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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
ii
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.
iii
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.
iv
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
v
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.
vi
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
2.7 Literature Cited............................................................................................................56
vii
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
3.8 Literature Cited............................................................................................................83
APPENDIX A: SUMMARY DATA AND FIGURES FROM INITIAL
CHLOROACETAMIDE DOSE-RESPONSE EXPERIMENTS............................................87
1
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.
2
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).
3
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
4
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
5
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
7
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.
8
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).
9
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
10
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
11
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).
12
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
1.7 Literature Cited
Accinelli C, Dinelli G, Vicari A (2001) Atrazine and metolachlor degradation in subsoils. Biol
Fertil Soils 33:495–500
Alletto L, Coquet Y, Benoit P, Heddadj D, Barriuso E (2011) Tillage management effects on
pesticide fate in soils. In E. Lichtfouse, M. Hamelin, M. Navarrete and P. Debaeke. eds.
Sustainable Agriculture (2). Springer: Dordrecht, Heidelberg, London, New York.
doi:10.1007/978-94-007-0394-0.
Armstrong TF, Meggitt WF, Penner D (1973) Absorption, translocation, and metabolism of
alachlor by yellow nutsedge. Weed Sci 21:357–360
Bach L, Faure JD (2010) Role of very-long-chain fatty acids in plant development, when chain
length does matter. Comptes Rendus Biologies 333:361–370
Bader RR, Blaser HU (1997) Catalysis for agrochemicals: the case history of the Dual®
Herbicide. Heterogeneous Catalysis and Fine Chemicals 4:17–29
Baran N, Gourcy L (2013) Sorption and mineralization of S-metolachlor and its ionic metabolites
in soils and vadose zone solids: Consequences on groundwater quality in an alluvial
aquifer (Ain Plain, France). J of Contam Hydrol 154:20–28
Bailey AM, Coffey MD (1986) Characterization of microorganisms involved in accelerated
biodegradation of metalaxyl and metolachlor in soils. Can J Microiol 32: 562–569
Bedmar F, Daniel PE, Costa JL, Giménez D (2011) Sorption of acetochlor, S-metolachlor, and
atrazine in surface and subsurface soil horizons of Argentina. Environ Toxicol Chem
30:1990–1996
Bedos C, Cellier P, Calvet R, Barriuso E, Gabrielle B (2002) Mass transfer of pesticides into the
atmosphere by volatilization from soils and plants: overview. Agronomie 22:21–33
16
Bell MS, Hager AG, Tranel PJ (2013) Multiple resistance to herbicides from four site-of-action
groups in waterhemp (Amaranthus tuberculatus). Weed Sci 61:460–468
Bell MS, Tranel PJ (2010) Time requirement from pollination to seed maturity in waterhemp
(Amaranthus tuberculaatus). Weed Sci 58:167–173
Blaser HU, Buser HP, Coers K, Hanreich R, Jalett HP, Jelsch E, Pugin B, Schneider HD,
Spindler F, Wegmann A (1999) The chiral switch of metolachlor: the development of
large-scale enantioselective catalytic process. Chimia 53:275–280
Blaser HU, Spindler F (1997) Enantioselective catalysis for agrochemicals. The case histories of
(S)-metolachlor, (R)-metalaxyl and clozylacon. Top Catal 4:275–282
Böger P (2003) Mode of action for choroacetamides and functionally related compounds. J
Pestic Sci 28:324–329
Böger P, Matthes B, Schmalfuβ J (2000) Towards the primary target of chloroacetamides: new
findings pave the way. Pest Manag Sci 56: 497–508
Breaux EJ (1987) Initial metabolism of acetochlor in tolerant and susceptible seedlings. Weed
Sci 35:463–468
Buhler DD, Kohler KA, Thompson RL (2001) Weed seed bank dynamics during a five-year crop
rotation. Weed Technol 15:170–176
Buhler DD, Hartzler RG (2001) Emergence and persistence of seed of velvetleaf, common
waterhemp, woolly cupgrass, and giant foxtail. Weed Sci 49:230–235
Burnet WM, Barr AR, Powles SB (1994) Chloroacetamide resistance in rigid ryegrass (Lolium
rigidum). Weed Sci 42:153–157
Busi R, Gaines TA, Powles SB (2017) Phorate can reverse P450 metabolism-based herbicide
resistance in Lolium rigidum. Pest Manag Sci 73:410–417
17
Busi R, Powles SB (2016) Cross-resistance to prosulfocarb + S-metolachlor and pyroxasulfone
selected by either herbicide in Lolium rigidum. Pest Manag Sci 72:1664–1672
Chandler JM, Basler E, Santelmann PW (1974) Uptake and translocation of alachlor in soybean
and wheat. Weed Sci 22:253–258
Chesters G, Simsiman GV, Levy J, Alhajjar BJ, Fathulla RN, Harkin JM (1989) Environmental
fate of alachlor and metolachlor. Pages 1–64 in Ware GW, Nigg HN, Bevenue A, eds.
