedom contrasts between increasing rates of

acetochlor and a 4X rate of S-metolachlor are presented (Table 2.5) similar to plant density 28

and 42 DAT. Biomass recovered from plots treated with 0.5, 1, and 2X rates of non-

encapsulated acetochlor were not significantly different than that recovered from plots treated

with a 4X rate of S-metolachlor.

37

Results from both field experiments support previous studies conducted from 2014–2015

at the CHR location (Evans 2016). In previous studies, 79–95% control of CHR was achieved

with non-encapsulated acetochlor at rates ranging from 1.1–4.4 kg ha-1 28 DAT (Evans 2016).

Similarly, only 20–62% control was achieved with rates of S-metolachlor ranging from 0.8–3.2

kg ha-1 (Evans 2016). At the MCR location where a large difference in efficacy between S-

metolachlor and non-encapsulated acetochlor was initially documented (Hausman et al. 2013),

greater than 93% control was measured with non-encapsulated acetochlor at 3.4 kg ha-1while S-

metolachlor at 1.6 kg ha-1 provided less than 18% control 30 DAT. Alachor at 2.2 kg ha-1

provided 62–78% control 30 DAT (Hausman et al. 2013), which is consistent with the results

from the present research.

Overall, results from both field experiments indicate that Group 15 herbicides tested

provide varying levels of control, and the difference between non-encapsulated acetochlor and S-

metolachlor is greater than expected. In the present research, control with typical field-use rates

of non-encapsulated acetochlor was 75% at 28 DAT and control with S-metolachlor was 27% or

less at the same evaluation timing. Greater than 98% control of waterhemp following PRE

applications of non-encapsulated acetochlor and 95% control following applications of S-

metolachlor at 28 days after planting (DAP) have been reported (Steckel et al. 2002).

Non-encapsulated acetochlor provided 42% control of the CHR population, while S-

metolachlor provided less than 10% control by 42 DAT in the present research. In contrast, 57%

control of waterhemp with PRE applications of S-metolachlor and 61% control with non-

encapsulated acetochlor 56 DAP have been reported (Steckel et al. 2002). Moreover, greater

than 80% control of waterhemp 8 weeks after planting with S-metolachlor has been reported

(Johnson et al. 2012) and 80% control with racemic metolachlor has been documented four

38

weeks after planting (Hager et al. 2002). In addition to the differences noted between non-

encapsulated acetochlor and S-metolachlor, pyroxasulfone provided less control of the CHR

population than reports on other HPPD-resistant populations. Greater than 87% control was

recorded on the MCR waterhemp population (Hausman et al. 2013) and 83–95% control was

reported on a confirmed HPPD-resistant population from Nebraska (Oliveira et al. 2017).

The decrease in efficacy of Group 15 herbicides at the Champaign Co., IL site is a

problem for growers. Ideally, 3–5 weeks of residual control is expected from PRE herbicides,

and PRE applications of Group 15 herbicides alone are not effective in completely controlling

the CHR population. Early POST applications may need to be implemented to compensate for

the reduced duration of activity, along with the best management practices of multiple effective

SOAs per season (Evans et al. 2016) and sequential applications of residual herbicides (Steckel

et al. 2002). Group 15 active ingredients are affected by environmental factors and their

efficacy can be greatly influenced by the timing of waterhemp emergence. Subsequent dose-

response experiments in greenhouse conditions were designed to begin ruling out environmental

factors and, more importantly, compare CHR to other waterhemp populations.

2.4.2 Acetochlor and S-metolachlor Dose-Response Experiments under Greenhouse

Conditions

Following herbicide application, at 5 DAT waterhemp seedlings had emerged

consistently in each insert. Plants from each population (M6, NH40, ACR, WUS) initially

appeared healthy, but by 7 DAT, treated plants began exhibiting overall less vigor than untreated

plants. This pattern continued throughout the entire experiment and affected plants remained in

an arrested state of growth or died during the 21 d period. Similar symptomology has been

39

previously reported (Deal and Hess 1980; Dhillon and Anderson 1972; Fuerst 1987). Initial

ANOVA analysis of LD50 and GR50 values revealed significant population, treatment, and

population by treatment interactions across experimental runs.

2.4.2.1 Dose-Response to S-metolachlor

Both HPPD-sensitive populations (ACR and WUS) were controlled at 270 g ha-1 or less

by 21 DAT (Figure 2.6). In contrast, both M6 and NH40 were able to survive treatments of 2.7

kg ha-1 (Figure 2.6) and on occasion, replications (individual containers) of either population

survived 8.4 kg ha-1. Survivors from replicates treated with 2.7 or 8.4 kg ha-1 were severely

stunted, but plants were growing with at least one true leaf. Dose-response curves to S-

metolachlor are presented in Figure 2.4. LD50 values (Table 2.6) indicate an increase in

herbicide needed to control either HPPD- and PSII-resistant population (M6 and NH40).

Calculated resistant-to-sensitive (R/S) values for M6 and NH40 are 17.9 and 33.3 when

compared to WUS. When compared to ACR R/S values for M6 and NH40 are 34.3 and 63.8

respectively.

Growth reduction was also calculated (Table 2.6), and similar to LD50 values, GR50

values also describe a positive shift in rate needed to reduce above ground biomass. R/S values

for M6 and NH40 were 7.5 and 12.9 respectively in comparison to WUS. When compared to

ACR, R/S values were 9.9 and 17.1 for M6 and NH40 respectively. The large difference in GR50

R/S values and those calculated from LD50 estimates can be attributed to the low overall biomass

recovered from containers treated with higher rates of the herbicide.

40

2.4.2.2 Dose-Response to Acetochlor

Complete mortality of both sensitive populations (ACR and WUS) was achieved at lower

rates of acetochlor (≤80 g ha-1) comparatively to either M6 or NH40. Both M6 and NH40 were

completely controlled at 800 or 2530 g ha-1 (Figure 2.5). Similar to the results in response to S-

metolachlor, plants surviving in containers treated with higher levels of the herbicide were

severely stunted. Dose-response curves are presented in Figure 2.5 and LD50 and GR50 values

are presented in Table 2.6. R/S ratios were 4.5 and 5.7 for M6 and NH40 respectively when

compared to WUS based on calculated LD50 values. When compared to ACR values were 14.1

and 17.9 respectively. In terms of GR50 values, R/S ratios were 6.1 and 6.7 for M6 and NH40

respectively when compared to WUS. In comparison to ACR, R/S values were 13.2 and 14.6.

