Influence of Herbicide Programs, Weed Height, And

INFLUENCE OF HERBICIDE PROGRAMS, WEED HEIGHT, AND

GLUFOSINATE AND 2,4-D COMBINATIONS ON WEED MANAGEMENT IN

SOYBEAN RESISTANT TO 2,4-D

A Thesis Presented to The Faculty of the Graduate School At the University of Missouri

In Partial Fulfillment Of the Requirements for the Degree Master of Science in Plant Sciences

By BRETT DOUGLASS CRAIGMYLE

Dr. Kevin Bradley, Thesis Supervisor

May 2012

The undersigned, appointed by the dean of the Graduate School, have examined the Thesis entitled INFLUENCE OF HERBICIDE PROGRAMS, WEED HEIGHT, AND GLUFOSINATE

AND 2,4-D COMBINATIONS ON WEED MANAGEMENT IN SOYBEAN

RESISTANT TO 2,4-D

Presented by BRETT DOUGLASS CRAIGMYLE A candidate for the degree of Master of Science in Plant Sciences And hereby certify that, in their opinion, it is worthy of acceptance.

Dr. Kevin W. Bradley

Dr. Reid J. Smeda

Dr. William J. Wiebold

Dr. Jeffrey M. Ellis

ACKNOWLEDGEMENTS

First and foremost I would like to thank my advisor Dr. Kevin Bradley for all of his wisdom, guidance, and support. I feel honored to have been able to study under such a hard working and motivated individual with such desire to see his graduate students succeed. Thank you for your time and patience you have put into my research projects, talks, and writings it has truly been a great learning experience and a big milestone in my life. I would also not be where I am today without the help of my committee, Dr. Reid

Smeda, Dr. William Wiebold, and Dr. Jeff Ellis.

I would also like to thank our technicians, Jim Wait, Travis Legleiter and Eric

Riley, along with my fellow colleagues in the graduate office: Kristen Rosenbaum, Bryan

Sather, Doug Spaunhorst, Craig Solomon, and Brock Waggoner. Whether it be the keen eye to see an error in the wonderful SAS program or daily entertainment, you have made my experience here enjoyable and I wish you all the best of luck in your endeavors. I would also like to thank all of the undergraduate students that have helped with my research and made this graduation happen in a timely fashion. I realize those long hot days with a hoe in hand, or dripping with sweat from long hours in the greenhouse isn’t fun, but it really is greatly appreciated.

Most importantly I would like to thank my family who has been there supporting me, pushing me, and driving me to be the best individual I can be. I can honestly say I couldn’t have gotten this far without them. Mom and Dad, I am fortunate to have been raised with such great values, work ethic, and love as you have given me.

TABLE OF CONTENTS

Acknowledgements ...... ii

List of tables……………...... iv

Chapter

I. Literature Review ...... 1

Justification ...... 1 Introduction ...... 3 2,4-D (2,4-dichlorophenoxyacetic acid) ...... 3 2,4-D Rates and Combinations ...... 6 Glyphosate-Resistant Weeds ...... 8 Introduction and Utility of 2,4-D Resistance Trait in Soybean ...... 12 Summary and Objectives ...... 13 Literature Cited ...... 14

II. Influence of Herbicide Programs on Weed Management in Soybeans with Resistance to Glufosinate and 2,4-D ...... 20

Abstract ...... 20 Introduction ...... 21 Materials and Methods ...... 24 Results and Discussion ...... 27 Literature Cited ...... 33

III. Influence of Weed Height and Glufosinate Plus 2,4-D Combinations on Weed Control in 2,4-D Resistant Soybeans ...... 46

Abstract ...... 46 Introduction ...... 47 Materials and Methods ...... 51 Results and Discussion ...... 55 Literature Cited ...... 66

iii

LIST OF TABLES

Chapter I

Influence of Herbicide Programs on Weed Management in Soybean with Resistance

to Glufosinate and 2,4-D

Table 2.1 Monthly rainfall (mm) and average monthly temperatures (C) from .. April through October in 2010 and 2011 in comparison to the 30-year average in Boone and Callaway counties in Missouri ...... 37

Table 2.2 Dates of major field operations along with soybean growth stage and weed sizes at the time of the herbicide applications at the Boone County and Calloway County sites in 2010 and 2011 ...... 38

Table 2.3 Influence of herbicide programs containing glufosinate or glufosinate plus 2,4-D on late-season annual grass and broadleaf weed control across four site-years in Missouri...... 39

Table 2.4 Comparison of herbicide programs containing glufosinate plus 2,4-D on late-season annual grass and broadleaf weed control across four site-years in Missouri ...... 42

Table 2.5 Influence of herbicide programs that contain glufosinate or glufosinate plus 2,4-D on soybean yield across four site-years in Missouri ...... 43

Table 2.6 Comparison of herbicide programs containing glufosinate plus 2,4-D on soybean yield across four site-years in Missouri ...... 45

Chapter II

Influence of Weed Height and Glufosinate Plus 2,4-D Combinations on Weed

Control in 2,4-D Resistant Soybean

Table 3.1 Dates of major field operations and soybean growth stage and weed height at the time of each herbicide applicatoin at the Boone and Calloway County sites in 2010 and 2011 ...... 72 iv

Table 3.2 Influence of weed height and glufosinate plus 2,4-D rate combinations on late season annual grass and broadleaf weed control across four site-years in Missouri ...... 73

Table 3.3 Comparison of sequential POST programs containing glufosinate or glufosinate plus 2,4-D on late season annual grass and broadleaf weed control across four site-years in Missouri ...... 74

Table 3.4 Soybean yield response to sequential POST programs containing glufosinate or glufosinate plus 2,4-D across four site-years in Missouri .. 75

Table 3.5 Comparison of sequential POST programs containing glufosinate or glufosinate plus 2,4-D on soybean yield across four site-years in Missouri ...... 76

Table 3.6 Control of 15 and 30 cm dicot plants 3 WAT with glufosinate and 2,4-D alone and in combination in greenhouse experiments ...... 77

Table 3.7 Control of 15 and 30 cm monocot plants 3 WAT with glufosinate and 2,4-D alone and in combination in greenhouse experiments ...... 78

CHAPTER I

LITERATURE REVIEW

Justification.

Farm expenses hit a record high in 2007 increasing by 9.3 percent from 2006. In

2008, farm expenses rose yet again by another 8.3 percent from 2007. These increases in production expenses were in direct response to increased inputs for fuel, fertilizers, and pesticides (USDA 2008; USDA 2009c). Farm expenses for 2010 are expected to be at the second highest level ever recorded, rising to 281.4 billion dollars (USDA 2010).

With recent increased production costs, farmers have adopted no-tillage systems, which yield environmental and economic benefits. This widely adopted farming technique allows farmers to reduce fuel, labor, and machinery costs while reducing soil erosion

(Doran et al 1984; Gebhardt et al. 1985). With no-tillage systems in place, farmers use non-selective pre-plant (PP) and residual herbicides in order to start with a clean, weed- free field which allows the crop to gain a competitive advantage over weeds (Krausz et al. 1993). In the past decade, soybean (Glycine max L.) production has increased from

28.3 million hectares to 31.4 million hectares, respectively (USDA 2009b). With this increase in hectares and concomitant increase of no-till practices, the adoption of glyphosate-resistant (GR) crop technology has also increased (USDA 2009b). In the early 1970’s, glyphosate was brought into the market for broad spectrum weed control

1 but was only available as a pre-emergent burndown (Woodburn 2000). In 1996, GR soybean were introduced which allowed growers to apply glyphosate directly to their crop. In the United States, the hectares of GR soybean increased 13% in 1996 to 88% in

2005 (Sankula 2006). Unfortunately, the overuse of this active ingredient over the last several years has led to the selection of weed populations that are resistant to glyphosate

(Heap 2010). Current weeds that are resistant to glyphosate in the United States include annual bluegrass (Poa annua L.), common ragweed (Ambrosia artemisiifolia L.), common waterhemp (Amarathus rudis Sauer.), giant ragweed (Ambrosia trifida L.), goosegrass (Eleusine indica L. Gaertn.), hairy fleabane (Conyza bonariensis L. Cronq.), horseweed (Conyza Canadensis L. Cronq.), Italian ryegrass (Lolium multiflorum Lam.

Husnot), johnsongrass (Sorghum halepense L. Pers.), junglerice (Echinochloa colona L.

Link.), kochia (Kochia scoparia L. Schrad.), palmer amaranth (Amaranthus palmeri S.

Wats.), and rigid ryegrass (Lolium rigidum Gaudin.) (Heap 2010).

One option for the control of GR broadleaf weeds is 2,4-D (Loux 2008). This growth regulator is an extremely important herbicide used in a variety of agronomic crops and has activity on broadleaf weeds which have become resistant to glyphosate. In current soybean systems, waiting periods before planting must be taken into consideration when applying 2,4-D. The ester salt of 2,4-D is restricted to pre-plant applications at least 7 DBP in soybean when using 0.56 kg/Ha, while amine formulations require a 15 day waiting period. A longer interval between application and planting is required if rates exceed 0.56 kg/Ha (Anonymous 2010). However, Dow AgroSciences

LLC is currently developing corn, soybean, and cotton with a trait that confers resistance to pre-plant or postemergence (POST) applications of 2,4-D. This new trait should

2 present growers with new options for the control of GR weeds and eliminate planting restrictions in either of these crops. This research will be conducted to better understand the utility of the 2,4-D resistance trait in current soybean production systems.

Specifically, the objectives of this research are to: 1) compare the efficacy and utility of

2,4-D-containing herbicide programs in soybean transformed with the glufosinate- and

2,4-D resistance trait with current standards used in glufosinate-resistant soybean systems, 2) determine the influence of weed height and glufosinate plus 2,4-D rate combinations on summer annual grass and broadleaf weed control in soybean with resistance to glufosinate and 2,4-D and 3) determine if antagonistic, synergistic, or additive responses occur on summer annual weed species with various glufosinate and

2,4-D combinations.

INTRODUCTION

2,4-D (2,4-dichlorophenoxyacetic acid)

In 1942, Franklin D. Jones invented 2,4-D while searching for a way to kill poison ivy (Industry Task Force II 2005). The phenoxy-carboxylic selective herbicide

2,4-D is the synthetic version of indoleacetic acid (IAA) which is a naturally occurring plant growth hormone (Industry Task Force II 2005). This herbicide kills susceptible broadleaf plants by mimicking the plant’s own hormones which are present in the meristematic regions of plants above and below ground. Growth regulator herbicides cause unorganized growth that actually crushes the plant’s vascular system, thus blocking the transport of nutrients, sugars, and water. Many people refer to this action as the plant growing itself to death (Anderson 2005). This disruption of biochemical processes occurs when 2,4-D is applied to susceptible plants and leads to epinasty, ethylene evolution, 3 chloroplast damage, changes in cell wall integrity, and increased biosynthesis (Ashton and Crafts 1981). With World War II occurring at the same time as the discovery of 2,4-

D, it was first planned to be used for military purposes, but the war ended before it could be put to use. The herbicidal properties of 2,4-D were patented on December 11, 1945, and this herbicide was first introduced commercially in 1946 by companies such as Dow

Chemical, Sherwin-Williams, and the American Chemical Paint Company (Anderson

2005). Up until recently, 2,4-D was the most widely used herbicide in the United States for the control of annual, biennial, and perennial broadleaf weeds in a wide variety of crops such as wheat, grain sorghum, corn, rice, sugarcane, and soybean. Even today, after more than 60 years of use, 2,4-D is still the third most widely used herbicide in the

United States, and the most widely used herbicide in the world. (Industry Task Force II

2005). The Environmental Protection Agency (EPA) designated that the United States

Department of Agriculture (USDA) complete a benefits assessment to determine the economic implications of a complete ban of this herbicide on agricultural productivity

(Szmedra 1997). In response, the USDA and National Agriculture Pesticide Impact

Assessment Program (NAPIAP) projected economic losses of approximately $1.3 billion in crops such as corn, wheat, barley, peanut, alfalfa, apple and strawberry as a result of the loss of 2,4-D (Szmedra 1997).

The environmental fate of 2,4-D has also been studied extensively since its initial release in 1946. An expert review of 2,4-D prepared for the British Columbia Ministry of

Forests stated that 2,4-D is possibly the most extensively researched of all pesticides, and the data has been examined by an unusual number of advisory committees and working groups (Industry Task Force 2005). Field dissipation studies across the U.S. showed that

4 less than 5% of the applied 2,4-D moved down more than 15-cm in the soil profile, proving that 2,4-D is rather immobile in the soil. In addition to its lack of mobility, 2,4-

D has a rather short half-life of 10 days on average (WSSA 2007). This is thought to be related directly to the amount of microorganisms within the soil as 2,4-D dissipation is directly related to microbial biomass and organic matter content within a given soil

(Voos and Groffman 1997).