Reviews of Environmental Contamination and Toxicology (110). Springer-Verlag: New
York. doi: 10.1007/978-1-4684-7092-5
Davies J, Caseley JC (1999) Herbicide safeners: a review. Pestic Sci 55:1043–1058.
Deal LM, Hess FD (1980) An analysis of the growth inhibitory characteristics of alachlor and
metolachlor. Weed Sci 28:168–175
Dhillon NS, Anderson JL (1972) Morphological, anatomical, and biochemical effects of
propachlor on seedling growth. Weed Res 12:182–189
Duke WB, Slife FW, Hanson JB, Butler HS (1975) An investigation on the mechanism of action
of propachlor. Weed Sci 27:122–147
Ebert E (1982) The role of waxes in the uptake of metolachlor into sorghum in relation to the
protectant CGA-43089. Weed Res 22:305–311
Evans CM (2016) Characterization of a novel five-way-resistant population of waterhemp
(Amaranthus tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 106 p.
Evans JA, Tranel PJ, Hager AG, Schutte B, Wu C, Chatham LA, and Davis AS (2016) Managing
the evolution of herbicide resistance. Pest Manag Sci 72:74–80
Federle TW, Dobbins DC, Thorton-Manning JR (1986) Microbial biomass, activity, and
community structure in subsurface soil. Ground Water 24:365–374
18
Frear DS, Swanson HR (1970) Biosynthesis of S-(4-ethylamino-6-isopropyl-amino-2-s-triazino)
glutathione: Partial purification and properties of glutathione S-transferase from corn.
Phytochemistry 9:2123–2132
Fuerst EP (1987) Understanding the mode of action of chloroacetamides and thiocarbamate
herbicides. Weed Technol 1:270–277
Ghanevati M, Jaworski J (2002) Engineering and mechanistic studies of the Arabidopsis FAE1
the plasma membrane. Z Naturforsch 57c:843–852
Gish TJ, Prueger JH, Daughtry CST, Kustas WP, Mckee LG, Russ AL, Hatfield JL (2011)
Comparison of field-scale herbicide runoff and volatilization losses: an eight-year field
investigation. J Environ Qual 40:1432–1442
Gish TJ, Prueger JH, Kustas WP, Hatfield JL, McKee LG, Russ AL (2009) Soil moisture and
metolachlor volatilization observations over three years. J Environ Qual 38:1785–1795
Götz T, Böger P (2004) The very-long-chain fatty acid synthesis is inhibited by
chloroacetamides. Z Naturforsch 59:549–553
Gronwald JW (1989) Influence of herbicide safeners on herbicide metabolism. Pages 103–128 in
Hatzios K, ed. Crop Safeners for Herbicides: Development, Uses, and Mechanisms of
Action. London: Academic Press
Hager AG, Wax LM, Simmons FW, Stoller EW (1997) Waterhemp management in agronomic
crops. Univ. of Illinois Bulletin 855:12
Hager AG, Wax LM, Stoller EW, Bollero GA (2002) Common waterhemp (Amaranthus rudis)
interference in soybean. Weed Sci 50:607–610
Hamill AS, Penner D (1973) Interaction of alachlor and carbofuran. Weed Sci 21:330–335
19
Hamm PC (1974) Discovery, development, and current status of the choroacetamide herbicides.
Weed Sci 22:541–545
Hartzler RG, Bruce B, Nordby D (2004) Effect of common waterhemp (Amaranthus rudis)
emergence date on growth and fecundity in soybean. Weed Sci 52:242–245
Hartzler RG, Buhler DD, Stoltenberg DE (1999) Emergence characteristics of four annual weed
species. Weed Sci 47:578–584
Hatton PJ, Dixon D, Cole DJ, Edwards R (1996) Glutathione transferase activities and herbicide
selectivity in maize and associated weed species. Pestic. Sci 46: 267–275
Hatzios KK, Hoagland R (1989) Crop safeners for herbicides: Development, uses, and
mechanisms of action. San Diego, CA: Academic Press, Inc. doi:10.1016/B978-0-12-
332910-3.50009-6
Hausman NE (2012) Characterization of HPPD-inhibitor resistance in waterhemp (Amaranthus
tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 103 p.