2.4.3 Implications

Overall, results indicate that non-encapsulated acetochlor, alachlor, and pyroxasulfone

provide the greatest PRE control of the CHR population under field conditions, with a varying

response of the population to other Group 15 herbicides. Greenhouse experiments corroborate

field data recorded at the CHR site, with an increase in S-metolachlor needed to control either

population with resistance to HPPD-, ALS-, and PSII-inhibitors. The decrease in efficacy of S-

metolachlor also corresponds with previous research (Evans 2016; Hausman et al. 2013). Both

multiple herbicide-resistant populations of waterhemp from Illinois with resistance to HPPD-

and PSII-inhibitors display less control in response to acetochlor and S-metolachlor in the

greenhouse, but complete control of both is achieved with acetochlor at rates lower than applied

in the field. Greenhouse results may partially explain field observations and suggest that plants

41

from both multiple herbicide-resistant populations contain mechanism(s) to detoxify certain

Group 15 herbicides.

Natural crop tolerance to this class of herbicides is achieved through rapid conjugation to

glutathione (GSH) or homoglutathione (hGSH) (Breaux 1987; Fuerst 1987). Detoxification can

occur enzymatically with the aid of glutathione S-transferases (GSTs) or non-enzymatically

(Frear and Swanson 1970; Gronwald 1989). Overall, higher levels of GST activity occur in

tolerant crops versus sensitive weed species in response to chloroacetamides (Hatton et al. 1996).

Waterhemp plants from the MCR population contain the metabolic capacity necessary for

oxidative metabolism of mesotrione and GST-mediated detoxification of atrazine (Ma et al.

2013). It is reasonable to believe that one or both of these biokinetic factors could be conferring

cross-resistance to certain Group 15 herbicides as well.

Cross-resistance affects multiple herbicides via a single mechanism and gene. Cross-

resistance to multiple herbicide SOAs is generally due to enhanced metabolism (Yu and Powles

2014), whereas target-site resistance is limited to affecting a single SOA group (Beckie and

Tardif 2012). It was postulated that resistance to the Group 15 herbicide pyroxasulfone in a

population of Lolium rigidum is governed by a single locus, which could contribute to cross-

resistance to herbicides from other SOA groups (Busi et al. 2014). Cross-resistance to

pyroxasulfone and the Group 8 herbicide prosulfocarb was selected through sequential

applications of either herbicide outdoors during normal growing season conditions (Busi and

Powles 2016). Both pyroxasulfone and prosulfocarb share a similar overall mode of action

(MOA) (Böger 2003; Busi 2014; Fuerst 1987), but Group 8 herbicides require initial oxidative

bio activation in order to be phytotoxic (Busi 2014; Busi et al. 2017; Fuerst 1987). Therefore,

resistance to Group 15 herbicides in Lolium rigidum could partially be due to cytochrome P450

42

enzymes (Busi et al. 2017), but more likely is due to increased GST mediated detoxification

since increased oxidative metabolism would antagonize Group 8 herbicides such as prosulfocarb

(Busi 2014; Busi et al. 2017).

A similar detoxification process may be occurring in CHR, but it is unclear why

acetochlor is less affected than other Group 15 herbicides. Herbicide detoxification mechanisms

in plants through GST-catalyzed conjugation to GSH or P450 activities are complex and

substrate specific (Edwards and Owen 1989; Werck-Reichhart et al. 2000; Riechers et al. 2010).

It is therefore possible that the mechanism(s) in CHR governing activities of Group 15 herbicides

for waterhemp control, such as enhanced detoxification, is preferential to Group 15 herbicides

other than acetochlor. Also, Group 15 herbicides target the VLCFA elongase encoded by the

FAE1 gene (Böger 2003), but it was demonstrated that Group 15 herbicides inhibit more than

one VLCFA-elongase enzyme in Arabidopsis thaliana, including At5g43760, At104220,

At1g25450, KCS1, KCS2, and FAE1 (Trenkamp et al. 2004). Acetochlor may inhibit more of

these condensing enzymes (or different enzymes) than other Group 15 active ingredients tested

on CHR and thus remains more effective, analogous to the complex interactions of synthetic

auxin herbicides with various TIR1/AFB auxin receptors (Mithila et al. 2011).

In addition, edaphic factors could be contributing to the decreased activity of certain

Group 15 herbicides at the CHR site. The site has a high level of organic matter, and in general,

soils with high organic matter will have increased microbial activity and lower herbicide

availability (Shaner et al. 2006; Long et al. 2014; Wu et al. 2011). Repeated applications of the

same active ingredient can condition the microbial community and result in increased microbial

degradation (Sanyal and Kulshrestha 1999; Shaner and Henry 2007).

43

Further research on both CHR and the MCR population is needed to determine the

underlying cause for the differential response of these populations to Group 15 herbicides.

Herbicides with this SOA have been a valuable resource of for over sixty years. Understanding

how these ‘old chemistries’ interact in the environment, both in the plant and soil, will be crucial

for maintaining them as an effective SOA for residual control of small-seeded broadleaves in the

future.

2.5 Source of Materials

1Teejet Technologies, P.O. Box 7900, Wheaton, IL 60187.

2Statistical Analysis Software (SAS) 9.4. SAS Institute, Inc., 100 SAS Campus Drive, Cary, NC

27513.

3Scotts Osmocote Classic 13-13-13, The Scotts Company, 14111 Scottslawn Rd., Marysville,

OH 43041.

4Peters 20-20-20, Everris NA inc., P.O. Box 3310, Dublin, OH 43016)

5Generation III Research Sprayer, DeVries Manufacturing, 86956 State Highway 251,

Hollandale, MN 56045.

6Netafim USA, 5470 East Home Ave, Fresno, CA 93727.

44

2.6 Tables and Figures

Table 2.1 Cumulative precipitation recorded at the Champaign Co., IL field

location during 2016–2017 field experiments.

Days after herbicide application

(DAA)

Precipitation (cm)

2016 2017

0–3 0.66 3.1

0–7 0.66 3.9

0–42 23.3 11.4

45

Table 2.2 Group 15 herbicides, rates, and source information for field studies at Champaign Co., IL (2016 to 2017). Herbicides

were applied to bare ground prior to weed emergence.