Not only has 2,4-D been researched extensively in plants, the translocation, degradation, and toxicity of 2,4-D has also been investigated thoroughly in mammals. In

1993, the EPA reported concerns on the health effects of farm workers as a result of exposure to 2,4-D and phenoxy class herbicides. On August 8, 2005 the EPA concluded that 2,4-D does not pose human health concerns when users follow product instructions

(Industry Task Force II 2005). The Industry Task Force (2005) went on to conclude that

2,4-D is rapidly and completely excreted in urine by humans when absorbed.

There are two main formulations of 2,4-D used in agriculture today, the amine and ester. Amine and ester formulations differ in that the esters have a higher vapor pressure and tend to be more susceptible to volatilization. Volatilization is a herbicides ability to turn into a vapor and move off site (Nice et al. 2004). Nice et al. (2004) reported that esters tend to act on susceptible weeds quicker because they are more soluble and are able to penetrate through the plant’s cuticle better than an amine.

Soybean are one crop that are susceptible to low levels of 2,4-D, from either drift, tank contamination, volatilization, or residual soil uptake. Krausz (1993) showed that when growers spray auxin-type herbicides sooner than the recommended time after an early preplant application, emerging soybean can come into contact with these herbicides and

5 the crop can suffer significant injury. A three year study conducted by Kelley et al.

(2005) showed that rates of 0.56 and 1.80 kg/Ha of 2,4-D applied at the V3, V7, and R2 stages injured soybean from 8- to- 49 % in the V3 stage, 22 and 52% in V7 stage, and 19 to 37% in the R2 stage. Yields were reduced by 15- to- 25% from the higher rates at all growth stages. To avoid possible injury to these susceptible plants, the use of low volatile ester formulations of 2,4-D is often recommended for pre-plant applications in reduced tillage soybean systems (Owen 1998). Amine salts are preferred when volatilization is of concern and are often used in hot, dry conditions. However, amines are known to be more water soluble, and root uptake is more likely.

Woodford (1952) stated that 2,4-D is absorbed easily in plants either through their roots or vegetative organs. It has been shown that 2,4-D passes through the leaf cuticle and epidermal cells, then moves within the mesophyll tissue into the phloem where it is translocated with the products of photosynthesis (Woodford 1952). Also, when taken up by the root, 2,4-D moves via the transpiration stream through the xylem (Woodford

1952).

2,4-D Rates and Combinations

Weed control is one of the most important factors affecting crop yields. Weeds not controlled by herbicides may increase yield losses by $15.5 billion/year in the United

States (Bridges 1992). A study done by Gianessi and Reigner (2007) found that U.S. crop production would decline by 135 billion kg of food and fiber if herbicides were not used for weed control.

Today, the most effective and most widely used tactic for weed control is the application of a herbicide. Adequate control of weeds requires specific timing to ensure

6 the highest level of weed control throughout the growing season. Several studies have shown that early-season weed control is critical in achieving maximum yields (Oliver

1988). Other studies have shown that plant size and growth stage are both factors that influence the degree of weed control with 2,4-D. A two year study conducted by Everitt and Keeling (2007) in cotton found that 2,4-D at rates of 0.56 and 1.12 kg/Ha controlled

3- to 8-cm horseweed by at least 92%, 28 days after treatment (DAT). However, in this same research, much poorer control of horseweed was observed when these rates of 2,4-

D were applied on 10- to 15-cm and 25- to 46-cm tall horseweed. Weed control at these growth stages never exceeded 73% at either rate. Similar results have been found with ragweed parthenium (Parthenium hysterophorus). Control of 2- to 7-cm tall ragweed parthenium with 2,4-D at 0.806 kg/Ha resulted in 90% control, but when applied to 42- to 90-cm plants, only 70% control was achieved (Reddy et al. 2007).

Application rate is another important factor that often determines the level of weed control achieved with 2,4-D. With the occurrence of GR horseweed in 16 states throughout the U.S., the inclusion of 2,4-D with glyphosate has become a standard recommendation for the control of this species (Heap 2010). For example, Eubank et al.

(2008) found that horseweed control increased from 73% with a glyphosate application to greater than 90% control with the addition of 2,4-D at 0.84 kg/Ha.

Synergism is an agrochemical’s ability to interact with one another and have beneficial outcomes. These benefits include increased weed control, decreased usage rates, and diminished toxicity on non-target plants in herbicide combinations rather than in individual applications. Antagonism is when agrochemicals have adverse affects when combined together than when applied separately (Hatzios et al. 1985; Akobundu et al.

1975). Some authors have observed a synergistic response between certain herbicides and 2,4-D (Waltz et al. 2003), while others have reported antagonistic interactions.

Steckel et al. (2006) found that GR horseweed control with glufosinate prior to no-till cotton planting was increased with the addition of 2,4-D. Gufosinate at 0.47 kg/Ha plus

2,4-D at 0.53 kg/Ha resulted in greater horseweed control than glufosinate alone 56 days after treatment, and also provided some residual control compared to glufosinate alone

(Steckel et al. 2006). Conflicting results have also been reported with 2,4-D and ALS- inhibiting herbicide combinations. Hart (1997) indicated that growth regulator herbicides for POST broadleaf weed control complement ALS-inhibitors. In a study conducted with halosulfuron on common lambsquarters it was shown that halosulfuron by itself did not control common lambsquarters. However, when mixed with 2,4-D at 0.017-, 0.035-, and

0.070-kg/Ha, common lambsquarters (Chenopodium album L.), control increased with the addition of 2,4-D (Isaacs et al. 2006). Similarly, Bradley et al. (2003) observed poorer control of trumpetcreeper (Campsis radicans L. Seem. Ex Bureau) in corn when sulfonylurea herbicides were applied alone compared to applications of these sulfonylureas with 2,4-D. However, an antagonistic response has been observed with johnsongrass when imazethapyr plus imazapyr were mixed with 2,4-D ester (Martin et al.

2007).

Glyphosate-Resistant Weeds

Some 30 years after the introduction of 2,4-D, glyphosate was introduced and provided farmers with a new tool for weed control (Givens et al. 2009). Growth regulators like 2,4-D were great for broadleaf plants, but now growers had a herbicide that would provide broad-spectrum control of both broadleaf and monocot plants in a safe

8 and effective manner. The initial reason for the introduction of glyphosate was

Monsanto’s desire to control perennial weeds. These initial ideas have since expanded into a variety of uses (Magin 2003). To this day, this molecule is still the fastest growing and largest selling chemical on the market (Green et al. 2008). Glyphosate is labeled for the control of over 300 annual, perennial and biennial grasses, sedges, and broadleaves, as well as woody brush and trees at various timings without any residual soil activity or re-cropping restrictions (Green et al. 2008).

At least one glyphosate application is currently applied to more than 90% of the field crop acreage in the United States (USDA 2009a). This highly adaptive herbicide has been widely accepted due to its compatibility with conservation tillage systems, broad-spectrum control of numerous weed species, applicator safety, lack of soil activity, and ease of broad-spectrum POST weed control with few tank mixtures (Mueller et al.

2005; Grichar and Prostko 2009). In 1996, the first commercially available GR soybean variety was introduced. Grower adoption of these systems increased rapidly and was used on more than 91% of soybean hectares planted by 2009 (USDA. 2009a). However,

GR crops have indirectly impacted our agroecosystem by reducing the number of alternative herbicide applications made by growers (Noris 2005; Owen 2008). Growers have relied exclusively on glyphosate for weed control in soybean and the use of tank mixtures and sequential applications of more than one herbicide has declined (Young

2006). The number of different herbicide sites of action (represented by a herbicide used on 10% or more of soybean hectares) declined from seven in 1995 to one in 2002 (Young

2006).

The overuse of glyphosate has also resulted in weed population shifts (Meuller et al. 2005; Owen 2008). A weed population shift can include either evolved herbicide- resistant weed populations or naturally tolerant weed populations which developed as a result of the selection pressure imposed by the crop production system (Owen 2008). As defined by the Weed Science Society of America (2008), resistance “is the inherited ability of a plant to survive and reproduce following exposure to a dose of herbicide normally lethal to the wild type.” In 1996, the first GR weed, rigid ryegrass, was discovered after 14 years of continuous glyphosate usage. Since that time, 16 GR weeds have been discovered worldwide, with 10 of these being of concern in the Midwestern

United States (Heap 2010). In Georgia, after four years of continuous use of glyphosate as a POST herbicide in GR cotton, glyphosate resistance was discovered in Palmer amaranth. Glyphosate-resistant horseweed and common ragweed were found to be resistant after three and six years, respectively, of continuous applications of glyphosate in GR soybean (Pollard et al. 2004; VanGessel 2001). However, one of the most troublesome weeds which have become resistant to glyphosate is the highly adaptive species common waterhemp. Glyphosate-resistant common waterhemp was first documented in 2006 after six years of continuous glyphosate use (Bradley et al. 2006).

In 2008 Legleiter and Bradley characterized two common waterhemp populations that were 19 and 9 times more resistant to glyphosate than a susceptible common waterhemp population.

In corn and soybean fields in Missouri and Illinois, common waterhemp has been cited as the most frequent and troublesome broadleaf weed encountered (Webster 2005;

Hager and Sprague 2002). Common waterhemp is troublesome for many reasons. An

10 average common waterhemp plant produces at least as many as 309,000 seeds with the possibility of producing up to 2.3 million seeds, 95% of which remain viable after 4 years in the soil (Hartzler et al.2004; Buhler and Hartzler 2001). Common waterhemp is known as to have a discontinuous emergence pattern. This gives it an advantage by being able to germinate much later in the growing season than many other summer annuals, thereby emerging after most herbicide applications have already been made (Hartzler et al. 1999; Steckel et al. 2007). It is even more concerning because it is a dioecious plant, which has the ability to outcross with other common waterhemp plants and other

Amaranthus species such as smooth pigweed (Amaranthus hybridus L.) and palmer amaranth, causing genetic variability (Franssen et al. 2001; Trucco et al. 2005; Wetzel et al. 1999). Common waterhemp populations have also been identified with resistance to

ALS-, PPO-, and photosystem II-inhibiting herbicides (Heap 2010), and in many instances multiple resistant common waterhemp populations have been confirmed. For example, in Douglas County, Kansas, a common waterhemp biotype survived eight times the normal use rate of an ALS-inhibiting herbicide while a biotype in Bond County,

Illinois, was found to be resistant to both ALS- and triazine-inhibiting herbicides (Horak and Peterson 1995).

With GR crops increasing greater than 10% per year in both developing and developed countries, the costs associated with the management of GR weeds could increase (Green 2009). With the increase in GR weeds, one concern is the potential for yield reductions. Eubank et al. (2008) showed yields decreasing by 26% when applications of glyphosate were made to GR horseweed compared to an alternative control method that included 2,4-D, which provided 95% control of horseweed. Similar

11 results were found by Steckel and Gwathmey (2009) in cotton where yield losses were

37- and- 44% when horseweed competed to the 8th cotton node in 2005 and 2006, respectively. From an economic standpoint, the control of GR horseweed was estimated to cost $30.07/Ha per year when in a cotton-soybean-corn rotation in Western Tennessee

(Mueller et al. 2005). Projected costs of GR common waterhemp in a corn-soybean rotation in southern Illinois were projected to be $44.25/Ha per year (Meuller et al.

2005). Legleiter et al. (2009) found that a standard glyphosate weed management program in GR soybean resulted in a loss of $23/Ha where GR common waterhemp was present due to ineffective common waterhemp control, increased common waterhemp competition, and lower soybean yields.

Introduction and Utility of 2,4-D Resistance Trait in Soybeans

Auxin resistant crops that are under development by Dow AgroSciences LLC have an aryloxyalkanoate dioxgenase (AAD) gene which confers resistance to the herbicide 2,4-D (Wright et al. 2005, 2007). The AAD gene was isolated from a gram- negative soil bacteria, Alcaligenes eutrophus, and codes for a 2-ketoglutarate-dependent dioxygenase that degrades the alkanoate side chain of the synthetic auxin (Fukumori and

Hausinger 2007). In short, the mechanism for herbicide resistance is a rapid single-step metabolic detoxification process mediated by a α-ketoglutarate-dependent dioxygenase enzyme (Simpson et al. 2008). Broadleaf plants without this gene are susceptible to applications of 2,4-D. Crops transformed with the 2,4-D resistance trait should provide growers with a wider window to treat weeds and plant crops, and offer a new alternative for the control of broadleaf weeds (Loux 2008.) Corn will be resistant to 2,4-D and also aryloxyphenoxypropionate herbicides and will likely be stacked in current hybrids that

12 offer both glyphosate- and glufosinate resistance. In crops transformed with the 2,4-D resistance trait, resistance can be seen from the early seedling up to the reproduction stage of growth at rates 4 to 8 times higher than current field use rates (Simpson et al.

2008). These traits will eliminate planting restrictions and should provide a new option for the control of broadleaf weeds that are resistant to glyphosate, atrazine, ALS-, or

PPO-inhibiting herbicides.