Hausman NE, Tranel PJ, D. E. Riechers DE, Maxwell DJ, Gonzini LC, Hager AG (2013)
Responses of an HPPD inhibitor-resistant waterhemp (Amaranthus tuberculatus)
population to soil-residual herbicides. Weed Technol 27:704–711
Heap I (2017) The International Survey of Herbicide Resistant Weeds.
www.weedscience.org/in.asp Accessed November 9, 2017
Horak MJ, Loughin TM (2000) Growth analysis of four Amaranthus species. Weed Sci 48:347–
355
Horak MJ, Peterson DE, Chessman DJ, Wax LM (1994) Pigweed identification: A pictorial
guide to the common pigweeds of the Great Plains. Manhattan, KS: Kansas Cooperative
Extension Service Publication S80
20
Inoue MH, Santana DC, Oliveira Jr. RS, Clemente RA, Dallacort R, Possamai ACS, Santana
CTC, Perereira KM (2010) Potencial de lixiviação de herbicidas utilizados na cultura do
algodão em colunas del solo. Planta Daninha 28:825–833
Jablonkai I, Dutka F (1985) Metabolism of acetochlor herbicide in tolerant and sensitive plant
species. J Radioanal Nucl Chem Let 94:271–280
Jaworski EG (1956) Biochemical action of CDAA, a new herbicide. Science 123:847–848
Jaworski EG (1969) Analysis of the mode of action of herbicidal α-chloroacetamides. J Agric
Food Chem 17:165–170
Knake EL, Appleby AP, Furtick WR (1967) Soil incorporation and site of uptake of
preemergence herbicides. Weeds 15: 228–232
Kreuz K, Gaudin J, Ebert E (1989) Effects of safeners CGA 154281, oxabetrinil and fenclorim
on uptake and degradation of metolachlor in corn (Zea mays L.) seedlings. Weed Res
29:399–405
Krutz LJ, Senseman SA, Zablotowicz RM, Matocha MA (2005) Reducing herbicide runoff from
agricultural fields with vegetative filter strips: a review. Weed Sci 53:353–357
Long YH, Li RY, Wu XM (2014) Degradation of S-metolachlor in soil as affected by
environmental factors. J Soil Sci Plant Nutri 14:189–198
Loux MM, Doohan D, Dobbels AF, Johnson WG,Young BG, Legleiter TR, Hager A (2017)
Weed Control Guide for Ohio, Indiana, and Illinois. Ohio State University Extension.
Ma Y, Liu WP, Wen YZ (2006) Enantioselective degradation of Rac-metolachlor and S-
metolachlor in soil. Pedosphere 16:489–494
Mann JD, Jordan LS, Day BE (1965) A survey of herbicides for their effect upon protein
synthesis. Plant Physiol 40:840–843
21
Mann JD, Pu M (1968) Inhibition of lipid synthesis by certain herbicides. Weed Sci 16:197–198
Matthes B, Schmalfuβ J, Böger P (1998) Chloroacetamide mode of action, II: inhibition of very-
long-chain fatty acid synthesis in higher plants. Z Naturforsch 53c:1004–1011
McCarty P L, Reinhard M, Rittmann BE (1981) Trace organics in groundwater. Environ Sci
Technol 15:40–45
Moser H, Rihs G, Sauter HP, Böhner B (1983) Atropisomerism, chiral center and activity of
metolachlor. Pages 315–320 in Pesticide Chemistry: Human Welfare and Environment
Muller MD, Poiger T, Buser HR (2001) Isolation and identification of the metolachlor
stereoisomers using high performance liquid chromatography, polarimetric
measurements, and enantioselective gas chromatography. J Agric Food Chem 49:42–49
Murray MJ (1940) The genetics of sex determination in the family Amaranthaceae. Genetics
25:409–431
Nakatani M, Yoshihiro Y, Honda H, Uchida Y (2016) Development of the novel pre-emergence
herbicide pyroxasulfone. J Pestic Sci 41:107–112
Patzoldt WL, Tranel PJ, Hager AG (2005) A waterhemp (Amaranthus tuberculatus) biotype with
multiple resistance across three herbicide sites of action. Weed Sci 53:30–36
Pillai P, Davis DE, Truelove B (1979) Effects of metolachlor on germination, growth, leucine
uptake, and protein synthesis. Weed Sci 27:634–637
Prueger JH, Gish TJ, McConnell LL, McKee LG, Hatfield JL, Kustas WP (2005) Solar radiation,
relative humidity, and soil water effects on metolachlor volatilization. Environ Sci
Technol 39:5219–5226
22
Rice PJ, Anderson TA, Coats JR (2002) Degradation and persistence of metolachlor in soil:
effects of concentration, soil moisture, soil depth, and sterilization. Environ Toxicol
Chem 21:2640–2648
Riechers DE, Kreuz K, Zhang Q (2010) Detoxification without intoxication: herbicide safeners
activate plant defense gene expression. Plant Physiol 153:3–13
Riechers DE, Vaughn KC, Molin WT (2005) The role of plant glutathione S-transferases in
herbicide metabolism, in Environmental Fate and Safety Management of Agrochemicals.