Common name Trade name Application rate Manufacturer

acetochlora

Warrant

kg ai ha-1

2.5

Monsanto Company, St. Louis, MO 63137;

www.monsanto.com

acetochlor Harness 2.7 Monsanto Company, St. Louis, MO 63137;

www.monsanto.com

S-metolachlor Dual Magnum 2.1 Syngenta Crop Protection, Greensboro, NC 27419;

www.syngentacropprotection.com

S-metolachlorb Dual II Magnum 2.1 Syngenta Crop Protection, Greensboro, NC 27419;

www.syngentacropprotection.com

metolachlor Stalwart 2.2 SipcamAgro, Durham, NC 27713;

www.sipcamadvan.com

dimethenamid-P Outlook 1.1 BASF Corporation Agricultural Products, Research Triangle Park, NC

27709; www.agro.basf.com

alachlor Intrro 3.6 Monsanto Company, St. Louis, MO 63137;

www.monsanto.com

pyroxasulfone Zidua 0.24 BASF Corporation Agricultural Products, Research Triangle Park, NC

27709; www.agro.basf.com aencapsulated formulation

bcontains the herbicide safener benoxacor

46

Table 2.3 Mean estimatesa of waterhemp control 28 and 42 days after treatment (DAT), density 28 and 42 DAT, and

recovered biomass 42 DAT of Group 15 herbicides (2016–2017).

Control Density Biomass

Herbicide Rate 28 DAT 42 DAT 28 DAT 42 DAT 42 DAT

kg ai ha-1 ─ % ─ ─ plants m-2 ─ g m-2

acetochlorb

acetochlor

S-metolachlor

S-metolachlorc

metolachlor

dimethenamid-P

alachlor

pyroxasulfone

2.5

2.7

2.1

2.1

2.2

1.1

3.6

0.24

23

75

16

27

14

13

67

56

b

a

b

b

b

b

a

a

3

42

6

10

3

3

31

21

d

a

d

cd

d

d

ab

bc

79

13

126

95

136

96

21

34

bcd

a

d

cd

d

cd

ab

abc

79

14

104

97

134

94

26

36

bcd

a

cd

cd

d

cd

ab

abc

284

135

427

381

425

407

241

276

abc

a

c

bc

c

c

ab

abc

Nontreated ─ ─ ─ 152 d 137 d 402 bc aMean estimates followed by the same letter within a column not significantly different at α= 0.05 (separated by LSD using the

SAS micro %pdmix800).

bencapsulated formulation

ccontains the herbicide safener benoxacor

47

Table 2.4 Mean estimatesa of waterhemp (Amaranthus

tuberculatus) control 28 and 42 days after treatment (DAT) from

the Group 15 rate titration study (2016–2017).

Control

Treatment Rate 28 DAT 42 DAT

Xb kg ha-1 ─ % ─

acetochlor ½ 1.4 44 cd 19 cd

1 2.7 67 bc 34 bc

2 5.4 85 ab 66 a

4 10.8 94 a 80 a

S-metolachlor ½ 1.1 10 e 0 d

1 2.1 10 e 0 d

2 4.2 20 e 8 cd

4 8.4 45 bcd 23 bc

pyroxasulfone ½ 0.12 27 de 15 cd

1 0.24 40 de 21 cd

2 0.48 63 abc 51 ab

4 0.96 74 abc 68 a aMean estimates followed by the same letter within a column not significantly different at α=

0.05 (separated by the SAS micro %pdmix800).

bRelative rate based on manufacturers’ labelled recommendations.

48

Table 2.5 Select contrasts of waterhemp density 28 and 42 days after treatment (DAT) and

recovered biomass 42 DAT between a rate of S-metolachlor compared to increasing rates of

acetochlor from the Group 15 rate titration study (2016–2017).

Density Biomass

Contrast 28 DAT 42 DAT 42 DAT

─ Ρ value ─

S-metolachlor (4) < acetochlor (0.5) 0.38 0.46 0.47

S-metolachlor (4) < acetochlor (1) 0.57 0.80 0.38



49

Table 2.6 Pooled greenhouse dose-response data to assess

differences among waterhemp (Amaranthus tuberculatus)

populations. Estimated LD50 and GR50 values are expressed as S-

metolachlor or acetochlor g ha-1 followed by their respective

standard errors of the mean.

Population LD50 GR50

g ha-1

Response to S-metolachlor

M6 1808 (±329) 431 (±61)

NH40 3360 (±624) 742 (±237)

ACR 53 (±9) 44 (±7)

WUS 101 (±16) 57 (±9)

Response to acetochlor

M6 178 (±24) 72 (±33)

NH40 226 (±34) 80 (±2)

ACR 13 (±2) 5 (±1)

WUS 40 (±4) 12 (±2)

50

Figure 2.1 Relationship of waterhemp (Amaranthus tuberculatus) density 28 DAT at the

Champaign Co., IL location in response to increasing rates of three Group 15 herbicides (2016–

2017). A continuous line with solid squares signifies treatments of S-metolachlor; a

discontinuous line with solid triangles signifies treatments of pyroxasulfone; and a continuous

line with solid circles represents treatments of acetochlor. Symbols on each line signify the

mean ±SE.

51

Figure 2.2 Relationship of waterhemp (Amaranthus tuberculatus) density 42 DAT at the

Champaign Co., IL location in response to increasing rates of three Group 15 herbicides (2016–

2017). A continuous line with solid squares signifies treatments of S-metolachlor; a

discontinuous line with solid triangles signifies treatments of pyroxasulfone; and a continuous

line with solid circles represents treatments of acetochlor. Symbols on each line signify the

mean ±SE.

52

Figure 2.3 Relationship of accumulated biomass per m-2 42 DAT at the Champaign Co., IL

location in response to increasing rates of three Group 15 herbicides (2016–2017). A continuous

line with solid squares signifies treatments of S-metolachlor; a discontinuous line with solid

triangles signifies treatments of pyroxasulfone; and a continuous line with solid circles represents

treatments of acetochlor. Symbols on each line signify the observed mean ±SE.

53

Figure 2.4 Herbicide dose-response experiments of four waterhemp (Amaranthus tuberculatus)

populations to soil-applied S-metolachlor. Data were collected 21 DAT. (A) dry biomass as a

percentage of untreated control, and (B) mean survival of waterhemp seedlings as a percentage

of untreated control. Lines in each graph were fitted using equation (1): (𝑦 = 𝑐 + 𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[log(𝑥)−log(𝐿𝐷50/𝐺𝑅50)]}), and each symbol represents the observed mean ±SE. M6,

continuous line and full squares; NH40, Continuous line and full circles; ACR, discontinuous

line and open squares; WUS, discontinuous line and open circles

54

Figure 2.5 Herbicide dose-response experiments of four waterhemp (Amaranthus tuberculatus)

populations to soil-applied acetochlor. Data were collected 21 DAT. (A) dry biomass as a

percentage of untreated control, and (B) mean survival of waterhemp seedlings as a percentage

of untreated control. Lines in each graph were fitted using equation (1): (𝑦 = 𝑐 + 𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[log(𝑥)−log(𝐿𝐷50/𝐺𝑅50)]}), and each symbol represents the observed mean ±SE. M6,


line and open squares; WUS, discontinuous line and open circles.