Summary and Objectives

Over the past decade, the adoption of GR crops and no-till practices has increased at a rapid rate. Increasing pressure from a single active ingredient has resulted in shifts to weeds that are resistant to glyphosate. Common waterhemp is one of these GR weeds, but many populations also have multiple resistance to herbicides with alternate modes of action. The herbicide 2,4-D has been around for nearly 70 years and has proven to be reliable, inexpensive, and has few reported cases of resistance in weeds. With the introduction of this new 2,4-D resistance trait in corn and soybean, growers will have the opportunity to use a variety of mode of actions while keeping their normal farming practices cost efficient. The objectives of this research are to: 1) compare the efficacy and utility of 2,4-D-containing herbicide programs in soybeans transformed with the glufosinate- and 2,4-D resistance trait with current standards used in glufosinate-resistant soybean systems, 2) determine the influence of weed height and glufosinate plus 2,4-D rate combinations on summer annual grass and broadleaf weed control in soybeans with resistance to glufosinate and 2,4-D and 3) determine if antagonistic, synergistic, or additive responses occur on summer annual weed species with combinations of glufosinate and 2,4-D.

LITERATURE CITED

Akobundu, I.O., R.D. Sweet, and W.B. Duke. 1975. A method of evaluating herbicide combinations and determining herbicide synergism. Weed Sci. 23:20-25.

Anderson, J.L., 2005. War on weeds: Iowa farmers and growth-regulator herbicides. Technol. and Cult.: 46.4:719-744.

Anonymous. 2010. 2,4-D Amine and ester specimen label. January 24, 2010. Web Internet: http://www.cdms.net/LabelsMsds/LMDefault.aspx.

Ashton, F.M. and A.S. Crafts. 1981. Mode of Action of Herbicides. 2nd ed. New York: J. Wiley. Pp. 272-302.

Bradley, K.W., E.S. Hagood Jr, and P.H. Davis. 2003. Evaluation of Postemergence herbicide combinations for long-term trumpetcreeper (Campsis radicans) control in corn (Zea Mays). Weed Technol. 17:718-723.

Bradley, K. W., J. Li, and N. H. Monnig. 2006. Greenhouse investigations of suspected glyphosate-resistant common waterhemp populations from Missouri. Weed Sci. Soc. Am. Abstr. no. 206. [CD-ROM Computer File]. Weed Sci. Soc. Am., Lawrence, KS. (Feb 06).

Bridges, D.C. 1992. Crop losses due to weeds in the United States. Champaign, IL: Weed Science Society of America.

Buhler, D.D., and R.G. Hartzler. 2001. Emergence and persistence of seed of velvetleaf, common waterhemp, woolly cupgrass, and giant foxtail. Weed Sci. 49:230-235.

Doran, J.W., W.W. Wilhelm, and J.F. Power. 1984. Crop residue removal and soil productivity with no-till corn, sorghum and soybean. Soil Sci. Soc. Am. J 48:640– 645.

Eubank, T.W., D.H. Poston, V.K. Nandula, C.H. Koger, D.R. Shaw, and D.B. Reynolds. 2008. Glyphosate-resistant horseweed (Conyza Canadensis) control using glyphosate-, paraquat-, and glufosinate-based herbicide programs. Weed Technol. 22:16-21.

Everitt, J.D. and J.W. Keeling. 2007. Weed control and cotton (Gossypium hirsutum) response to preplant applications of dicamba, 2,4-D, and diflufenzopyr plus dicamba. Weed Technol. 21:506-510.

Franssen, A.S., D.Z. Skinner, K. Al-Khatib, M.J. Horak, and P.A. Kulakow. 2001. Interspecific hybridization and gene flow of ALS resistance in Amaranthus species. Weed Sci. 49:598-606.

Fukumori, F. and R.P. Hausinger. 2007. Purification and characterization of 2,4- dichlorophenoxyacetate/α-ketoglutarate dioxygenase. J. Biol. Chem. 268:24311- 24317.

Gebhardt, M.R., T.C. Daniel, E.E. Schweizer, and R.R. Allmaras. 1985. Conservation tillage. Science 230:625–630.

Gianessi, L. and N. Reigner. 2007. The value of herbicides in U.S. crop production. Weed Technol. 21:559-566.

Givens, W.A. D.R. Shaw, W.G. Johnson, S.C. Weller, B.G. Young, R.G. Wilson, M.D.K. Owen, and D. Jordan. 2009. A grower survey of herbicide use patterns in glyphosate-resistant cropping systems. Weed Technol. 23:156-161.

Green, J.M. 2009. Evolution of glyphosate-resistant crop technology. Weed Sci. 57:108- 117.

Green, J.M., C.B. Hazel, D.R. Forney, and L.M. Pugh. 2008. New multiple-herbicide crop resistance and formulation technology to augment the utility of glyphosate. Pest Manag. Sci. 64:332-39.

Grichar J.W. and E.P. Prostko. 2009. Effect of glyphosate and fungicide combinations on weed control in soybeans. Crop Prot. 28:619-622.

Hager, A. and C. Sprague. 2002. Weeds on the horizon. In The Bulletin, Issue no. 6. Champaign, IL: University of Illinois.

Hart, S.E., and D.J. Maxwell. 1997. Postemergence broadleaf weed control in corn. DeKalb, IL. Research report. Proc. North Cent. Weed Sci. Soc. 52:128-129.

Hartzler, R.G., B.A. Battles, and D. Norby. 2004. Effect of common waterhemp (Amaranthus rudis) emergence date on growth and fecundity in soybean. Weed Sci. 52:242-245.

Hartzler, R.G., D.D. Buhler, and D.E. Stoltenberg. 1999. Emergence characteristics of four annual weed species. Weed Sci. 47:578-584.

Hatzios, K.K., and D. Penner. 1985. Interactions of herbicides with other agrochemicals in higher plants. Rev. Weed Sci. 1:1-52.

Heap, I. The international survey of herbicide resistant weeds. Online. Internet. February 18, 2010. Available www.weedscience.org.

Horak, M.J. and D.E. Peterson. 1995. Biotypes of palmer amaranth (Amaranthus palmeri) and common waterhemp (Amaranthus rudis) are resistant to imazethapryr and thifensulfuron. Weed Technol. 9:192-195.

Industry Task Force II on 2,4-D research Data. 2005. Issue backgrounder. January 14, 2010. Web Internet: http://www.24d.org/background/Backgrounder-What-is-24D- Dec-2005.pdf

Isaacs, A., K. K. Hatzios, H.P. Wilson and J.M. Toler. 2006. Halosulfuron and 2,4-D mixtures’ effects on common lambsquarters (Chenopodium album). Weed Technol. 20:137-142.

Kelley, K.B., L.M. Wax, A.G. Hager, and D.E. Riechers. 2005. Soybean response to plant growth regulator herbicides is affected by other postemergence herbicides. Weed Sci. 53:101-112.

Krausz, R.F., G. Kapusta, and J.L. Matthews. 1993. Soybean (Glycine max) tolerance to 2,4-D ester applied preplant. Weed Technol. 7:906–910.

Legleiter, T.R., and K.W. Bradley. 2008. Glyphosate and multiple herbicide resistance in common waterhemp (Amaranthus rudis) populations from Missouri. Weed Sci. 56:582-587.

Legleiter, T.R., K.W. Bradley, and R.E. Massey. 2009. Glyphosate-resistant waterhemp (Amaranthus rudis) control and economic returns with herbicide programs in soybean. Weed Technol. 23:54-61.

Loux, M. 2008. Can the DHT trait solve all of our glyphosate resistance problems?. Proc. North Cent. Weed Sci. Soc. 63:86.

Magin, R. W. 2003. Glyphosate: Twenty-eight years and still growing-The discovery, development, and impact of this herbicide on the agrichemical industry. 23rd International Symposium, ASTM STP 1449; G.Volgas, R. Downer, and H. Lopez, Eds. ASTM International, West Conshohocken, PA.

Martin, J.R., and C.R. Tutt. 2007. Johnsongrass control with postemergence corn herbicides applied alone or in tank mix combinations. Proc. North Cent. Weed. Sci. 62:12.

Mueller, T.C., P.D. Mitchell, B.G. Young, and A. S. Culpepper. 2005. Proactive versus reactive management of glyphosate-resistant or–tolerant weeds. Weed Technol. 19:924-933.

Nice, G., B. Johnson, and T. Bauman. 2004. Purdue Extension Weed Science: Amine or ester, which is better? Web Internet: http://www.btny.purdue.edu/weedscience/2004/articles/amineester04.pdf.

Norris R.F. 2005. Ecological bases of interactions between weeds and organisms in other pest categories. Weed Sci. 53:909-913.

Oliver, L.R. 1988. Principles of weed threshold research. Weed Technol. 2:298-303.

Owen, M. 1998. 2,4-D Use in soybeans. January 21, 2010. Web Internet: http://www.ipm.iastate.edu/ipm/icm/1998/5-18-1998/24dinsoy.html.

Owen, M. 2008. Review weed species shifts in glyphosate-resistant crops. Pest Manag. Sci. 64:377-387.

Pollard, J.M., B.A. Sellers, and R.J. Smeda. 2004. Differential response of common ragweed to glyphosate. Proc. N. Cent. Weed Sci. Soc. 59:27.

Reddy,K.N., C.T. Bryson and I.C. Burke. 2007. Ragweed parthenium (Parthenium hysterophorus) control with preemergence and postemergence herbicides. Weed Technol. 21:982-986.

Sankula, S. 2006. Quantification of the impacts on U.S. agriculture of biotechnology- derived crops planted in 2005. National Center for Food and Agricultural Policy.

Simpson, D.M., T.R. Wright, R.S. Chambers, M.A. Peterson, C. Cui, A.E. Robinson, J.S. Richburg, D.C. Ruen, S. Ferguson, B.E. Maddy, and E.F. Schreader. 2008. Dow Agrosciences herbicide tolerance traits in corn and soybean. Proc. North Cent. Weed Sci. Soc. 63:85.

Steckel, L.E. and C.O. Gwathmey. 2009. Glyphosate-resistant horseweed (Conyza Canadensis) growth, seed production, and interference in cotton. Weed Sci. 57:346-350.

Steckel, L.E., C.C. Craig, R.M. Hayes. 2006. Glyphosate-resistant horseweed (Conyza Canadensis) control with glufosinate prior to planting no-till cotton (Gossypium hirsutum). Weed Technol. 20:1047-1051.

Steckel, L.E., C.L. Sprague, E.W. Stoller, L.M. Wax, and F.W. Simmons. 2007. Tillage, cropping system, and soil depth effects on common waterhemp (Amaranthus rudis) seed-bank persistence. Weed Sci. 55:235-239.

Szmedra, P. 1997. Banning 2,4-D and the phenoxy herbicides: Potential economic impact. Weed Sci. 45:592-598.

Trucco, F., R. Justice, A.L. Rayburn, and P.J.Tranel. 2005. Promiscuity in weedy amaranths: high frequency of female tall waterhemp (Amaranthus tuberculatus) X smooth pigweed (A. hybridus) hybridization under field conditions. Weed Sci. 53:46-54.

[USDA] United States Department of Agriculture. 2008. National Agriculture Statistics Service. Farm production expenditures hit record high in 2007, USDA reports. Web page: http://www.nass.usda.gov/Newsroom/2008/08_07_2008.asp

[USDA] United States Department of Agriculture. 2009a. Economic Research Center. Adoption of genetically engineered crops in the U.S.: Soybeans varieties. Web Internet: http://www.ers.usda.gov/data/biotechcrops/ExtentofAdoptionTable3.htm.

[USDA] United States Department of Agriculture. 2009b. Agriculture Statistics Board. June Acreage Report. Web internet: http://www.nass.usda.gov/Charts_and _Maps/graphics/cornac.gif.

[USDA] United States Department of Agriculture. 2009c. National Agriculture Statistics Service. Farm production expenditures hit record high in 2009, USDA reports. Web page: http://www.nass.usda.gov/Newsroom/2009/08_06_2009.asp

[USDA] United States Department of Agriculture. 2010. Economic Research Center. Farm income and costs: 2010 farm sector income forecast. Web page: http://www.ers.usda.gov/Briefing/FarmIncome/nationalestimates.htm.

VanGessel, M.J. 2001. Glyphosate-resistant horseweed in Delaware. Weed Sci. 49:703-705.

Voos, G., and P.M. Groffman. 1997. Relationships between microbial biomass and dissipation of 2,4-D. J. Environ. Qual. 25, 5-12.

Waltz, A.L., A.R. Martin, and K.T. Horky. 2003. Weed control in grain sorghum. N. Cent. Weed Sci. Res. Rep. 60:45-46.

Webster, T.M. 2005. Weed survey-southern states. Proc. S. Weed Sci. 58:291-306.

Wetzel, D.K., M.J. Horak, D.Z. Skinner, and P.A. Kulakow. 1999. Transferal of herbicide resistance traits from Amaranthus palmeri to Amaranthus tuberculatus. Weed Sci. 47:538-543.