Clark JM, Ohkawa H, eds. Washington DC: American Chemical Society. 216–232
doi:10.1021/bk-2005-0899.ch019
Riechers DE, Zhang Q, Xu F, Vaughn KC (2003) Tissue-specific expression and localization of
safener-induced glutathione S-transferase proteins in Triticum tauschii. Planta 217:831–
840 doi:10.1007/s00425-003-1063-y
Sanyal D, Kulshrestha G (1999) Effects of repeated metolachlor applications on its persistence in
field soil and degradation kinetics in mixed microbial cultures. Biol Fert Soils 30:124–
131
Sauer J (1955) Revision of the dioecious Amaranths. Madrono 13:5–46
Sauer J (1957) Recent migration and evolution of the dioecious Amaranths. Evolution 11:11–31
Scribner EA, Battaglin WA, Goolsby DA, EM Thurman (2000) Changes in herbicide
concentrations in Midwestern streams in relation to changes in use, 1989–1998. The
Science of the Total Environment. 248:255–263
Sellers BA, Smeda RJ, Johnson WG, Kendig JA, Ellersieck MR (2003) Comparative growth of
six Amaranthus species in Missouri. Weed Sci 51:329–333
23
Shaner DL, ed (2014) Herbicide Handbook. 10th edn. Lawrence, KS: Weed Science Society of
America. Pp 405–408
Shaner DL, Brunk G, Belles D, Westra P, Nissen S (2006) Soil dissipation and biological
activity of metolachlor and S-metolachlor in five soils. Pest Manag Sci 62:617–623
Shaner DL, Henry WB (2007) Field history and dissipation of atrazine and metolachlor in
Colorado. J Environ Qual 36:128–134
Shimabukuro RH, Lamoureux GL, Frear DS (1978) Glutathione conjugation: A mechanism for
herbicide detoxification and selectivity in plants. Pages 133–149 in Pallos FM, and
Casida JE, eds. Chemistry and Action of Herbicide Antidotes. Academic Press: New
York, San Fransisco, London.
Somerville GJ, Powles SB, Walsh MJ, Renton M (2017) Why was resistance to shorter-acting
pre-emergence herbicides slower to evolve? Pest Manag Sci 73:844–851
Sommer A, Böger P (1999) Characterization of recombinant corn glutathione S-transferase
isoforms I, II, III, and IV. Pestic Biochem Physiol 63:127–138
Steckel LE (2007) The dioecious Amaranthus spp.: here to stay. Weed Technol 21:567–570
Steckel LE, Sprague CL (2004) Common waterhemp (Amaranthus rudis) interference in corn.
Weed Sci 52:359–364
Steckel LE, Sprague CL, Hager AG (2002) Common waterhemp (Amaranthus rudis) control in
corn (Zea mays) with single preemergence and sequential applications of residual
herbicides. Weed Technol 16:755–761
Steckel LE, Sprague CL, Hager AG, Simmons FW, Bollero GA (2003) Effects of shading on
common waterhemp (Amaranthus rudis) growth and development. Weed Sci 51:898–903
24
Steckel LE, Sprague CL, Stoller EW, Wax LM, Simmons FW (2007) Tillage, cropping system,
and soil depth effects on common waterhemp (Amaranthus rudis) seed-bank persistence.
Weed Sci 55:235–239
Tanetani Y, Fujioka T, Kaku K, Shimizu T (2011) Studies on the inhibition of plant very-long-
chain fatty acid elongase by a novel herbicide pyroxasulfone. J Pesti Sci 36:221–228
Tanetani Y, Ikeda M, Kaku K, Shimizu T, Matsumoto H (2013) Role of metabolism in the
selectivity of a herbicide, pyroxasulfone, between wheat and rigid ryegrass seedlings. J
Pestic Sci 38:152–156
Tanetani Y, Kaku K, Kawai K, Fujioka T, Shimizu T (2009) Action of mechanism of a novel
herbicide, pyroxasulfone. Pestic Biochem Physiol 95:47–55
Weissshaar H, Böger P (1987) Primary effects of chloroacetamides. Pestic Biochem Physiol
28:286–293
Wu TL, Correll DL, Remenapp HE (1983) Herbicide runoff from experimental watersheds. J
Environ Qual 12:330–336
Wu XM, Li M, Long YH, Liu RX, Yu YL, Fang H, Li SN (2011) Effects of adsorption on
degradation and bioavailability of metolachlor in soil. J Soil Sci Plant Nutr 11:83–97
Zemolin CR, Avila LA, Cassol GV, Massey JH, Camargo ER (2014) Environmental fate of S-
metolaclor-a review. Planta Daninha 32:655–664
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
S-metolachlor (4) < acetochlor (2) 0.13 0.15 0.12
S-metolachlor (4) < acetochlor (4) 0.03 0.04 0.01
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,
continuous line and full squares; NH40, Continuous line and full circles; ACR, discontinuous
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
2.7 Literature Cited
Bach L, Faure JD (2010) Role of very-long-chain fatty acids in plant development, when chain
length does matter. Comptes Rendus Biologies 333:361–370
Beckie HJ, Tardif FJ (2012) Herbicide cross resistance in weeds. Crop Prot 35:15–28.