55

Figure 2.6 Response of four waterhemp (Amaranthus tuberculatus) populations 14 DAT in response to (A) 25 g acetochlor ha-1, (B)

800 g acetochlor ha-1, (C) 270 g S-metolachlor ha-1, and (D) 2650 g S-metolachlor ha-1. In each frame, outside columns are untreated

(signified by U) and treated containers are located in the center below labeled rate. Populations (1, M6; 2, NH40; 3, WUS; 4, ACR)

displayed with untreated nearest number and corresponding treatment directly adjacent. Herbicide treatments were applied directly the

soil PRE.

56



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CHAPTER 3

SOILLESS ASSAY TO CHARACTERIZE THE RESPONSE OF MULTIPLE

HERBICIDE-RESISTANT WATERHEMP (AMARANTHUS TUBERCULATUS) TO

CHLOROACETAMIDE HERBICIDES

3.1 Abstract

Previous and ongoing field research indicates that a population of waterhemp (CHR) with

resistances to herbicides from five site-of-action (SOA) groups, including 4-

hydroxyphenylpyruvate dioxygenase (HPPD)- and photosystem II (PSII)-inhibitors, displayed a

decreased response to several chloroacetamide herbicides, with significant differences in control

following (PRE) applications of acetochlor and S-metolachlor. Growth chamber experiments

were initiated to investigate the response of multiple herbicide-resistant waterhemp populations

to acetochlor and S-metolachlor. Chloroacetamide herbicides are PRE herbicides that are

applied directly to soil. Once in the soil, their efficacy can greatly be influenced by soil

properties such as clay content, organic matter, and microbial activity. Environmental factors

such as temperature and precipitation can also influence their ability to provide weed control.

The goal of growth chamber experiments is two-fold: (1) characterize the response of Illinois

HPPD- and PSII-resistant waterhemp populations to both acetochlor and S-metolachlor relative

to sensitive populations and (2) explore if edaphic factors contribute to the response of

populations to acetochlor and S-metolachlor. Included in experiments are three multiple-

resistant waterhemp populations: M6 (progeny from CHR), NH40 (progeny obtained from

Mclean Co., IL), and ACR (Adams Co., IL), in comparison with a known sensitive population

(WUS). Experiments were conducted in sterile petri plates with herbicide treated agarose gel.

64

Radicle elongation was evaluated 3 d after planting as an indicator of plant response to either

herbicide as chloroacetamides directly inhibit root growth in dicot species. Inhibition of radicle

growth (GR50) comparisons and their corresponding resistant-to-sensitive (R:S) ratios were

insignificant. Initial analysis indicated that waterhemp population, herbicide treatment, and their

interactions were not significant. Results from the growth chamber were inconclusive and

further research on the CHR population in the greenhouse was warranted.

3.2 Introduction

Native to the Midwest, waterhemp [(Amaranthus tuberculatus (Moq) Sauer] is a small-

seeded, summer-annual broadleaf weed species (Sauer 1955). It has become one of the most

troublesome weed species for growers in the region due to its adaptable biology. Waterhemp is

naturally able to excel in disturbed environments (Sauer 1957), and is a vigorous grower utilizing

the C4 carbon fixation pathway (Steckel 2007). Waterhemp is also dioecious with separate male

and female plants (Murray 1940). A single female plant can be pollinated by multiple males

resulting in high levels of genetic diversity (Hager 1997). This diversity allows resistance to

develop in response to herbicides from various site-of action (SOA) groups (Steckel 2007) with a

total resistance to herbicides from six SOAs as a species and commonly found multiple-resistant

populations (Heap 2017). In addition to herbicide resistance, waterhemp is capable of producing

up to a million seeds per female plant that emerge in several events throughout the growing

season (Buhler and Hartzler 2001; Harzler et al. 1999; Steckel et al. 2003).

Chloroacetamides are preemergence (PRE) herbicides with activity on annual grasses and

small-seeded broadleaf weed species (Fuerst 1987). Active ingredients from this class of

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herbicides are known as very-long-chain fatty acid (VLCFA)-inhibitors since their SOA is

VLCFA-synthase in the VLCFA-elongase complex, and inhibition of this site results in the

depletion of VLCFAs (Böger 2003). VLCFAs have acyl chains in excess of 18 carbons and are

integral components in cellular membranes and cuticle waxes (Bach and Faure 2010). The

depletion of VLCFAs is responsible for the phytotoxicity of chloroacetamides (Böger 2003)

leading to unstable cells and eventual plant death (Matthes et al. 1998). At field use rates,

chloroacetamides do not inhibit germination but rather inhibit emerging weed seedlings (Fuerst

1987). Generally, affected species either fail to emerge, or remain stunted soon after emergence

(Deal and Hess 1980; Dhillon and Anderson 1972; Pillai et al. 1979).

In previous research, a large difference in efficacy was reported between acetochlor and

S-metolachlor on a population of waterhemp from Champaign County, IL (CHR) (Evans 2016).

The population was characterized resistant to 4-hydroxyphenylpyruvate dioxygenase (HPPD)-,

photosystem II (PSII)-, acetolactate synthase (ALS)-, and protoporphyrinogen oxidase (PPO)-

inhibiting herbicides and the synthetic auxin 2,4-D (Evans 2016). Similar findings were reported

earlier on a separate HPPD-, PSII-, and ALS-resistant population from Mclean County, IL

designated MCR (Hausman et al. 2013). In both cases, acetochlor provided significantly greater

control than S-metolachlor (Evans 2016; Hausman et al. 2013). Current research investigated the

previous field observations on the CHR population (data not shown) and further characterization

was needed.

Acetochlor and S-metolachlor are influenced by edaphic factors and the environment.

Efficacy of either herbicide is greatly influenced by the precipitation timing and amount relative

to herbicide application. Moreover, sorption of acetochlor or S-metolachlor varies greatly with

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soil organic matter and clay content, being less available as either increases (Hiller et al. 2009;

Shaner et al. 2006; Wu et al. 2011). Reports also indicate that microbial degradation is a major

contributor to the break down or mineralization of S-metolachlor (Ma et al. 2006; Zemolin et al.

2014). Growth chamber experiments were designed to characterize the CHR and MCR

populations in response to chloroacetamides under controlled conditions, and also explore if

edaphic factors contribute to the divergence in control between acetochlor and S-metolachlor

under field conditions.