Woodburn, A.T. 2000. Glyphosate: Production, pricing and use worldwide. Pest Manag. Sci. 56:309-312.

Woodford, E.K. 1952. The mode of action of 2:4-Dichlorophenoxy-Acetic acid and 2- Methyl-4-Chlorophenoxyacetic acid. J. Sci. Food Agric. 3:349-353.

Wright, T.R., J.M. Lira, D.J. Merlo, N. Hopkins, inventors; Dow Agrosciences assignee. 2005 Nov 17. Novel herbicide resistance genes. World Intellectual Property Organization patent WO/2005/107437.

Wright, T.R., J.M. Lira, D.J. Merlo, N. Hopkins, inventors; Dow Agrosciences assignee. 2007 Nov 17. Novel herbicide resistance genes. World Intellectual Property Organization patent WO/2007/107437.

[WSSA] Weed Science Society of America. 2007. Herbicide handbook. 9th ed. Lawrence, KS, 327 pp.

[WSSA] Weed Science Society of America. 2008. Resistance and tolerance definitions. Web page: http://www.wssa.net/Weeds/Resistance/definitions.htm.

Young B.G. 2006. Changes in herbicide use patterns and production practices resulting from glyphosate-resistant crops. Weed technol. 20:301-307.

CHAPTER II

INFLUENCE OF HERBICIDE PROGRAMS ON WEED MANAGEMENT

IN SOYBEAN WITH RESISTANCE TO GLUFOSINATE AND 2,4-D

ABSTRACT

Four field trials were conducted in Boone and Callaway counties in Missouri in

2010 and 2011 to investigate herbicide programs for the management of summer annual grass and broadleaf weeds in soybean resistant to 2,4-D and glufosinate. Results from these experiments revealed that the addition of 0.56, 0.84, or 1.12 kg/Ha 2,4-D to either or both postemergence (POST) applications of glufosinate in a 2-pass POST herbicide program increased control of common waterhemp compared to two POST applications of glufosinate alone. Similar levels of common cocklebur, giant foxtail, large crabgrass, and barnyardgrass control were achieved with any of the 2-pass POST programs that contained 2,4-D compared to 2-pass POST programs containing glufosinate alone.

Similar control of these species was also achieved with the inclusion of 2,4-D amine in either the first or second pass of glufosinate. Two-pass programs resulted in the highest levels of weed control (90%). Annual grass and broadleaf weed control was up to 59% lower when 1-pass POST herbicide programs were compared to PRE followed by (fb)

POST or 2-pass POST programs. However, 1-pass POST programs provided exceptional

20 control of common cocklebur and giant foxtail. Across all site-years, soybean yields ranged from 2680- to- 3102 kg/Ha for all herbicide treatments, but did not differ statistically. Overall, results from these experiments indicate that compared to glufosinate alone, PRE fb POST or 2-pass POST herbicide programs that incorporate 2,4-

D amine with glufosinate in 2,4-D resistant soybeans enhance control of common waterhemp, while providing similar levels of control for other summer annual grass and broadleaf weeds.

INTRODUCTION

In the past several decades farming practices have changed dramatically, especially in the methods utilized to control weed species in the major agronomic crops.

Increased farm size and production costs have led to the widespread adoption of herbicide-resistant crops as a tool for weed management (Young 2006). In soybean for example, the total number of active ingredients and herbicide modes of actions within a growing season has declined, along with the total number of herbicide applications

(Young 2006). Before the introduction of glyphosate-resistant (GR) crops, farmers relied heavily upon soil-applied herbicides such as the dinitroanalines and imidazolinones for weed management. In 1995, trifluralin, imazethapyr, pendimethalin, and imazaquin were among the most commonly used herbicides in soybean, with applications occurring on

20, 26, 44, and 15% of the U.S. soybean acreage, respectively (USDA 1996). Since the introduction of glyphosate- and glufosinate-resistant soybeans in 1996 and 2009, respectively, the predominant weed control programs have consisted of single or multiple postemergence (POST) herbicide applications with less reliance upon soil-applied herbicides (Norsworthy 2003: Young 2006). Young (2006) reported that from 1995 to

2002 the number of glyphosate applications in soybean increased from 1 to 1.4.

However, other authors have shown that a preemergence (PRE) residual herbicide program followed by a POST herbicide application has the potential to reduce weed densities, and in some instances increase yields (Barnes and Oliver 2004; Ellis and

Griffin 2002; Gardner et al. 2006). Although there have been many reports of PRE fb

POST programs leading to similar yields compared to sequential POST applications, it is a more common occurrence to find increased yields with PRE fb POST over single PRE or POST herbicide applications (Barnes and Oliver 2004; Payne and Oliver 2000; Stewart et al. 2011; Nurse et al. 2007; Watts et al. 1997). For example, Norsworthy (2004) observed similar levels of weed control with PRE fb POST herbicide programs compared to programs that contained sequential POST-only herbicide applications. However a yield increase was only found with the PRE fb POST programs when soybean were planted in 4.5m verses 3.9m rows. Other researchers have found that incorporating a

PRE into a herbicide program can delay late POST applications of glyphosate up to 7 days or in some situations eliminate a late POST application (Ellis and Griffin 2002).

One-pass POST programs may also result in yield losses; from a survey of Indiana soybean farmers, averaged yields from 1-pass POST programs were 3,260 kg/Ha compared to 3,460 kg/Ha with herbicide programs that contained two or more herbicide applications (Johnson et al. 2007).

Unfortunately, the continual use of glyphosate in GR crops along with the concurrent decrease in the use of other active ingredients has led to weed population shifts, and to the selection of weed populations with resistance to glyphosate (Heap 2010;

Meuller et al. 2005; Owen 2008; Young 2006). Currently, there are 13 species with

22 resistance to glyphosate in the United States including horseweed (Conyza canadensis L.

Cronq.), palmer amaranth (Amaranthus palmeri S. Wats.), common waterhemp

(Amaranthus rudis Sauer.), giant ragweed (Ambrosia trifida L.), and common ragweed

(Ambrosia artemisiifolia L.) which impact the largest production area across the country

(Heap 2010). In the first ten years following the introduction of GR crops, GR weeds were identified at a rate of 1.4 weeds/year. In the past 6 years, the identification of GR weeds has increased to a rate of 1.7 weeds/year (Heap 2011). The frequency of GR in weed biotypes is projected to increase in any location where glyphosate is relied upon as the primary or sole herbicide for weed control (Norsworthy et al. 2012; Young 2006).

Dow AgroSciences LLC is currently developing corn, soybean, and cotton hybrids with a trait that confers resistance to pre-plant or POST applications of 2,4-D

(Simpson et al 2009; Wright et al. 2010). The transgene responsible for the degradation of 2,4-D in these plants is a bacterial substrate of the aryloxyalkanoate dioxygenase enzyme (AAD). The AAD-12 gene that was incorporated into 2,4-D resistant soybean acts on pyridyloxyacetate auxin herbicides such as triclopyr and fluroxypyr, along with

2,4-D (Wright et al. 2010). This trait should present growers with new options for the control of broadleaf weeds which demonstrate resistance to glyphosate. Additionally, applications of 2,4-D on cotton and soybean transformed with the 2,4-D resistance trait should provide growers with an additional mode of action not currently labeled for POST applications in these environments. Restrictions that currently exist between applications of 2,4-D and planting of these crops will also be eliminated (Loux 2008).

Currently, there are over 90 different broadleaf weed species controlled by 2,4-D in a variety of agronomic crops (Anonymous 2011). Redroot pigweed (Amaranthus

23 retroflexis L.) and common waterhemp are two species within the Amaranthaceae, or pigweed family, that can be controlled effectively with timely applications of 2,4-D. In previous research, redroot pigweed control exceeded 98% at rates of 0.6 kg 2,4-D/Ha and higher, and greater than 90% control of common waterhemp has been observed with applications of 2,4-D at 0.28 kg/Ha on 2.5- to 7-cm plants (Anderson et al. 1996; Sarabi et al. 2011). Broad spectrum control of broadleaf weeds results with 2,4-D applications, and this herbicide is used frequently for the control of GR weed species such as horseweed (Eubank et al. 2008; Heap 2010). Scherder et al. (2009) also reported that

2,4-D provided greater than 90% control of GR common waterhemp as well as several other broadleaf weeds which respond poorly to glyphosate.

Much research has been conducted to evaluate weed control in response to PRE fb POST, two-pass POST, or one-pass POST multi-herbicide combinations with glyphosate in glyphosate-resistant soybean. Little research has been conducted to evaluate the utility of similar program approaches for soybean resistant to 2,4-D and glufosinate. The objectives of this research were to: 1) compare and contrast the summer annual grass and broadleaf weed control provided by PRE fb POST , 2-pass POST, 1- pass POST residual, and 1-pass late POST programs that contain glufosinate plus 2,4-D and; 2) to determine the most effective rate and timing for the application of 2,4-D amine and/or glufosinate in soybean with resistance to these herbicides.

MATERIALS AND METHODS

Site Description.

Duplicate field experiments were conducted at two locations in Missouri during the summers of 2010 and 2011, resulting in a total of four site-years. Each year, one

24 experiment was conducted in Boone County at the University of Missouri Bradford

Research and Extension Center (38°53'N, 92°12'W), and another was located in Callaway

County near Mokane (38°39'N, 91°52'W). Sites were selected based upon the presence of dense infestations of common waterhemp, common cocklebur (Xanthium strumarium

L.), giant foxtail (Setaria faberi Herm), large crabgrass (Digitaria sanguinalis L.), and barnyardgrass (Echinochloa crus-galli L.) at the Boone County site, and the presence of dense infestations of common waterhemp at the Callaway County site. The soil type at the Boone County location was a Mexico silt loam (fine, smectic, mesic Aeric Vertic

Epiaqualfs) with 2.3% organic matter and pH of 6.5 in 2010 and a pH of 6.0 and organic matter content of 2.4% in 2011. At the Callaway County site, the soil type was a Hodge fine sand, loamy substratum (mixed, Mesic Typic Udipsamments) with organic matter content of 1.4 and 1.5% and pH of 6.8 and 6.7 in 2010 and 2011, respectively. At each location, glufosinate- and 2,4-D-resistant soybean provided by Dow AgroSciences LLC were planted into a conventionally-tilled seedbed in four rows spaced 76-cm apart at a seeding rate of 395,000 seeds/Ha. Monthly rainfall totals and average monthly temperatures at each location are presented in Table 2.1. In all experiments, the experimental design consisted of a randomized complete block and with 6 replications.

Individual plots were 2 by 9 m in size. All herbicide applications were made with a CO₂- powered backpack sprayer delivering 140 L/Ha with flat fan nozzle tips at 117 Kpa. A detailed list of seeding and herbicide application dates and soybean and weeds stages at application are listed in Table 2.2.

Treatment Evaluation and Data Collection.

Visual herbicide injury and weed control evaluations were conducted at weekly intervals for up to 8 weeks after planting (WAP). Late season weed control data correspond to the 8 WAP data which occurred 2 weeks after the 1-pass late POST applications had been made. Visual crop injury and weed control ratings were based on a scale from 0 to 100 with 0 indicating no crop injury or weed control and 100 representing complete plant death. In both years, soybean were harvested from the center two rows in each plot with a small plot combine and yields were adjusted to 13% moisture content. A complete list of herbicide treatments evaluated in all experiments is provided in Table

2.3.

Statistical Analysis.

Visual weed control data and soybean yield were subjected to analysis of variance using the PROC MIX procedure in SAS (SAS 9.2, SAS® Institute Inc.). Year-location combinations were considered an environment sampled at random as suggested by

Carmer et al. (1989). Herbicide treatment and application timing were considered fixed effects in the model while environment, replications, and interactions within environment were considered random effects. Weed control data were transformed using arcsine of the square root. Transformations did improve the model for weed control. Analyses for these data were performed on the transformed means and detected using Fisher’s protected LSD at α= 0.05. Means were then back transformed for data presentation.

Transformations did not improve the model with respect to yield data. Contrast comparisons among herbicide programs represent a priori orthogonal contrasts. All possible pair wise comparisons were made across all site-years as well as environments

26 to determine whether differences exist between PRE fb POST, 2-pass POST, 1-pass

POST residual, and 1-pass late POST programs.

RESULTS AND DISCUSSION

Evaluation of 2,4-D.