Bell MS, Hager AG, Tranel, PJ (2013) Multiple resistance to herbicides from four site-of-action
groups in waterhemp (Amaranthus tuberculatus). Weed Sci 61:460–468
Bell MS, Tranel PJ (2010) Time requirement from pollination to seed maturity in waterhemp
(Amaranthus tuberculaatus). Weed Sci 58:167–173
Böger P (2003) Mode of action for choroacetamides and functionally related compounds. J.
Pestic Sci 28:324–329
Breaux EJ (1987) Initial metabolism of acetochlor in tolerant and susceptible seedlings. Weed
Sci 35:463–468
Buhler DD, Hartzler RG (2001) Emergence and persistence of seed of velvetleaf, common
waterhemp, woolly cupgrass, and giant foxtail. Weed Sci 49:230–235
Burnet WM, Barr AR, Powles SB (1994) Chloroacetamide resistance in rigid ryegrass (Lolium
rigidum). Weed Sci 42:153–157
Busi R (2014) Resistance to herbicides inhibiting the biosynthesis of very-long-chain fatty acids.
Pest Manag Sci 70:1378–1384
Busi R, Gaines TA, Powles SB (2017) Phorate can reverse P450 metabolism-based herbicide
resistance in Lolium rigidum. Pest Manag Sci 73:410–417
Busi R, Gaines TA, Vila-Aiub MM, Powles SB (2014) Inheritance of evolved resistance to a
novel herbicide (pyroxasulfone). Plant Sci 217–218:127–134
57
Busi R, Powles SB (2016) Cross-resistance to prosulfocarb + S-metolachlor and pyroxasulfone
selected by either herbicide in Lolium rigidum. Pest Manag Sci 72:1664–1672
Deal LM, Hess FD (1980) An analysis of the growth inhibitory characteristics of alachlor and
metolachlor. Weed Sci 28: 168–175
Dhillon NS, Anderson JL (1972) Morphological, anatomical, and biochemical effects of
propachlor on seedling growth. Weed Res 12:182–189
Edwards R, Owen WJ (1989) The comparative metabolism of S-triazine herbicides atrazine and
terbutryne in suspension cultures of potato and wheat. Pestic Biochem Physiol 34:246–
254
Evans CM (2016) Characterization of a novel five-way-resistant population of waterhemp
(Amaranthus tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 106 p.
Evans JA, Tranel PJ, Hager AG, Schutte B, Wu C, Chatham LA, and Davis AS (2016) Managing
the evolution of herbicide resistance. Pest Manag Sci 72:74–80
Frear DS, Swanson HR (1970) Biosynthesis of S-(4-ethylamino-6-isopropyl-amino-2-s-triazino)
glutathione: Partial purification and properties of glutathione S-transferase from corn.
Phytochemistry 9:2123–2132
Fuerst EP (1987) Understanding the mode of action of chloroacetamides and thiocarbamate
herbicides. Weed Technol 1:270–277
Gronwald JW (1989) Influence of herbicide safeners on herbicide metabolism. Pages 103–128 in
Hatzios K, ed. Crop safeners for herbicides: Development, uses, and mechanisms of
action. London: Academic Press.
58
Hager AG, Wax LM, Bollero GA, Simmons FW (2002) Common waterhemp (Amaranthus rudis
Sauer) management with soil-applied herbicides in soybean (Glycine max (L.) Merr.).
Crop Protection 21:277–283.
Hager AG, Wax LM, Simmons FW, Stoller EW (1997) Waterhemp management in agronomic
crops. Univ. of Illinois Bulletin 855:12
Hager AG, Wax LM, Stoller EW, Bollero,GA (2002) Common waterhemp (Amaranthus rudis)
interference in soybean. Weed Sci 50:607–610
Hamm PC (1974) Discovery, development, and current status of the choroacetamide herbicides.
Weed Sci 22:541–545
Hartzler RG, Buhler DD, Stoltenberg DE (1999) Emergence characteristics of four annual weed
species. Weed Sci 47:578–584
Hatton PJ, Dixon D, Cole DJ, Edwards R (1996) Glutathione transferase activities and herbicide
selectivity in maize an associated weed species. Pestic. Sci 46: 267–275
Hausman NE (2012) Characterization of HPPD-inhibitor resistance in waterhemp (Amaranthus
tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 103 p.