3.3 Materials and Methods

3.3.1 Inhibition of Waterhemp Radicle Elongation in Response to Chloroacetamide

Herbicides

3.3.1.1 Waterhemp Populations

Four populations of waterhemp were chosen for characterization in response to

acetochlor and S-metolachlor. M6, derived from the CHR site, is the progeny of resistant x

resistant (R x R) isolated greenhouse crosses from seed collected in the field. A previously

confirmed HPPD- and atrazine-resistant population (NH40) derived from the MCR site

(Hausman 2012) was also included for comparison with M6 (Evans 2016). Two known HPPD-

sensitive populations (ACR, WUS) were included in order to calculate R/S ratios. ACR is

resistant ALS-, s-triazine, and PPO-inhibiting POST herbicides (Patzoldt et al. 2005) while WUS

is not resistant to any herbicide. All seeds were stratified according to methods outlined by Bell

et al. (2013) and stored at 4°C for at least 20 days prior to experiment initiation to improve

germination.

67

3.3.1.2 Agar Preparation and Herbicide Incorporation

24 hr prior to planting, sterile 100 cm-2 petri plates1 were prepared with agar. Molecular

grade agarose gel was constructed at 1% vol/vol and stabilized at 50°C in a hot water bath. 0.01

mol stock solutions of acetochlor and S-metolachlor were prepared, and diluted stocks were

made ranging from 0.005–50 mM on a base 3.16 logarithmic scale. Plates were poured below a

laminar hood to prevent contamination. 45 ml of agarose gel was poured into 100 ml specimen

containers1 and 450 μl of diluted herbicide stock was added to the agar and thoroughly mixed.

The desired range of rates for each herbicide was 0.05–500 μM. For example, to make a plate

with 500 µM concentration of either herbicide, 450 μl of 50 mM herbicide was added to 45 ml

agarose. After mixing, the agarose was poured into the petri plates carefully to prevent the

formation of air bubbles. Plates were allowed to completely cool beneath the laminar hood and

sealed for storage prior to planting.

3.3.1.3 Plant Culture

Seeds from each of the four populations were pre-germinated in sterile 100 X 15 mm

petri plates1 on 90 mm circular filter paper2 moistened with 5 ml ddH20. Plates were sealed with

parafilm1 and placed in a growth chamber set at 35/15°C day/night with a 16 hr photoperiod.

Light was supplemented by inflorescent light to provide 130 to 150 µmol m-2 s-1 photon flux at

the plate surface.

After 24 hours of incubation in the growth chamber, seeds with protruding radicles not

more than 1 mm in length were chosen for transfer to plates containing the agarose medium.

68

Five seeds of each of the four populations were placed in labeled locations on each prepared petri

plate for a total of twenty seeds. Seeds among each population were placed approximately 1 cm

apart with at least 1 cm from the side of the plate. Seeds were gently pressed into the growth

medium (approximately 2 mm) and plates were sealed with parafilm.

Each treatment included three replicate petri plates with five biological replicates per

population per plate. Plates were then placed in the growth chamber at approximately a 75° angle

to allow contact of both the radicle and emerging shoot to the herbicide-containing agar.

Conditions were maintained as stated previously for the duration of the experiment.

3.3.1.4 Data Collection and Statistical Analysis

High quality photographs were taken directly after planting to document the baseline

radicle lengths for each biological replication. The camera was mounted on a tripod to maintain

the same distance from each plate for each photograph, and a ruler was included as a scaling

factor for each image. Photographs were taken again 3 d after planting following the same

procedure. Radicle lengths were measured using ImageJ software3. Once measured, baseline

radicle lengths were subtracted from lengths documented at 72 hr after planting, and

measurements were divided by the average of untreated replicates to be converted to a

percentage of untreated.

Statistical analysis was performed using R software 3.4.2. Growth measurements from

all three experimental runs were pooled and analyzed using non-linear regression in the ‘drc’

package in R (Knezevic et al. 2007). Each treatment was analyzed separately. The logistic dose-

response function was fitted utilizing the following equation:

69

𝑦 = 𝑐 +𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[log(𝑥)−log(𝐿𝐷50/𝐺𝑅50)]} [1]

The logistic function consists of four-parameters: b is the slope of the curve, c is the

lower asymptote, d is the upper asymptote, and GR50 is the 50% reduction in radicle growth.

Initially GR50 values were calculated for each individual experimental run. GR50 values were

then analyzed by ANOVA via a general linear mixed effects model in the ‘nlme’ package in R to

test the main effects of treatment, population, and their interactions. Experimental run was

considered a random effect.

3.4 Results and Discussion

3.4.1 Inhibition of Waterhemp Radicle Elongation in Response to Chloroacetamide

Herbicides

Relative radicle growth was inhibited 72 h after planting as each herbicide rate increased

(Figures 3.1 and 3.2). Neither herbicide completely inhibited radicle elongation. Germination

had already been initiated and radicle growth began before exposure to the herbicide, which

could explain why growth was not completely inhibited. Chloroacetamide herbicides due not

cause growth to abruptly stop, but rather inhibit plant establishment (Fuerst 1987). Naturally,

growth would continue until the herbicide entered the growing seedling and reached the target

site. Calculated GR50 values (Table 3.1) and overall differences between populations were

negligible. Higher GR50 values were calculated for acetochlor relative to S-metolachlor implying

that waterhemp populations were less sensitive to acetochlor in the absence of soil. Analysis of

effective dose values by ANOVA did not reveal a significant effect of herbicide treatment,

70

waterhemp population, or their interactions. In addition, calculated resistant-to-sensitive (R/S)

values were insignificant.

The dose-response to S-metolachlor is presented (Figure 3.1). Both M6 and NH40 were

less affected than either HPPD-sensitive population (WUS and ACR) at rates less than 1.6 μM.

In contrast, all populations had a similar response to the herbicide at rates above 1.6 μM, and in

most cases, ACR and WUS were less inhibited. The dose-response to acetochlor is presented

(Figure 3.2). Overall, less separation between populations was documented comparatively to S-

metolachlor. All populations had a similar response in radicle elongation at rates greater than 1.6

μM, and at several rates ACR and WUS were less inhibited, similar to findings with S-

metolachlor.

The results from this experiment were not as anticipated. Based on data collected in the

field on the CHR population, and previous findings on the MCR population (Hausman et al.