Within the PRE fb POST herbicide programs, the addition of either rate of 2,4-D to POST applications of glufosinate improved the control of common waterhemp up to 6 and 11% compared to POST application of glufosinate alone (Table 2.3). Barnyardgrass control was also slightly higher with the addition of 0.56 or 0.84 kg/Ha 2,4-D compared to glufosinate alone following a PRE application of sulfentrazone plus cloransulam, but control of large crabgrass and giant foxtail was similar regardless of the addition of 2,4-

D. These results are in contrast to many reports of decreased grass and/or broadleaf control with the addition of growth regulator herbicides to glyphosate, glufosinate, fenoxaprop, haloxyfop, sethoxydim, nicosulfuron, and rimsulfuron (Hennigh et al. 2010;

Koger et al. 2007; Mueller et al. 1989; Young et al. 1996). Within the 2-pass POST programs, treatments that contained glufosinate and 2,4-D resulted in similar common cocklebur and grass control compared to treatments of glufosinate alone. However, the addition of 2,4-D to POST glufosinate treatments increased the level of common waterhemp control up to 25% compared to applications of glufosinate alone. Across 3 site-years, common waterhemp control with a 2-pass POST program of glufosinate alone averaged 74% while common waterhemp control was 96% or greater with the inclusion of 2,4-D into at least one of the POST applications. Scherder et al. (2009) also observed greater than 90% control of common waterhemp with 2,4-D, while Steckel et al. (2006)

27 reported better control of glyphosate-resistant horseweed with 0.47 kg/Ha glufosinate plus 0.53 kg/Ha 2,4-D control than with glufosinate alone.

In contrast to Siebert et al. (2004) who found that increasing the 2,4-D rate increased red morningglory control, the results from these experiments indicate that applications of 2,4-D at 0.56, 0.84, and 1.12 kg/Ha provide similar levels of annual grass and broadleaf weed control when applied to weeds 30 cm or less in height. Sarabi et al.

(2011) also observed 100% control of redroot pigweed with 2,4-D at rates of 0.6, 0.8 and

1 kg/Ha. However, when 2,4-D was applied at 0.07 to 0.4 kg/Ha, control was inconsistent, ranging from 27 to 80%. Similar to the evaluation of 2,4-D rate, the addition of 2,4-D to glufosinate in the first POST, second POST, or both POST applications was generally not a determining factor in the level of weed control achieved.

There was, however, improved control of common waterhemp when 2,4-D was applied at

1.1 kg/Ha in both POST applications compared to 2,4-D at 0.56 kg/Ha in the second post only. This suggests that the addition of 2,4-D in the first POST application may provide more effective control of this species, and that any survivors or additional flushes will likely be eliminated with the second POST glufosinate plus 2,4-D application.

Herbicide Program Comparisons.

PRE fb POST and 2-pass POST herbicide programs provided the highest levels of weed control recorded in these experiments (Table 2.4). PRE fb POST programs provided better common waterhemp control than 2-pass POST programs, but control was exceptional with both program approaches. The slightly higher control observed with

PRE fb POST programs is most likely due to the reduction in the population density of common waterhemp present at the POST application timing (data not shown). Ellis and

Griffin (2002) also observed weed density reductions in response to PRE herbicide applications. All PRE fb POST programs enhanced control of common waterhemp and giant foxtail in comparison to 1-pass POST residual programs. Additionally, PRE fb

POST herbicide programs provided better large crabgrass, barnyardgrass, and common waterhemp control compared to 1-pass late POST programs.

Two-pass POST herbicide programs provided better than 90% control of all the weeds evaluated in these experiments (Table 2.4). Specifically, 2-pass POST programs provided better control of large crabgrass and giant foxtail than any of the other programs evaluated in these experiments. Gonzini et al. (1990) also observed higher giant foxtail control with 2-pass POST programs containing glyphosate in GR soybean than with either PRE fb POST or one-pass POST programs.

Common cocklebur control was higher with 1-pass late POST programs compared to PRE fb POST or 2-pass POST programs, most likely due to the later emergence of this species in this experiment (Norsworthy and Oliveira 2007) (Table 2.4).

With the exception of common cocklebur and giant foxtail, 1-pass late POST herbicide programs provided the poorest levels of weed control for all species evaluated. Corbett et al. (2004) also reported high levels of giant foxtail control with single applications of glufosinate. When 1-pass late POST applications were made, control of common waterhemp, large crabgrass, and barnyardgrass were reduced by 12, 41, and 33%, respectively, compared to 2-pass POST programs. Knezevic et al. (2009) also observed reductions in weed control following later herbicide applications made to larger plants.

Reductions in control were also observed with 1-pass POST residual compared to PRE fb

POST and 2-pass POST programs.

Common waterhemp and giant foxtail control was at least 10% lower with 1-pass

POST residual programs than with PRE fb POST programs and, with the exception of barnyardgrass, resulted in 7- to- 15% less control of the other weeds evaluated compared to 2-pass POST program. Large crabgrass and barnyardgrass control exceeded 80% with one-pass POST residual programs while control was never greater than 73% with 1-pass late POST programs. Increased rates of glufosinate and 2,4-D in 1-pass late POST programs provided similar control of common waterhemp and common cocklebur than 1- pass POST residual programs, while improving giant foxtail control by 8%.

Soybean Injury and Yield.

The highest visual soybean injury observed in response to any of the treatments evaluated in these experiments was 16%, which was observed in response to glufosinate plus 2,4-D plus S-metolachlor plus fomesafen 7 days after treatment (data not shown).

All other treatments that contained glufosinate plus 2,4-D resulted in less than 3% visual soybean injury at all time intervals after treatment (data not shown).

Soybean yields ranged from 2680- to 3102-kg/Ha and overall there were few differences in soybean yields between the herbicide treatments or programs evaluated in this research (Tables 2.5 and 2.6). Conflicting results have been reported as to which herbicide programs are most likely to result in highest soybean yields. Results from several studies have shown that either PRE fb POST or sequential POST programs are more likely to provide higher yields than single POST programs (Heatherly et al 2002;

Payne and Oliver 2000; Stewart et al. 2011.). In this research, there were no differences in soybean yield between herbicide programs, most likely due to the fact that all programs provided greater than 80% weed control, resulting in little competition between

30 the crop and weeds for inputs (Table 2.6). Other researchers have reported that the most dominant weed species within a field will determine the effect of herbicide programs on soybean seed yield (Barnes and Oliver 2004). For example, Barnes and Oliver (2004) found that when palmer amaranth was the dominant species, POST programs of glyphosate were able to control this weed resulting in no differences among yields from sequential PRE fb POST or POST programs. However, when hemp sesbania (Sesbania exaltata Rydb. Ex A. W. Hill) was the dominant weed, sequential PRE fb POST programs out-yielded POST-only programs. In this research, common waterhemp was the dominant species across all site years, and control of this species was never less than

84%. Although no differences were observed among programs, all herbicide treatments provided higher yields than the untreated control and similar-yields to the weed-free control (Table 2.5).

In summary, PRE fb POST or two-pass POST herbicide programs that incorporate 2,4-D plus glufosinate treatments in soybeans with resistance to glufosinate and 2,4-D can enhance the control of problematic species like common waterhemp, and provide comparable control of other summer annual grass and broadleaf with two-pass

POST programs which contain glufosinate alone. Although 1-pass late POST programs provided high levels of common cocklebur and giant foxtail control in this research, 1- pass LPOST programs will likely result in poorer control of some annual grass and broadleaf weeds, and are more likely to result in soybean yield reductions. As glyphosate resistance increases with species and the total area infested, the incorporation of additional effective herbicide modes of action like glufosinate and 2,4-D is necessary to

31 control GR weed species, and to prevent the evolution of herbicide resistance in future weed biotypes (Culpepper 2006: Diggle et al. 2003; Heap 2010) .

LITERATURE CITED

Anderson, D.D., F.W. Roeth, and A.R. Martin. 1996. Occurrence and control of triazine- resistant common waterhemp (Amaranthus rudis) in field corn (Zea mays). Weed Technol. 10:570-575.

Anonymous. 2011. Agri Star® 2,4-D Amine 4 product label. Ankeny, IA: Albaugh Inc. 5 p. Available: http://www.cdms.net/LDat/ld4JF000.pdf. Accessed: March 13, 2012.

Barnes, J.W., and L.R. Oliver. 2004. Preemergence weed control in soybean with cloransulam. Weed Technol. 18:1077-1090.

Carmer, S.G., W.E. Nyquist, and W.M. Walker. 1989. Least significant differences for combined analysis of experiments with two or three-factor treatment designs. Agron. J. 81:665-672.

Corbett, J.L., S.D. Askew, W.E. Thomas, and J.W. Wilcut. 2004. Weed efficacy evaluations for bromoxynil, glufosinate, glyphosate, pyrithiobac, and sulfosate. Weed Technol. 18:443-453.

Culpepper, A.S. 2006. Glyphosate-induced weed shifts. Weed Technol. 20:277-281.

Diggle, A.J., P.B. Neve, and E.P. Smith. 2003. Herbicides used in combination can reduce the probability of herbicide resistance in finite weed populations. Weed Research 43:371-382.

Ellis, J.M., and J.L. Griffin. 2002. Benefits of soil-applied herbicides in glyphosate- resistant soybean (Glycine max). Weed Technol. 16:541-547.

Eubank, T.W., D.H. Poston, V.K. Nandula, C.H. Koger, D.R. Shaw, and D.B. Reynolds. 2008. Glyphosate-resistant horseweed (Conyza canadensis) control using glyphosate-, paraquat-, and glufosinate-based herbicide programs. Weed Technol. 22:16-21.

Gardner, A.P., A.C. York, D.L. Jordan, and D.W. Monks. 2006. Management of annual grasses and Amaranthus spp. in glufosinate-resistant cotton. J. Cotton Sci. 10:328- 338.

Gonzini, L.C., S.E. Hart, and L.M. Wax. 1999. Herbicide combinations for weed management in glyphosate-resistant soybean (Glycine max). Weed Technol. 13:354-360.

Heap, I. 2010. The international survey of herbicide resistant weeds. www.weedscience.org. Accessed: February 18, 2010.

Heatherly, L.G., C.D. Elmore, and S.R. Spurlock. 2002. Weed management systems for conventional and glyphosate-resistant soybean with and without irrigation. Agron. J. 94:1419-1428.

Hennigh, D.S., K. Al-Khatib, and M.R. Tuinstra. 2010. Postemergence weed control in acetolactate synthase-resistant grain sorghum. Weed Technol. 24:219-225.

Johnson, W.G., K.D. Gibson, and Shawn P. Conley. 2007. Does weed size matter? An Indiana grower perspective about weed control timing. Weed Technol. 21:542- 546.

Koger, C.H., I.C. Burke, D.K. Miller, J.A. Kendig, K.N. Reddy, and J.W. Wilcut. 2007. MSMA antagonizes glyphosate and glufosinate efficacy on broadleaf and grass weeds. Weed Technol. 21:159-165.

Loux, M. 2008. Can the DHT trait solve all of our glyphosate resistance problems?. North Central Weed Science Society Proc. 63:86.

Mueller, T.C., P.D. Mitchell, B.G. Young, and A. S. Culpepper. 2005. Proactive versus reactive management of glyphosate-resistant or–tolerant weeds. Weed Technol. 19:924-933.

Mueller, T.C., W.W. Witt, and M. Barrett. 1989. Antagonism of johnsongrass (Sorghum halepense) control with fenoxaprop, haloxyfop, and sethoxydim by 2,4-D. Weed Technol. 3:86-89.

National Climatic Data Center. 2011. United States climate normals 1981 to 2010. http://ggweather.com/normals/MO.html#J. Accessed: March 15, 2012.

Norsworthy, J. K. 2003. Use of soybean production surveys to determine weed management needs of South Carolina farmers. Weed Technol. 17:195-201.

Norsworthy, J.K. 2004. Soil-applied herbicide use in wide-and narrow-row glyphosate- resistant soybean (Glycine max). Crop Protection 23:1237-1244.

Norsworthy, J.K., and M.J. Oliveria. 2007. Tillage and soybean effects on common cocklebur (Xanthium strumarium) emergence. Weed Sci. 55:474-480.

Norsworthy, J.K., S. Ward, D. Shaw, R. Llewellyn, R. Nichols, T.M. Webster, K. Bradley, G. Frisvold, S. Powles, N. Burgos, W. Witt, and M. Barrett. 2012. Reducing the risks of herbicide resistance: Best management practices and recommendations. Weed Science: In press.

Nurse, R.E., A.S. Hamill, C.J. Swanton, F.J. Tardif, W. Deen, and P.H. Sikkema. 2007. Is the application of a residual herbicide required prior to glyphosate application in no-till glyphosate-tolerant soybean (Glycince max)? Crop Protection 26:484-489.

Owen, M. 2008. Review weed species shifts in glyphosate-resistant crops. Pest Manag. Sci. 64:377-387. Payne, S.A., and L.R. Oliver. 2000. Weed control programs in drilled glyphosate- resistant soybean. Weed Technol. 14:413-422

Sarabi, V., M.H.R. Mohassel, and M. Valizadeh. 2011. Response of redroot pigweed (Amaranthus retroflexus) to tank mixtures of 2,4-D plus MCPA with foramsulfuron. Australian J. Crop Sci. 5:605-610.