Hausman NE, Singh S, Tranel PJ, Riechers DE, Kaundun SS, Polge ND, Thomas DA, Hager AG
(2011) Resistance to HPPD-inhibiting herbicides in a population of waterhemp
(Amaranthus tuberculatus) from Illinois, United States. Pest Manag Sci 67:258–261
Hausman NE, Tranel PJ, Riechers DE, Hager AG (2016) Response of a waterhemp (Amaranthus
tuberculatus) population resistant to HPPD-Inhibiting herbicides to foliar-applied
herbicides. Weed Technol 30:106–115
59
Hausman NE, Tranel PJ, D. E. Riechers DE, Maxwell DJ, Gonzini LC, Hager AG (2013)
Responses of an HPPD inhibitor-resistant waterhemp (Amaranthus tuberculatus)
population to soil-residual herbicides. Weed Technol 27:704–711
Heap I (2017) The International Survey of Herbicide Resistant Weeds.
www.weedscience.org/in.asp Accessed November. 9, 2017
Johnson WG, Chahal GS, Regehr DL (2012) Efficacy of various corn herbicides applied preplant
incorporated and preemergence. Weed Technol 26:220–229
Knezevic SZ, Streibig JC, Ritz C (2007) Utilizing R software package for dose-response studies:
the concept and data analysis. Weed Technol 21:840–848
Long YH, Li RY, Wu XM (2014) Degradation of S-metolachlor in soil as affected by
environmental factors. J Soil Sci Plant Nutr 14:189–198
Loux MM, Doohan D, Dobbels AF, Johnson WG,Young BG, Legleiter TR, Hager A (2017)
Weed Control Guide for Ohio, Indiana, and Illinois. Ohio State University Extension.
Ma R, Kaundun SS, Tranel PJ, Riggins CW, McGinness DL, Hager AG, Hawkes TH, McIndoe
E, Riechers DE (2013) Distinct detoxification mechanisms confer resistance to atrazine in
a population of waterhemp. Plant Physiol 163:363–377
Matthes B, Schmalfuβ J, Böger P (1998) Chloroacetamide mode of action, II: inhibition of very-
long-chain fatty acid synthesis in higher plants. Z Naturforsch 53c:1004–1011
Mithila J, Hall JC, Johnson WG, Kelley KB, Riechers DE (2011) Evolution of resistance to
auxinic herbicides: historical perspectives, mechanisms of resistance, and implications
for broadleaf weed management in agronomic crops. Weed Sci 59:445–457
60
Murray MJ (1940) The genetics of sex determination in the family Amaranthaceae. Genetics
25:409–431
Nakatani M, Yoshihiro Y, Honda H, Uchida Y (2016) Development of the novel pre-emergence
herbicide pyroxasulfone. J Pestic Sci 41:107–112
Oliveira MC, Jhala AJ, Gaines T, Irmak S, Amundsen K, Scott JE, Knezevic SZ (2017)
Confirmation and control of HPPD-inhibiting herbicide-resistant waterhemp
(Amaranthus tuberculatus) in Nebraska. Weed Technol 31:67–79
Patzoldt WL, Tranel PJ, Hager AG (2005) A waterhemp (Amaranthus tuberculatus) biotype with
multiple resistance across three herbicide sites of action. Weed Sci 53:30–36
Pillai P, Davis DE, Truelove B (1979) Effects of metolachlor on germination, growth, leucine
uptake, and protein synthesis. Weed Sci 27:634–637
Riechers DE, Kreuz K, Zhang Q (2010) Detoxification without intoxication: herbicide safeners
activate plant defense gene expression. Plant Physiol 153:3–13
Sanyal D, Kulshrestha G (1999) Effects of repeated metolachlor applications on its persistence in
field soil and degradation kinetics in mixed microbial cultures. Biol Fert Soils 30:124–
131
Sauer J (1955) Revision of the dioecious Amaranths. Madrono 13:5–46
Saxton AM (1998) A macro for converting mean separation output to letter groupings in Proc
Mixed. Proc Annu SAS Users Group Int 23:1243–1246
Shaner DL, Brunk G, Belles D, Westra P, Nissen S (2006) Soil dissipation and biological
activity of metolachlor and S-metolachlor in five soils. Pest Manag Sci 62:617–623
61
Shaner DL, Henry WB (2007) Field history and dissipation of atrazine and metolachlor in
Colorado. J Environ Qual 36:128–134
Somerville GJ, Powles SB, Walsh MJ, Renton M (2017) Why was resistance to shorter-acting
pre-emergence herbicides slower to evolve? Pest Manag Sci 73:844–851
Steckel LE (2007) The dioecious Amaranthus spp.:here to stay. Weed Technol 21:567–570
Steckel LE, Sprague CL (2004) Common waterhemp (Amaranthus rudis) interference in corn.