2013), we expected to see a divergence in response of either M6 or NH40 to chloroacetamide

herbicides compared to sensitive populations. Based on data recorded in subsequent greenhouse

dose-response experiments (data not shown), the duration of this experiment may not have

allowed the differential response to fully quantify itself. Differences in the greenhouse appeared

7 d after treatment (DAT) and compounded as the experiment progressed (data not shown). By 3

d after planting in the present research, both HPPD- and atrazine-resistant populations exhibited

a positive increase in S-metolachlor needed for inhibition comparatively to sensitive populations

(Figure 3.1). This separation occurred at very low herbicide doses, however, and as rates

increased, the sensitive populations responded similar or were less affected than populations

containing resistance to HPPD-inhibitors and atrazine. If the experiments were allowed to

71

progress past 7 d, the results may have differed. In addition, edaphic factors may influence the

response of all populations to S-metolachlor and acetochlor, which could explain the lack of

separation between populations in herbicide-treated agarose.

Results from the radicle elongation experiments do however correspond to previous

reports of root inhibition in dicot species (Deal and Hess 1980; Dhillon and Anderson 1972;

Duke et al. 1975; Pillai et al. 1979; Sloan and Camper 1986). In the present research, waterhemp

radicle length was inhibited over 60% in response to both acetochlor and S-metolachlor as rates

increased from 0.05–500 μM. Root length was severely inhibited in squash (Cucurbita maxima

‘Duchesne’) seedlings as early as 3 DAT with 4 and 16 ppm concentrations of propachlor

(Dhillon and Anderson 1972). Subsequent studies revealed that radicle growth in cucumber

(Cucumis sativus L. ‘Straight Eight’) seedlings were inhibited within 24 hr of being treated with

the same active ingredient (Duke et al. 1975). Similarly, 63% inhibition of radicle elongation in

cucumber (Cucumis sativus L. cv. ‘Marketeer’) 3 d after treatment was reported (Sloan and

Camper 1986). Other reports indicated that up to 70% inhibition of root growth is possible in

response to metolachlor at concentrations ranging from 1–100 μM with various dicot species

(Deal and Hess 1980; Pillai et al. 1979). Interestingly, previous reports on the herbicidal activity

of chloroacetamides utilized large-seeded dicot species even though the active ingredients only

provide control of small-seeded dicot weeds and annual grasses (Fuerst 1987). The present

research corroborates past observations and indicates root inhibition is a valid observation in

affected dicot-weed species.

Overall, more research is necessary in characterizing multiple herbicide-resistant

populations in a controlled environment. Ongoing field data is useful in documenting the

72

problem growers face, but environmental factors create variability among treatments and

growing seasons. Greenhouse dose-response experiments are important to characterize the

response of multiple herbicide-resistant populations to chloroacetamide herbicides, but cannot

completely rule out edaphic factors. Modifications to the present research, and additional

experiments in controlled environments, will be essential in understanding the response of

waterhemp populations to chloroacetamide herbicides. Chloroacetamides have been effective

active ingredients for residual control of troublesome small-seeded dicot weed species for over

sixty years (Hamm 1974), and understanding how they work on multiple herbicide-resistant

waterhemp populations will be essential in maintaining them as an effective SOA for years to

come.

3.5 Research Summary and Concluding Remarks

For over sixty years, active ingredients from the chloroacetamide family of herbicides

have been an effective resource for PRE control of small-seeded dicot weed species, including

those belonging to the Amaranthaceae family (Jaworski 1956; Hamm 1974). Their respective

mode-of-action (MOA) and site-of-action (SOA) remained a mystery for decades, until it was

finally discovered that the chloroacetamides and related compounds cause a depletion of very-

long-chain fatty acids (VLCFAs) (Böger 2003). VLCFAs consist of acyl chains in excess of 18

carbon and are integral components of cellular membranes and cuticle waxes (Bach and Faure

2010). Affected plants have cells with poor membrane stability, which result in cells prone to

lyse and eventual plant death (Matthes et al. 1998). Chloroacetamides effect emerging seedlings,

73

and sensitive species either fail to emerge or struggle to become established following

emergence (Fuerst 1987).

Waterhemp has been, and will continue to be, one of the most problematic weeds

Midwest growers face. With high reproductive ability and developmental plasticity (Steckel et

al. 2003; Steckel 2007), the species is able to proliferate in a wide range of conditions, including

those created in agronomic fields (Sauer 1957). With the potential to reduce soybean yields over

40% (Hager et al. 2002) and corn yield over 70% (Steckel and Sprague 2004), controlling

waterhemp infestations is a challenge that is economically important. Waterhemp is very

efficient at developing resistance to various herbicides and has been previously reported resistant

to herbicides from six SOAs, including: 4-hydroxyphenylpyruvate dioxygenase (HPPD),

photosystem II (PSII), acetolactate synthase (ALS), 5-enolpyruvylskikimate-3-phosphate

synthase (EPSPS), and protoporphyrinogen oxidase (PPO) inhibiting herbicides along with the

synthetic auxin 2,4-D (Heap 2017). Multiple or “stacked” herbicide resistance is a common

occurrence with three, four, and five-way resistances being reported in waterhemp populations

(Patzoldt et al. 2005; Bell et al. 2013; Evans 2016).

During research conducted on the first HPPD-resistant population of waterhemp (MCR)

in Mclean County, IL, S-metolachlor provided significantly less than anticipated control PRE

(Hausman et al. 2013). A few years later while characterizing a novel five-way resistant

population of waterhemp (CHR) from Champaign County, IL, with resistance to HPPD-, PSII-,

ALS-, and PPO-inhibitors plus the synthetic auxin 2,4-D, a similar decrease in efficacy of S-

metolachlor was reported (Evans 2016). In both scenarios, another chloroacetamide, acetochlor,

remained effective (Hausman et al. 2013; Evans 2016). With similar observations on

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comparable waterhemp populations from different geographies, investigation of this anomaly

was warranted. Experiments that are described in this thesis were implemented at the CHR site

and in controlled greenhouse and growth chamber environments. The overall goal of this

research was to determine if the divergence in response between acetochlor and S-metolachlor is

recurring, and if resistance to VLCFA-inhibiting herbicides had truly developed.

The field experiments presented in Chapter 2 were initiated to expand on previous

research (Evans 2016). The goal was to determine the response of the CHR to various Group 15,

or VLCFA-inhibiting herbicides, at typical field use rates based on their respective

manufacturer’s labeled recommendations. In addition, three active ingredients (non-

encapsulated acetochlor, S-metolachlor, and pyroxasulfone) were chosen for comparison at

increasing rates. Furthermore, greenhouse dose-response experiments presented in Chapter 2

were conducted to quantify the difference of CHR progeny (M6) relative to a derivative from the

MCR population (NH40) and HPPD-sensitive waterhemp populations in response to both

acetochlor and S-metolachlor.