Scherder, E.F., M.E. Schultz, M.A. Peterson, J.M. Ellis, S.C. Ditmars, K.W. Bradley, R.J. Smeda, and W.G. Johnson. 2009. Control of glyphosate-resistant and susceptible weeds with 2,4-D alone or in tank mixes with glyphosate. NCWSS Proc. 64:120.

Siebert, J.D., J.L. Griffin, and C.A. Jones. 2004. Red morningglory (Ipomoea cochineal) control with 2,4-D and alternative herbicides. Weed Technol. 18:38-44.

Simpson, D.M., D.C. Rune, E.F. Scherder, M.A. Peterson, S.C. Ditmars, J.M. Ellis, J.S. Richburg, and D.T. Ellis. 2009. Performance of Dow Agrisciences herbicide tolerance trait in soybean. NCWSS Proc. 64:21.

Stewart, C.L., R.E. Nurse, L.L. Ban Eerd, R.J. Vyn, and P.H. Sikkama. 2011. Weed control, environmental impact, and economics of weed management strategies in glyphosate-resistant soybean. Weed Technol. 25:535-541.

[USDA] United States Department of Agriculture, National Agricultural Statistics Service. 1996. Agricultural Chemical Usage: 1995 Field Crops Summary: http://usda.mannlib.cornell.edu/. Accessed: February 21 2012.

Watts, J.R., E.C. Murdock, G.S. Stapleton, and J.E. Toler. 1997. Sicklepod (Senna obtusifolia) control in soybean (Glycine max) with single and sequential herbicide applications. Weed Technol. 11:157-163.

Wright, T.R., G. Shan, T.A. Walsh, J.M. Lira, C. Cui, P. Song, M. Zhuang, N.L. Arnold, G. Lin, S. M. Russell, R.M. Cicchillo, M.A. Peterson, D.M. Simpson, N. Zhou, J. Ponsamuel, and Z. Zhang. 2010. Robust crop resistance to broadleaf and grass herbicides provided by aryloxalkanoate dioxygenase transgenes. PNAS 107:20240-20245.

Young, B.G. 1996. Interactions of sethoxydim and corn (Zea mays) postemergence broadleaf herbicides on three annual grasses. Weed Technol. 10:914-922.

Young, B.G. 2006. Changes in herbicide use patterns and production practices resulting from glyphosate resistant crops. Weed Technol. 20:301-307.

Table 2.1. Monthly rainfall (mm) and average monthly temperatures (C) from April through October in 2010 and 2011 in comparison to the 30-yr average in Boone and Callaway counties in Missouri. Rainfall Temperature 30-yr 30-yr Location Month 2010 2011 averagea 2010 2011 average

------mm ------C ------Boone April 196 72 121 15.4 13.6 13.6

May 108 136 127 17.7 16.7 18.9

June 84 77 94 24.5 23.9 23.8

July 204 59 101 25.4 27.6 25.7

August 207 61 75 25.2 24.7 24.8

September 176 46 78 19.4 17.4 20.4

October 11 26 99 14.3 13.7 14.0

Callaway April 114 90 108 16.0 15.6 13.5

May 111 132 126 18.9 18.3 18.4

June 139 90 116 26.1 25.6 23.4

July 139 24 109 26.7 29.4 25.8

August 96 61 108 26.7 26.1 24.7

September 171 81 109 20.6 18.3 20.1

October 8 28 90 15.6 15.0 14.2 a 30-yr averages (1981-2010) obtained from National Climatic Data Center (2011).

Dates of herbicide application

PRE fb POST 5/28 fb 6/24 6/6 fb 7/12 5/6 fb 6/24 6/3 fb 7/1

2-pass POST 6/18 fb 6/30 6/29 fb 7/14 6/10 fb 6/24 7/5 fb 7/18

1-pass POST residual 6/18 6/29 6/1 6/24

1-pass late POST 6/30 7/6 6/21 7/14

Soybean growth stage at application

PRE fb POST --- fb V3 --- fb V5 --- fb R1 --- fb V5

2-pass POST V2 fb V5 V2 fb V6 V4 fb R1 V6 fb R1

1-pass POST residual V2 V2 V2 V3

1-pass late POST V5 V6 R1 R1

Average weed size (cm) at application

PRE fb POST --- fb 10 --- fb 10 --- fb 10 --- fb 10

2-pass POST 7.5 fb 10 10 fb 10 10 fb 13 10 fb 20

1-pass POST residual 8 10 9 8

1-pass late POST 18 19 33 30

Table 2.3. Influence of herbicide programs containing glufosinate or glufosinate plus 2,4-D on late-season annual grass and broadleaf weed control across four site-yearse in Missouri.a Weed species Treatmentd Timingbc Rate AMATA XANST SETFA DIGSA ECHCG

kg/Ha ------% Visual control ------

Sulfentrazone + chloransulam PRE 0.139 + 0.018 93 c 75 g 95 ab 90 cd 92 b Glufosinate EPOSTd 0.45

Sulfentrazone + chloransulam PRE 0.139 + 0.018 99 ab 86 d-f 97 ab 91 b-d 97 a Glufosinate + 2,4-D EPOST 0.45 + 0.56

Sulfentrazone + chloransulam PRE 0.139 + 0.018 98 ab 86 c-f 97 ab 91 cd 97 a Glufosinate + 2,4-D EPOST 0.45 + 0.84

Sulfentrazone + chloransulam PRE 0.139 + 0.018 99 a 83 f 95 ab 90 cd 96 ab Glufosinate + 2,4-D EPOST 0.45 + 1.12

Glufosinate EPOST 0.45 74 f 88 a-f 99 a 98 a 96 ab Glufosinate MPOST 0.45

Glufosinate EPOST 0.45 96 bc 91 a-e 99 a 94 a-c 98 a Glufosinate + 2,4-D MPOST 0.45 + 0.56

Glufosinate EPOST 0.45 97 a-c 91 ab 99 a 97 a 96 a Glufosinate + 2,4-D MPOST 0.45 + 0.84 39

Glufosinate EPOST 0.45 99 ab 92 ab 99 a 96 a-c 97 ab Glufosinate + 2,4-D MPOST 0.45 + 1.12

Glufosinate EPOST 0.45 + 0.56 96 a-c 94 a-d 99 a 99 ab 98 ab Glufosinate + 2,4-D MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 0.84 98 ab 90 a-e 99 a 94 a-c 95 ab Glufosinate MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 1.12 98 ab 94 a-c 99 a 97 a-c 97 a Glufosinate MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 0.56 98 ab 92 ab 99 a 96 a-c 95 ab Glufosinate MPOST 0.45 + 0.56 40

Glufosinate + 2,4-D EPOST 0.45 + 0.84 98 ab 92 a 99 a 96 ab 96 a Glufosinate MPOST 0.45 + 0.84

Glufosinate + 2,4-D EPOST 0.45 + 1.12 99 a 91 a-e 99 a 93 a-c 98 a Glufosinate + 2,4-D MPOST 0.45 + 1.12

Glufosinate + 2,4-D V2-V3 0.45 + 0.56 93 c 81 ef 87 c 84 d 96 ab + S-metolachlor + 1.2 + Fomesafen + 0.27

Glufosinate + 2,4-D V2-V3 0.45 + 0.56 75 ef 86 b-f 86 c 79 d 98 a + Acetochlor + 1.27

Glufosinate + 2,4-D LPOST 0.59 + 1.12 83 de 90 a-e 92 bc 51 e 71 c 40

Glufosinate + 2,4-D LPOST 0.73 + 1.12 85 d 89 a-f 95 ab 62 e 75 c a Data were pooled by environment (location and year) by the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. Means followed by the same letter within a column are not statistically different according to Fisher’s Protected LSD (α= 0.05). b Abbreviations: fb, followed by; EPOST, early postemergence; MPOST, mid-postemergence; LPOST, late- postemergence. c Application timing: PRE, at planting; EPOST, 10-cm weeds; MPOST, 10-cm weed re-growth; V2-V3, two to three trifoliate; LPOST, 30-cm weeds. d POST treatments included ammonium sulfate at 3.38 kg/Ha. e Site-years: AMATA, Boone county 2010, Calloway county 2010 and 2011; XANST, Boone county 2010 and 2011; SETFA, Calloway county 2010 and 2011; DIGSA, Calloway county 2010 and 2011; ECHCG, Calloway county 2010 and 2011.

Table 2.4. Comparisond of herbicide programs containing glufosinate plus 2,4-D on late-season annual grass and broadleaf weed control across four site-yearse in Missouri.a Weed species Herbicide program AMATA XANST SETFA DIGSA ECHCG

------% Visual control ------

PRE fb POST vs 2-pass POSTbc 97 vs 95 * 82 vs 91 * 96 vs 99 * 90 vs 96 * 95 vs 97 NS

PRE fb POST vs 1-pass POST residual 97 vs 84 * 82 vs 84 NS 96 vs 86 * 90 vs 81 NS 95 vs 97 NS

PRE fb POST vs 1-pass LPOST 97 vs 84 * 82 vs 90 * 96 vs 94 NS 90 vs 57 * 95 vs 73 *

2-pass POST vs 1-pass POST residual 95 vs 84 * 91 vs 84 * 99 vs 86 * 96 vs 81 * 97 vs 97 NS 42

2-pass POST vs 1-pass LPOST 95 vs 84 * 91 vs 90 NS 99 vs 94 * 96 vs 57 * 97 vs 73 *

1-pass POST residual vs 1-pass LPOST 84 vs 84 NS 84 vs 90 NS 86 vs 94 * 81 vs 57 * 97 vs 73 * a Data were pooled by environment (location and year) by the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. b Abbreviations: fb, followed by; EPOST, early postemergence; MPOST, mid-postemergence; LPOST, late- postemergence. c POST treatments included ammonium sulfate at 3.38 kg/Ha. d A priori orthogonal contrasts. * Significance (P < 0.05). e Site-years: AMATA, Boone county 2010, Calloway county 2010 and 2011; XANST, Boone county 2010 and 2011; SETFA, Calloway county 2010 and 2011; DIGSA, Calloway county 2010 and 2011; ECHCG, Calloway county 2010 and 2011.

Table 2.5. Influence of herbicide programs that contain glufosinate or glufosinate plus 2,4-D on soybean yield across four site-yearse in Missouri.a

Treatment Timingc Rate Yield

----- kg ai Ha ------kg Ha -----

Sulfentrazone + chloransulam PRE 0.139 + 0.018 2857 b-d Glufosinate EPOSTbd 0.45

Sulfentrazone + chloransulam PRE 0.139 + 0.018 2680 d Glufosinate + 2,4-D EPOST 0.45 + 0.56

Sulfentrazone + chloransulam PRE 0.139 + 0.018 2817 b-d Glufosinate + 2,4-D EPOST 0.45 + 0.84

Sulfentrazone + chloransulam PRE 0.139 + 0.018 2817 b-d Glufosinate + 2,4-D EPOST 0.45 + 1.12

Glufosinate EPOST 0.45 2772 b-d Glufosinate MPOST 0.45

Glufosinate EPOST 0.45 2871 a-d Glufosinate + 2,4-D MPOST 0.45 + 0.56

Glufosinate EPOST 0.45 2808 b-d Glufosinate + 2,4-D MPOST 0.45 + 0.84

Glufosinate EPOST 0.45 2910 a-d Glufosinate + 2,4-D MPOST 0.45 + 1.12

Glufosinate EPOST 0.45 + 0.56 2916 a-d Glufosinate + 2,4-D MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 0.84 2861 a-d Glufosinate MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 1.12 2927 a-c Glufosinate MPOST 0.45

Glufosinate + 2,4-D EPOST 0.45 + 0.56 3102 a Glufosinate MPOST 0.45 + 0.56

Glufosinate + 2,4-D EPOST 0.45 + 0.84 2829 b-d

Glufosinate MPOST 0.45 + 0.84

Glufosinate + 2,4-D EPOST 0.45 + 1.12 2723 b-d Glufosinate + 2,4-D MPOST 0.45 + 1.12

Glufosinate + 2,4-D V2-V3 0.45 + 0.56 2956 ab + S-metolachlor + 1.2 + Fomesafen + 0.27

Glufosinate + 2,4-D V2-V3 0.45 + 0.56 2689 cd + Acetochlor + 1.27

Glufosinate + 2,4-D LPOST 0.59 + 1.12 2692 cd

Glufosinate + 2,4-D LPOST 0.73 + 1.12 2806 b-d

Weedy control 1699 e

Weed-free control 2862 a-d a Data were pooled by environment (location and year) by the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. Means followed by the same letter within a column are not statistically different according to Fisher’s Protected LSD (α= 0.05). b Abbreviations: fb, followed by; EPOST, early postemergence; MPOST, mid- postemergence; LPOST, late-postemergence. c Application timing: PRE, at planting; EPOST, 10-cm weeds; MPOST, 10-cm weed re-growth; V2-V3, two to three trifoliate; LPOST, 30-cm weeds. d POST treatments included ammonium sulfate at 3.38 kg/Ha. e Site-years: Yield, Boone county 2010 and 2011, Calloway county 2010 and 2011.