Weed Sci 52:359–364
Steckel LE, Sprague CL, Hager AG (2002) Common waterhemp (Amaranthus rudis) control in
corn (Zea mays) with single preemergence and sequential applications of residual
herbicides. Weed Technol 16:755–761
Steckel LE, Sprague CL, Hager AG, Simmons FW, Bollero GA (2003) Effects of shading on
common waterhemp (Amaranthus rudis) growth and development. Weed Sci 51:898–903
Tanetani Y, Fujioka T, Kaku K, Shimizu T (2011) Studies on the inhibition of plant very-long-
chain fatty acid elongase by a novel herbicide pyroxasulfone. J Pesti Sci 36:221–228
Tanetani Y, Kaku K, Kawai K, Fujioka T, Shimizu T (2009) Action of mechanism of a novel
herbicide, pyroxasulfone. Pestic Biochem Physiol 95:47–55
Trenkamp S, Martin W, Tietjen K (2004) Specific and differential inhibition of very-long-chain
fatty acid elongases from Arabidopsis thaliana by different herbicides. Proc Natl Acad
Sci USA 101:11903–11908
Werck-Reichhart D, Hehn A, Didierjean L (2000) Cytochromes P450 for engineering herbicide
tolerance. Trends Plant Sci 5:116–123
62
Wu XM, Li M, Long YH, Liu RX, Yu YL, Fang H, Li SN (2011) Effects of adsorption on
degradation and bioavailability of metolachlor in soil. J Soil Sci Plant Nutr 11:83–97
Yu Q, Powles SA (2014) Metabolism-based herbicide resistance and cross-resistance in crop
weeds: a threat to herbicide sustainability and global crop production. Plant Physiol
166:1106–1118
63
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
65
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
66
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
74
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.
75
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
76
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
77
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.
79
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
80
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
Response to S-metolachlor
M6 3.59 (±1)
NH40 1.46 (±0.34)
ACR 0.4 (±0.35)
WUS 1.8 (±1.12)
Response to acetochlor
M6 2.71 (±2.52)
NH40 1.90 (±0.008)
ACR 3.31 (±8.87)
WUS 8.48 (±7.13)
81
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,
continuous line and full squares; NH40, Continuous line and full circles; ACR, discontinuous
line and open squares; WUS, discontinuous line and open circles.
82
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.
83
3.8 Literature Cited
Bach L, Faure JD (2010) Role of very-long-chain fatty acids in plant development, when chain
length does matter. Comptes Rendus Biologies. 333:361–370
Bell MS, Hager AG, Tranel PJ (2013) Multiple resistance to herbicides from four site-of-action
groups in waterhemp (Amaranthus tuberculatus). Weed Sci. 61:460–468
Böger P (2003) Mode of action for choroacetamides and functionally related compounds. J.
Pestic. Sci. 28:324–329
Breaux EJ (1987) Initial metabolism of acetochlor intolerant and susceptible seedlings. Weed
Sci. 35:463–468
Buhler DD, Hartzler RG (2001) Emergence and persistence of seed of velvetleaf, common
waterhemp, woolly cupgrass, and giant foxtail. Weed Sci. 49:230–235
Busi R (2014) Resistance to herbicides inhibiting the biosynthesis of very-long-chain fatty acids.
Pest Manag. Sci. 70:1378–1384
Busi R, Gaines TA, Powles SB (2017) Phorate can reverse P450 metabolism-based herbicide
resistance in Lolium Rigidum. Pest Manag. Sci. 73:410–417
Deal LM, Hess FD (1980) An analysis of the growth inhibitory characteristics of alachlor and
metolachlor. Weed Sci. 28:168–175
Dhillon NS, Anderson JL (1972) Morphological, anatomical, and biochemical effects of
propachlor on seedling growth. Weed Res. 12:182–189
Duke WB, Slife FW, Hanson JB, Butler HS (1975) An investigation on the mechanism of action
of propachlor. Weed Sci. 27:122–147
84
Evans CM (2016) Characterization of a novel five-way-resistant population of waterhemp
(Amaranthus tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 106 p.
Evans JA, Tranel PJ, Hager AG, Schutte B, Wu C, Chatham LA, Davis AS (2016) Managing the
evolution of herbicide resistance. Pest Manag. Sci. 72:74–80
Fuerst EP (1987) Understanding the mode of action of chloroacetamides and thiocarbamate
herbicides. Weed Technol. 1:270–277
Gronwald JW (1989) Influence of herbicide safeners on herbicide metabolism. Pages 103–128 in
Hatzios K., ed. Crop Safeners for Herbicides: Development, Uses, and Mechanisms of
Action. London: Academic Press
Hamm PC (1974) Discovery, development, and current status of the choroacetamide herbicides.