In the field, CHR responded to VLCFA-inhibiting herbicides similarly to observations

made by Evans (2016). Non-encapsulated acetochlor was among active ingredients providing

high levels of control of with a 1X rate providing 75% control of CHR. Alachlor, a close

structural analog to acetochlor, provided 67% control of CHR, similar to reports by Hausman et

al. (2013). S-metolachlor, regardless of formulation, provided less than 27% control at a field

use rate. More importantly, even as rates of S-metolachlor were increased to 4X the

recommended use rate, control comparable to acetochlor was not achieved.

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In the greenhouse, a large divergence in control was documented with both M6 and

NH40 relative to the HPPD-sensitive populations (WUS and ACR) following PRE applied

acetochlor and S-metolachlor. LD50 and GR50 values and respective resistant-to-sensitive ratios

(R/S) were calculated to quantify this difference. In response to S-metolachlor, there was a 17.9

and 33.3-fold difference between M6 and N40 respectively compared to WUS when calculated

based on seedling survival (LD50). R/S values were higher when compared to ACR. Most

importantly, seedlings from both M6 and NH40 were able to survive at rates up to, and above,

those used in the field. In response to acetochlor, there were significant differences between

either population with both HPPD- and PSII-inhibitor resistance (M6 and NH40) compared to

sensitive populations, but the calculated R/S ratios were smaller. In addition, none of the

populations were able to survive a field use rate of acetochlor in the greenhouse and, most often,

populations were controlled at 1–2 levels of magnitude below a field rate.

While interesting, research presented in Chapter 2 revealed a very troublesome situation.

Field results indicate that Group 15 herbicides are not effective in controlling the CHR

population with the exception of acetochlor. Greenhouse experiments corroborate field data and

indicate that both M6 and NH40 exhibit a decreased response to both acetochlor, and most

notably, S-metolachlor. This concludes that the CHR population may contain a novel form of

herbicide resistance to Group 15 herbicides. A similar conclusion can be reached in regards to

MCR based on previous field observations, and the response of NH40 in the greenhouse.

Resistance to Group 15 herbicides is very rare, and worldwide only five grass species have been

documented resistant (Heap 2017). Resistance to this class of herbicides has not been reported

previously in a dicot weed species. Not only does this research document potential resistance to

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Group 15 herbicides in a dicot species for the first time, it also raises the number of herbicide

SOAs to which waterhemp is resistant to seven.

Moreover, CHR may represent a population of waterhemp with individuals containing

resistance to herbicides from six different SOAs. This creates a nightmare situation for the

grower. Currently, based on the present and past research, control of the CHR population PRE is

only achieved with non-encapsulated acetochlor and metribuzin (Evans 2016). Even though

control is adequate, it is not complete control, and based off greenhouse observations in Chapter

2, how long will acetochlor remain effective? Presently, there is already an increase in effective

rate needed for control of CHR in the greenhouse relative to HPPD-sensitive populations. If the

grower was to rely solely on acetochlor in future seasons, eventual failure of the active ingredient

is certain.

The question is: How widespread of an issue is VLCFA-inhibitor resistance in

waterhemp? This research documents potential resistance in two geographically separated

populations from Illinois. The CHR and MCR populations have been heavily researched for

several years. It is not unreasonable to believe that other populations have developed resistance,

and due to the outcrossing ability of waterhemp, fields surrounding both the CHR and MCR

locations likely have individuals containing similar resistance. On the other hand, this may be a

very limited scenario and may remain isolated for years to come.

Only time will tell the fate of Group 15 herbicides for control of waterhemp. They have

remained effective for decades, but increased stress of effective PRE programs and overlapping

residual herbicides in each season has increased their usage. In some cases, the same acreage

may be treated with the same Group 15 active ingredient multiple times each season. In

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addition, many of today’s modern herbicide premixes rely on this class of herbicides as their

residual component. This is especially true in soybean production where options are limited for

postemergence (POST)-applied residual herbicides. From a historical perspective, reliance on a

single herbicide SOA results in resistance, and the same situation is possible for Group 15

herbicides.

Overall, results from Chapter 2 reinforce the need for an integrated management

approach to control waterhemp. PRE residual herbicides along with nonchemical control

methods will continue to be important (Hager et al. 1997) along with multiple effective herbicide

SOAs each season (Evans et al. 2016). Waterhemp must be controlled to prevent passing of

genetic material to the next generation. With the reduction in effective SOAs and reduced

duration of control documented with PRE herbicides at the CHR location, the grower may have

to implement earlier POST applications, overlapping residual herbicides, and alternative

strategies for preventing waterhemp establishment.

Research on the CHR and MCR populations is far from over, and further experimentation

is warranted. At this point, the mechanism for resistance to Group 15 herbicides is unknown for

either population. Being soil applied, many factors influence the efficacy of this class of

herbicides and results from Chapter 3 were inconclusive in discounting edaphic factors for the

results documented in the field. Further experimentation is needed to investigate this aspect as

the response of either population with resistance to HPPD- and PSII-inhibitors may not only

plant related. A combination genotypic and environmental factor interactions is also possible.

Increased greenhouse experimentation is planned to quantify the response of multiple

herbicide-resistant populations to other Group 15 herbicides such as pyroxasulfone and

78

dimethenamid-P. Experiments utilizing soils with low levels of organic matter not only be

useful in characterizing the response of waterhemp populations to chloroacetamide herbicides,

but also in documenting the influence of organic matter on herbicide efficacy. Greenhouse

synergy studies with various insecticides such as phorate and malathion may provide insight into

biological mechanisms within the plant, and soilless assays utilizing agar or hydroponic systems

will be useful in determining what factors are influencing the results presented in Chapter 2.

Analytical laboratory experimentation is needed to investigate bio-kinetic factors within

the plant and determine the underlying cause of potential resistance to Group 15 herbicides in the

examined HPPD- and PSII-resistant waterhemp populations from Illinois. Both MCR and CHR

are resistant to HPPD-, ALS-, and PSII inhibiting herbicides. In addition, previous field research

(Hausman et al. 2016) along with unpublished greenhouse findings, indicated that MCR also has

a decreased response to 2,4-D similar to CHR. Mechanistically, previous research documented

that the MCR population has the genetic capacity for cytochrome P450 mediated metabolism of

the HPPD-inhibiting herbicide mesotrione and glutathione-S-transferase (GST) mediated

detoxification of the PSII-inhibitor atrazine (Ma et al. 2013). Target site investigation in the

CHR population did not reveal any mutations to the psbA gene (Evans 2016), so resistance to

atrazine in the CHR population is likely non-target site based similar to MCR.