Table 2.6. Comparisond of herbicide programs containing glufosinate plus 2,4-D on soybean yield across four site-yearse in Missouri.a Herbicide program Soybean Yield

------kg Ha ------

PRE fb POST vs 2-pass POSTbc 2793 vs 2872 NS

PRE fb POST vs 1-pass POST residual 2793 vs 2823 NS

PRE fb POST vs 1-pass late POST 2793 vs 2749 NS

2-pass POST vs 1-pass POST residual 2872 vs 2823 NS

2-pass POST vs 1-pass late POST 2872 vs 2749 NS

1-pass POST residual vs 1-pass late POST 2823 vs 2749 NS a Data were pooled by environment (location and year) by the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. b Abbreviations: fb, followed by; EPOST, early postemergence; MPOST, mid- postemergence; LPOST, late-postemergence.c POST treatments included ammonium sulfate at 3.38 kg ai/Ha. d A priori orthogonal contrasts. * Significance (P < 0.05). e Site-years: Yield, Boone county 2010 and 2011, Calloway county 2010 and 2011.

CHAPTER III

INFLUENCE OF WEED HEIGHT AND GLUFOSINATE PLUS 2,4-D

COMBINATIONS ON WEED CONTROL IN 2,4-D RESISTANT SOYBEAN

ABSTRACT

Introduction of transgenic crops with resistance to 2,4-D will provide growers with new weed management options in soybean. To better understand the utility of this technology in soybean production systems, field and greenhouse experiments were conducted in 2010 and 2011 to investigate the effects of weed height and the compatibility of glufosinate and 2,4-D combinations on weed control in soybean with resistance to 2,4-D and glufosinate. Results from these experiments indicate that, when applied alone, a significant increase in the rate of glufosinate or 2,4-D is needed in order to achieve similar levels of weed control as lower rates of glufosinate plus 2,4-D applied in combination. Sequential POST herbicide programs that integrated 2,4-D amine with glufosinate enhanced the control of common waterhemp compared to sequential applications of glufosinate alone. The addition of either rate of 2,4-D to 0.45 kg/Ha glufosinate improved common waterhemp control by 3 to 10% for 10-to 15-cm applications, by 14 to 15% for 20- to 25-cm applications, and by 17 to 18% for 30- to 35-

46 cm applications. Glufosinate plus 2,4-D combinations also improved the control of

Asiatic dayflower and barnyardgrass by 28 to 77% and 1 to 19% respectively, compared to applications of either of these herbicides alone, however antagonism of large crabgrass was observed with this combination in both field and greenhouse experiments.

Reductions in weed control were observed in response to increased weed heights, however sequential glufosinate and 2,4-D applications were less affected by weed height than were sequential glufosinate-only applications. Soybean yields were also reduced by approximately 3% in response to 30- to 35-cm compared to 10- to 15-cm herbicide applications. Overall, results from these experiments indicate that glufosinate plus 2,4-D combinations can provide increased control of problematic weeds like Asiatic dayflower and common waterhemp while providing similar grass control as herbicide programs that contain glufosinate alone.

INTRODUCTION

The adoption of glyphosate-resistant (GR) crops has increased steadily since the introduction of GR soybean in 1996 (USDA 2009). In the United States, GR soybean hectares increased from 13% in 1997 to 88% in 2005 (Sankula 2006). Concurrent with the increased adoption of GR crop technologies came a corresponding increase in glyphosate use, and a shift in the total number of active ingredients used in soybean production. In 1995, 11 herbicidal active ingredients were applied on 10% of the soybean acreage. By 2002, this number had declined to only 1, which has contributed to the selection of GR weeds (Young 2006). Currently, 13 weed species are resistant to glyphosate in the United States: annual bluegrass (Poa annua L.), common ragweed

(Ambrosia artemisiifolia L.), common waterhemp (Amarathus rudis Sauer.), giant

47 ragweed (Ambrosia trifida L.), goosegrass (Eleusine indica L. Gaertn.), hairy fleabane

(Conyza bonariensis L. Cronq.), horseweed (Conyza canadensis L. Cronq.), Italian ryegrass (Lolium multiflorum Lam. Husnot), johnsongrass (Sorghum halepense L. Pers.), junglerice (Echinochloa colona L. Link.), kochia (Kochia scoparia L. Schrad.), palmer amaranth (Amaranthus palmeri S. Wats.), and rigid ryegrass (Lolium rigidum Gaudin.)

(Heap 2010).

One herbicide that can provide good control of certain GR broadleaf weeds is 2,4-

D (Loux 2008). Currently, 2,4-D is labeled for selective, post-emergence (POST) broadleaf weed control in corn, grain sorghum, rice, sugarcane, turfgrass, various small grain and grass forage crops, as well as non-crop uses. After more than 60 years of use,

2,4-D is still today the third most widely used herbicide in the United States, and the most widely used herbicide in the world. (Industry Task Force II 2005). Dow AgroSciences

LLC is currently developing corn, soybean, and cotton with a trait that confers resistance to pre-plant or postemergence (POST) applications of 2,4-D (Simpson et al. 2009; Wright et al. 2010). The transgene responsible for the degradation of 2,4-D (AAD-12) is a bacterial substrate of the aryloxyalkanoate dioxygenase enzyme (AAD). AAD-12 acts on pyridyloxyacetate auxin herbicides such as triclopyr and fluroxypyr, along with 2,4-D

(Wright et al. 2010). The availability of cotton and soybean with resistance to 2,4-D should provide growers with a new option for the control of GR weeds like horseweed, hairy fleabane, kochia, common waterhemp, palmer amaranth, and common and giant ragweed in these crops. Anderson et al. (1996) reported over 90% control of common waterhemp when applied to 2.5- to 7.5-cm plants at rates of 2,4-D as low as 0.28 kg/Ha.

Similarly, in field studies conducted by Kruger et al. (2010), at least 90% control of GR

48 horseweed was achieved with 0.56 kg/Ha at heights up to 30-cm in Indiana fields.

However, a greenhouse screen of horseweed populations collected in Indiana revealed that some populations exhibited tolerance to 2,4-D at rates ranging from two- to three- fold the recommended use rate (Kruger et al. 2008; Kruger et al 2010). Kochia and common waterhemp populations have also been characterized with resistance to 2,4-D in

North Dakota and Nebraska respectively (Berbards et al. 2012; Nandula and Manthey

2010).

Plant size is one factor that influences the degree of weed control achieved with

2,4-D. Everitt and Keeling (2007) found that 2,4-D rates of 0.56 and 1.12 kg/Ha controlled 3- to 8-cm horseweed ≥ 92% by 28 days after treatment (DAT). However, reduced control of horseweed was observed with these same rates of 2,4-D when applied to 10- to 15-cm and 25- to 46-cm horseweed. A similar response to 2,4-D has also been reported with other weed species such as red morningglory (Ipomoea coccinea L.) and dogfennel (Eupatorium capillifolium Lam. Small.). Seibert et al. (2004) observed 100% control of 30-cm red morningglory, however a 6 to 19% reduction in control was observed when 2,4-D was applied to 60-cm plants. Dogfennel control was reduced from

85 to 70 to 6% when applications of 2,4-D and dicamba were applied to plants 36-, 72-, and 154-cm in height, respectively (Sellers et al. 2009).

Application rate is another factor that often determines the level of weed control achieved with 2,4-D. Several authors have observed increases in broadleaf weed control in response to higher application rates of 2,4-D (Everitt and Keeling 2007; Sarabi et al

2011; Siebert et al 2004). Everitt and Keeling (2007) found that increasing the rate of

2,4-D from 0.20- to 0.56-kg/Ha improved the control of both Russian thistle (Salsola

49 iberica Sennen. & Pau.) and horseweed. Red Morningglory control was increased by 6% in 2001 and 17 % in 2002 when rates of 2,4-D increased from 0.53 to 1.1 kg/Ha, with levels reaching as high as 100% control at the 1.1 kg/Ha rate (Siebert et al. 2004).

Similarly, Sarabi et al (2011) observed less than 80% control of redroot pigweed

(Amaranthus retroflexus L.) with 2,4-D rates of 0.4 kg/Ha or lower, but 100% control of this species was achieved with 2,4-D rates ranging from 0.6 to 1 kg/Ha.

Synergism is a term that can describe an agrochemical’s ability to interact with another agrochemical in such a way that overall weed control is improved compared to the effect of each agrochemical independently. Benefits could include increased weed control, decreased use rates, and reduced toxicity on non-target plants. Antagonism is when agrochemicals have adverse effects when applied in combination rather than separately (Hatzios et al. 1985; Akobundu et al. 1975). Some authors have observed a synergistic response with co-applications of certain herbicides with 2,4-D (Waltz et al.

2003), while others have reported antagonistic interactions. Steckel et al. (2006) reported greater GR horseweed control was achieved with 0.47 kg glufosinate/Ha plus 0.53 kg

2,4-D/Ha than with glufosinate alone, and that this combination also provided some residual control compared to a single application of glufosinate. Other authors have reported synergistic interactions between 2,4-D and ALS-inhibiting herbicides on common lambsquarters (Chenopodium album L.) and trumpetcreeper (Campsis radicans

L. Seem. Ex. Bureau.) (Bradley et al. 2003; Hart 1997; Isaacs et al. 2006). However, antagonistic responses have been observed with co-applications of 2,4-D plus fenoxaprop, imazethapyr plus imazapyr, haloxyfop, and sethoxydim on johnsongrass

(Martin et al. 2007: Mueller et al. 1989). Similarly, 2,4-D co-applications with

50 nicosulfuron and rimsulfuron antagonized green foxtail (Setaria viridis L. Beauv.), while combinations of 2,4-D and atrazine with nicosulfuron and rimsulfuron have shown antagonism on green foxtail as well as barnyardgrass (Echinochloa crus-galli L. Beauv.)

(Hennigh et al. 2010). Young et al. (1996) reported a 5 to 6 % reduction in giant foxtail

(Setaria faberi Herrm.) and large crabgrass (Digitaria sanguinalis L. Scop.) control when

2,4-D was combined with sethoxydim, and an 18% reduction in shattercane (Sorghum bicolor L. Moench ssp. arundinaceum Desv. De wet & Harlan) control with 2,4-D plus sethoxydim compared to sethoxydim alone.

Although a limited amount of research has been conducted on the pre-plant utility of 2,4-D and glufosinate combinations, little research has been conducted on POST applications of these herbicide combinations in soybean with resistance to 2,4-D and glufosinate. Additionally, the influence of weed height and the question of whether these two active ingredients act synergistically or antagonistically when applied in combination has not been thoroughly investigated. The objectives of this research was to determine the influence of weed height and glufosinate plus 2,4-D rate combinations on summer annual grass and broadleaf weed control in soybean with resistance to glufosinate and

2,4-D.

MATERIALS AND METHODS

Site Description.

Duplicate field experiments were conducted at two locations in Missouri during the summers of 2010 and 2011. Each year, one experiment was conducted in Boone

County, Missouri at the University of Missouri Bradford Research and Extension Center

(38°53'N, 92°12'W), and another was located in Callaway County near Mokane, Missouri

(38°39'N, 91°52'W). Sites were selected based on the presence of dense infestations of a variety of summer annual grass and broadleaf weed species. The weeds present at the

Boone County site included common waterhemp, common cocklebur (Xanthium strumarium L.), ivyleaf morningglory (Ipomoea hederacea Jacq.), giant foxtail, large crabgrass, and barnyardgrass. At the Callaway County site, the only weed present was common waterhemp. The soil type at the Boone County location was a Mexico silt loam

(fine, smectic, mesic Aeric Vertic Epiaqualfs) with 2.3% organic matter and pH of 6.5 in

2010 and a pH of 6.0 and organic matter content of 2.4% in 2011. At the Callaway

County site, the soil type was a Hodge fine sand, loamy substratum (mixed, Mesic Typic

Udipsamments) with organic matter content of 1.4 and 1.5% and pH of 6.8 and 6.7 in

2010 and 2011, respectively. At each location, glufosinate- and 2,4-D-resistant soybean provided by Dow AgroSciences LLC were planted into a conventionally-tilled seedbed in rows spaced 76-cm apart at a seeding rate of 395,000 seeds/Ha. In all experiments, the experimental design consisted of a randomized complete block and each treatment was replicated 6 times. Individual plots were 2- by 9-m in size. All herbicide applications were applied at 5 km hˉ¹ with a CO₂-powered backpack sprayer delivering 140 L/Ha with flat fan nozzle tips¹.

Treatment Information.

In each experiment, glufosinate (Ignite® 280 SL, Bayer CropScience) was applied at 0.45 kg/Ha alone and in combination with 2,4-D (Weedar® 64, Nufarm) at

0.56, 0.84 and 1.1 kg/Ha at 10- to 15-, 20- to 25-, and 30- to 35-cm application timings.