Weed Sci. 22:541–545
Hager AG, Wax LM, Simmons FW, Stoller EW (1997) Waterhemp management in agronomic
crops. Univ. of Illinois Bulletin 855:12
Hager AG, Wax LM, Stoller EW, Bollero GA (2002) Common waterhemp (Amaranthus rudis)
interference in soybean. Weed Sci. 50:607–610
Hartzler RG, Buhler DD, Stoltenberg DE (1999) Emergence characteristics of four annual weed
species. Weed Sci 47:578–584
Hausman NE (2012) Characterization of HPPD-inhibitor resistance in waterhemp (Amaranthus
tuberculatus). Master’s thesis. Urbana, IL: University of Illinois. 103 p.
Hausman NE, Tranel PJ, Riechers DE, Hager AG (2016) Response of a waterhemp (Amaranthus
tuberculatus) population resistant to HPPD-Inhibiting herbicides to foliar-applied
herbicides. Weed Technol 30:106–115
85
Hausman NE, Tranel PJ, Riechers DE, Maxwell DJ, Gonzini LC, Hager AG (2013) Responses
of an HPPD inhibitor-resistant waterhemp (Amaranthus tuberculatus) population to soil-
residual herbicides. Weed Technol 27:704–711
Heap I (2017) The International Survey of Herbicide Resistant Weeds.
www.weedscience.org/in.asp Accessed November. 9, 2017
Hiller E, Čerňanský S, Krascenits Z, Milička J (2009) Effect of soil and sediment composition on
acetochlor sorption and desorption. Environ Sci Pollut Res 16:546–554
Jaworski EG (1956) Biochemical action of CDAA, a new herbicide. Science 123:847–848
Knezevic SZ, Streibig JC, Ritz C (2007) Utilizing R software package for dose-response studies:
the concept and data analysis. Weed Technol 21:840–848
Ma R, Kaundun SS, Tranel PJ, Riggins CW, McGinness DL, Hager AG, Hawkes TH, McIndoe
E, Riechers DE (2013) Distinct detoxification mechanisms confer resistance to atrazine in
a population of waterhemp. Plant Physiol 163:363–377
Ma Y, Liu WP, Wen (2006) Enantioselective degradation of Rac-metolaclor and S-metolachlor
in soil. Pedosphere. 16:489–494
Matthes B, Schmalfuβ J, Böger P (1998) Chloroacetamide mode of action, II: inhibition of very-
long-chain fatty acid synthesis in higher plants. Z Naturforsch 53c:1004–1011
Murray MJ (1940) The genetics of sex determination in the family Amaranthaceae. Genetics
25:409–431
Patzoldt WL, Tranel PJ, Hager AG (2005) A waterhemp (Amaranthus tuberculatus) biotype with
multiple resistance across three herbicide sites of action. Weed Sci 53:30–36
86
Pillai P, Davis DE, Truelove B (1979) Effects of metolachlor on germination, growth, leucine
uptake, and protein synthesis. Weed Sci 27:634–637
Sauer J (1955) Revision of the dioecious Amaranths. Madrono 13:5–46
Sauer J (1957) Recent migration and evolution of the dioecious Amaranths. Evolution 11:11–31
Shaner DL, Brunk G, Belles D, Westra P, Nissen S (2006) Soil dissipation and biological
activity of metolachlor and S-metolachlor in five soils. Pest Manag Sci 62:617–623
Sloan ME, Camper ND (1986) Effects of alachlor and metolachlor on cucumber seedlings.
Environmental and Experimental Botany. 26:1–7
Steckel LE (2007) The dioecious Amaranthus spp.:here to stay. Weed Technol 21:567–570
Steckel LE, Sprague CL (2004) Common waterhemp (Amaranthus rudis) interference in corn.
Weed Sci 52:359–364
Steckel LE, Sprague CL, Hager AG, Simmons FW, Bollero GA (2003) Effects of shading on
common waterhemp (Amaranthus rudis) growth and development. Weed Sci 51:898–903
Wu XM, Li M, Long YH, Liu RX, Yu YL, Fang H, Li SN (2011) Effects of adsorption on
degradation and bioavailability of metolachlor in soil. J Soil Sci Plant Nutr 11:83–97
Zemolin CR, Avila LA, Cassol GV, Massey JH, Camargo ER (2014) Environmental fate of S-
metolachlor-a review. Planta Daninha. 32:655–664
87
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 ─
Response to S-metolachlor
M6 2919 (±427) 239 (±48)
WUS 96 (±14) 29 (±6)
Response to acetochlor
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
Response to S-metolachlor
M6:WUS 30.5 8.3
Response to acetochlor
M6:WUS 5.1 2.8
88
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.
89
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.