With striking similarities between the two populations, this researcher speculates that

either mechanism (P450 or GST) may potentially be responsible for resistance to Group 15

herbicides. Either of these mechanisms may be a general mechanism of cross-resistance to

herbicides from multiple SOAs. Research on a population of lolium rigidum resistant to Group

15 herbicides implied that resistance was partially due to cytochrome P450 enzymes (Busi et al.

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2017), but more likely GSTs are involved (Busi 2014). Rapid conjugation to glutathione (GSH)

or homoglutathione (hGSH) usually through increased GST activity endows crop tolerance to

this class of herbicides (Breaux 1987; Gronwald 1989). Potentially, weeds such as the

populations of waterhemp described in this research, may be emulating this mechanism.

Metabolism studies utilizing radiolabeled herbicide along with in vitro target site analysis will be

useful in understanding the underlying mechanism of resistance.

Waterhemp will continue to be a problem for growers and herbicides will continue to be

the control method of choice. With potential resistance to Group 15 herbicides in waterhemp,

growers should understand what is at stake if herbicides are misused. Without any novel

herbicide SOAs on the immediate horizon, stewardship will be key in maintaining the resources

we currently have. Waterhemp is a formidable opponent, with a high ability to evolve and

compete with crops for yield. Resistance evolution in waterhemp is the survival of the fittest. I

hope this research can demonstrate to growers that the fittest cannot be allowed to survive when

it comes to controlling waterhemp and preserving chemical control options for the future.

3.6 Source of Materials

1Fisher Scientific Co. LLC, 4500 Turnberry Dr., Hanover Park, IL 60133

2Whatman No.1, Whatman International Ltd., Maidstone, England

3ImageJ, U.S. National Institutes of Health, Bethesda, MD 20892

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3.7 Table and Figures

Table 3.1 Pooled growth chamber dose-response data to

assess differences among waterhemp (Amaranthus

tuberculatus) populations. Estimated GR50 values are

expressed as S-metolachlor or acetochlor µM. Values

followed by their respective standard errors of the mean.

Population GR50

µM


M6 3.59 (±1)

NH40 1.46 (±0.34)

ACR 0.4 (±0.35)

WUS 1.8 (±1.12)


M6 2.71 (±2.52)

NH40 1.90 (±0.008)

ACR 3.31 (±8.87)

WUS 8.48 (±7.13)

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0 . 0 5 0 . 5 5 5 0 5 0 0

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

R a d i c l e E l o n g a t i o n

3 D A P

S-metolachlor ( M )

Ra

dic

le G

ro

wth

(%

of c

on

tr

ol)

M 6

W U S

A C R

N H 4 0

0

Figure 3.1 Radicle Inhibition in Response to S-metolachlor. Dose-response of four

waterhemp (Amaranthus tuberculatus) populations to S-metolachlor in herbicide treated agar.

Data collected 3 d after planting (DAP) in the form of radicle growth as a percentage of

untreated control. Lines in each graph were fitted using the equation (𝑦 = 𝑐 +

𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[𝑙𝑜𝑔(𝑥)−𝑙𝑜𝑔(𝐿𝐷50/𝐺𝑅50)]}) and each symbol represents the observed mean ±SE. M6,


line and open squares; WUS, discontinuous line and open circles.

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0 . 0 5 0 . 5 5 5 0 5 0 0

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

R a d i c l e E l o n g a t i o n

3 D A P

acetochlor ( M )

Ra

dic

le

G

ro

wth

(%

o

f c

on

tr

ol)

A C R

M 6

N H 4 0

W U S

Figure 3.2 Radicle Inhibition in Response to Acetochlor. Dose-response of four waterhemp

(Amaranthus tuberculatus) populations to acetochlor in herbicide treated agar. Data collected 3

d after planting (DAP) in the form of radicle growth as a percentage of untreated control. Lines

in each graph were fitted using the equation (𝑦 = 𝑐 +𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[𝑙𝑜𝑔(𝑥)−𝑙𝑜𝑔(𝐿𝐷50/𝐺𝑅50)]}) and each

symbol represents the observed mean ±SE. M6, continuous line and full squares; NH40,

Continuous line and full circles; ACR, discontinuous line and open squares; WUS, discontinuous

line and open circles.

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APENDIX A

SUMMARY DATA AND FIGURES FROM INITIAL CHLOROACETAMIDE

DOSE-RESPONSE EXPERIMENTS

Table A.1 Pooled greenhouse data from initial dose-response

experiments. Estimated LD50 and GR50 values are expressed as

S-metolachlor or acetochlor g ha-1. Values followed by their

respective standard errors of the mean.

Population LD50 GR50

─ g ha-1 ─


M6 2919 (±427) 239 (±48)

WUS 96 (±14) 29 (±6)


M6 170 (±39) 45 (±7)

WUS 33 (±4) 16 (±3)

Table A.2 Resistant to sensitive ratios (R:S)

from initial dose-response experiments to

assess differences in survival and biomass

accumulated 21 d after treatment (DAT).

Survival Biomass


M6:WUS 30.5 8.3


M6:WUS 5.1 2.8

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Figure A.1 Initial Dose-Response to S-metolachlor. Dose-response of two waterhemp

(Amaranthus tuberculatus) populations to S-metolachlor (M6, multiple herbicide-resistant

progeny from greenhouse crosses of plants from Champaign Co., IL site and WUS, a standard

known sensitive population). Data collected at 21 DAT (A) dry biomass as a percentage of

untreated control and (B) mean survival of waterhemp seedlings as a percentage of untreated

control. Lines in each graph were fitted using equation (𝑦 = 𝑐 +𝑑−𝑐

1+𝑒𝑥𝑝{𝑏[log(𝑥)−log(𝐿𝐷50/𝐺𝑅50)]})

and each symbol represents the observed mean ±SE. M6, continuous line and full squares;

WUS, discontinuous line and open circles.

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Figure A.2 Initial Dose-Response to Acetochlor. Dose-response of two waterhemp

(Amaranthus tuberculatus) populations to acetochlor (M6, multiple herbicide-resistant progeny

from greenhouse crosses of plants from Champaign Co., IL site and WUS, a standard known

sensitive population). Data collected at 21 DAT (A) dry biomass as a percentage of untreated

control and (B) mean survival of waterhemp seedlings as a percentage of untreated control.

Lines in each graph were fitted using equation (y = c +d−c

1+exp{b[log(x)−log(LD50/GR50)]}) and each

symbol represents the observed mean ±SE. M6, continuous line and full squares; WUS,

discontinuous line and open circles.

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