Glufosinate was also applied alone at 0.59 and 0.73 kg/Ha at each application timing. All treatments were followed with a sequential POST application of glufosinate at 0.45

52 kg/Ha once weed escapes and/or weed regrowth in response to a given treatment reached

10-cm in height. Ammonium sulfate was added to all treatments at 0.34 kg/Ha, and a non-treated control and weed-free control were also included for comparison. A detailed list of seeding dates, herbicide application dates, and soybean and weed stages at the time of each herbicide application are listed in Table 3.1.

Visual evaluations of weed control crop injury were taken at regular intervals up to two weeks after the final herbicide applications were made on 30- to 35-cm weeds.

Visual ratings were based on a scale of 0 to 100, with 0 indicating no control or injury and 100 indicating plant death. Visual weed control and soybean yield data were analyzed using the PROC MIX procedure in SAS (SAS 9.2, SAS® Institute Inc.). As suggested by Carmer et al. (1989), year-location combinations were considered an environment sampled at random; herbicide treatment and application timing were considered fixed effects in the model while environment, replications, and interactions within environment and replications were considered random effects. Weed control data were transformed using arcsine of the square root. Transformations did improve the model for weed control. Analyses for this data were performed on the transformed means detected using Fisher’s protected LSD at α= 0.05. Means were then back transformed for data presentation. Yield data did not require transformation. Contrast comparisons among herbicide programs represent a priori orthogonal contrasts. These pairwise comparisons were made across all site-years allowing for the determination of whether differences exist among 10- to 15-cm, 20- to 25-cm, and 30- to 35-cm application timings.

Greenhouse Experiments.

Separate experiments were conducted on each of the following summer annual weeds: Asiatic dayflower (Commelina communis L.), barnyardgrass, giant ragweed, common cocklebur, common waterhemp, and large crabgrass. In all greenhouse trials, seed from each representative weed species were broadcast over 30- by 60-cm greenhouse flats containing commercial potting medium (Pro-Mix, Hummert

International). This same medium was used to cover the seedbed at approximately 6- to

12-mm depending upon seed size. After emergence, single plants were transplanted into

15-cm greenhouse pots containing a 1:1 mixture of commercial potting medium to soil.

All plants were maintained in a greenhouse at 30- to 35-C, watered and fertilized as needed, and provided with artificial lighting from metal halide lamps (600 µmol photon m-2 s-1) simulating a 15-h photoperiod day.

All rates of glufosinate and 2,4-D were applied alone or in combination and were arranged factorially. Glufosinate was applied at 0, 0.45, 0.59, and 0.73 kg/Ha while 2,4-

D was applied at 0, 0.56, 0.84, and 1.1 kg/Ha. All herbicide treatments were applied at two application timings; plants reaching 15- and 30-cm in height. Ammonium sulfate was added to all treatments at 1.44 kg/Ha. All treatments were applied with a compressed air laboratory spray chamber equipped with an even flat-fan spray nozzle delivering 220 L/Ha at 234 kPa.

Visual evaluations of weed control were taken at 3, 7, 14, and 21 days after treatment (DAT) and were based on a scale of 0 to 100, with 0 equal to the untreated control and 100 equal to complete plant death. Visual weed control from the 21 DAT evaluations are presented in Tables 3.6 and 3.7.

All greenhouse experiments were arranged in a completely randomized design and each experiment was conducted twice. All treatments were replicated six times. A

Colby analysis was conducted on several common summer annual weed species to determine synergistic, antagonistic, or additive effects of glufosinate plus 2,4-D combinations. Expected weed control (Ei) with each respective herbicide combination was calculated using Colby’s equation (1967), by inserting the observed means for glufosinate (X) and 2,4-D (Y) alone at Xi and Yi rates into equation 1:

Ei = 100 – [((100 – Xi)(100 – Yi))/100] (1)

Expected values were separated from observed values using a t-test for matched samples (P< 0.05), as proposed by Flint et al. (1988). Antagonism was concluded when the difference among observed minus the expected values was significantly negative.

However, if the difference was significantly positive, both herbicides acted synergistically. If the difference was not significant, the interaction was considered additive. Data were subjected to ANOVA using the general linear models procedure in

SAS. Means were separated using Fisher’s protected LSD test at P ≤ 0.05.

RESULTS AND DISCUSSION

Weed control in field experiments.

All glufosinate sequential POST programs provided 80% or greater grass and broadleaf weed control two weeks after 30- to 35-cm applications (Table 3.2). However, the addition of 2,4-D to glufosinate sequential POST programs provided 85% or greater control of all annual grass and broadleaf weeds evaluated in these experiments. The addition of 2,4-D to any rate of glufosinate enhanced the level of common waterhemp control compared to sequential applications of glufosinate alone regardless of application

55 timing. The addition of either rate of 2,4-D to 0.45 kg/Ha glufosinate improved common waterhemp control by 3 to 10% for 10-to 15-cm applications, by 14 to 15% for 20- to 25- cm applications, and by 17 to 18% for 30- to 35-cm applications. Hillger et al. (2009) also reported enhanced control of taller broadleaf weeds with 2,4-D and glyphosate combinations compared to glyphosate alone when applied to 5- to 10-, 15- to 20- and 25- to 30-cm weeds, while Steckel et al. (2006) observed a 35% increase in horseweed control with applications of glufosinate plus 2,4-D compared to applications of glufosinate alone. Sequential applications of glufosinate plus 2,4-D provided similar levels of ivyleaf morningglory, common cocklebur, giant foxtail, and large crabgrass control as sequential applications of glufosinate alone. There was one instance where glufosinate plus 2,4-D combinations improved the control of barnyardgrass compared to sequential glufosinate applications.

In contrast to many reports of increased weed control in response to increasing rates of 2,4-D (Everitt and Keeling 2007; Sarabi et al. 2011; Siebert et al. 2004), in these experiments increasing the rate of 2,4-D did not improve the level of grass or broadleaf weed control when applied in combination with glufosinate (Table 3.2). Additionally, in only one instance, increasing the rate of 2,4-D from 0.84 to 1.12 kg/Ha resulted in a reduction in barnyardgrass control at the 10- to 15-cm timing (Table 3.2). Hennigh et al.

(2010) also observed reduced control of barnyardgrass when 2,4-D was applied in combination with atrazine, nicosulfuron and rimsulfuron. Similarly, increasing the rate of glufosinate alone rarely resulted in higher levels of weed control. At the 20- to 25-cm application timing, increasing the glufosinate rate from 0.45 to 0.73 kg/Ha improved the control of common waterhemp from 84 to 90% and barnyardgrass from 89 to 98%. Guza

56 et al. (2003) also reported increased levels of redroot pigweed (Amaranthus retroflexus

L.) and barnyardgrass control with increasing rates of glufosinate from 0.3 to 0.4 kg/Ha.

Although all glufosinate sequential POST programs provided acceptable levels of grass and broadleaf weed control, the timing at which herbicide applications were made had an impact on the level of weed control achieved. The results from these experiments indicate that herbicide applications made later in the season to taller weeds can result in lower levels of weed control. When averaged across all sequential POST programs, herbicide applications made at the 30- to 35-cm timing compared to the 10- to 15-cm timing resulted in lower levels of ivyleaf morningglory and large crabgrass control, and herbicide applications made at 30- to 35-cm compared to 20- to 25-cm resulted in lower levels of common waterhemp and large crabgrass control (Table 3.3). Hoss et al. (2003) also reported that the control achieved with glufosinate applications to 8-cm ivyleaf morningglory plants was reduced by 45% when the same treatment was applied to 30-cm plants. Reductions have also been found in the control of common cocklebur and

Pennsylvania smartweed (Polygonum pensylvanicum L.) with glufosinate rates of 0.42 and 0.56 kg/Ha when applied to 15- compared to 10-cm weeds (Steckel et al. 1997). In this research, there were also two instances where lower weed control was observed in response to early, rather than late herbicide applications; 10- to 15-cm applications provided significantly lower common waterhemp and common cocklebur control compared to 20- to 25-cm applications (Table 3.2). In the case of common cocklebur, lower control was also observed in 10- to 15-cm compared to 30- to 35-cm applications.

In both instances, this response can be attributed to the later emergence of these weed species after the sequential POST applications had been made (Hartzler et al. 1999;

Norsworthy and Oliveira 2007). Weed height had less of an effect on sequential applications of 2,4-D and glufosinate combinations than sequential applications of glufosinate applied alone, especially in the case of common waterhemp. This suggests that sequential glufosinate plus 2,4-D applications allow for a wider window of application to GR and other annual broadleaf weeds, and may result in less yield loss due to in-crop competition from larger weeds that aren’t adequately controlled by sequential applications of glufosinate alone.

Sequential applications of glufosinate and 2,4-D provided greater control of common waterhemp than sequential glufosinate-only programs at all application timings

(Table 3.3). Both sequential POST programs provided high levels of ivyleaf morningglory control, but sequential POST programs of glufosinate plus 2,4-D provided a slight increase in control when applied to 20- to 25-cm weeds compared to sequential

POST applications of glufosinate alone. Other authors have also reported high levels of ivyleaf morningglory control with glufosinate (Everman et al. 2007; Koger et al. 2007;

Krausz et al. 1999). Large crabgrass and barnyardgrass control were reduced from 94 to

89% and 93 to 89%, respectively, at the 20- to 25-cm timing with the addition of 2,4-D, indicating some tendency towards antagonism of these two active ingredients on grass species at later application timings. This corresponds to a report by Young et al. (1996) who found a 5 to 6% reduction in large crabgrass control with 2,4-D and sethoxydim combinations compared to sethoxydim alone.

Soybean injury and yield.

No more than 5% visual injury was observed in response to any glufosinate plus 2,4-D treatment at any time interval after treatment (data not shown). All herbicide treatments

58 resulted in higher yields than the untreated control (Table 3.4). Previous research has indicated that soybean yield losses should be expected if herbicide applications are delayed until weeds reach 15- to 23-cm in height, or before soybeans reach the V3 to V4 stage of growth (Dalley et al. 2004; Mulugetta and Boerboom 2000; Van Acker et al.

1993). Although all treatments differed from the untreated control, there were few differences in soybean yield among the herbicide treatments evaluated in these experiments (Table 3.4). When averaged across all sequential POST programs, soybean yield was reduced by approximately 3% in response to 30- to 35-cm compared to 10- to

15-cm herbicide applications (Table 3.5). Other comparisons of the sequential POST programs evaluated in this research revealed that most of the reductions in soybean yield could be attributed to later, rather than earlier, application timings (Table 3.5). Herbicide applications made later in the season allow weeds to compete with the crop for water, nutrients, and light, resulting in soybean yield losses (Dalley et al. 2004; Gower et al.

2003).

Greenhouse experiments.

Single applications of glufosinate and 2,4-D provided 75% or greater control of all 15-cm dicot weed species (Table 3.6). Increasing the rate of glufosinate or 2,4-D did not improve the level of common cocklebur or giant ragweed control when applied at the

15-cm timing, but did improve the control of common waterhemp. Common waterhemp control increased from 78 to- 95% with higher rates of 2,4-D, and from 75 to 92% with higher rates of glufosinate. Control of 15-cm common cocklebur and giant ragweed was generally similar with glufosinate or 2,4-D, regardless of rate. However, applications of

2,4-D at 0.84 and 1.12 kg/Ha to 15-cm common waterhemp provided greater control of

59 this species than glufosinate at either 0.45 or 0.59, but not at 0.73 kg/Ha. Other authors have also reported that increasing the rate of glufosinate can result in higher levels of weed control (Guza et al. 2003; Steckel et al. 1997).

Glufosinate was influenced more by dicot weed height than was 2,4-D (Table

3.6). At the 30-cm application timing, some reduction in common waterhemp, common cocklebur, and giant ragweed control occurred with glufosinate applications to 30- compared to 15-cm plants, depending on glufosinate rate. Conversely, only common waterhemp control was reduced with 0.84 and 1.12 kg/Ha 2,4-D at the 30- compared to the 15-cm application timing. However, similar levels of common cocklebur and giant ragweed control were achieved with all rates of 2,4-D, regardless of application timing.

This response is similar to the results observed in field experiments, and agrees with other researchers who have found reduced control with increased weed heights (Everitt and Keeling 2004; Knezevic et al.2009; Seibert et al. 2004: Steckel et al. 1997). Tharp et al. (1999) reported higher GR50 values for several weeds when applications were made to

15- to 30-cm plants rather than 4- to 8-cm plants, thereby requiring higher herbicide doses in order to achieve similar levels of control. At the 30-cm application timing, any rate of 2,4-D provided better control of giant ragweed than 0.45 or 0.59 kg/Ha glufosinate, and better control of common cocklebur than any rate of glufosinate.

Many researchers have found that herbicides applied in combination can provide better control than applications of those herbicides alone (Hillger et al. 2009; Isaacs et al.

2006; Gonzini et al. 1999). When glufosinate and 2,4-D combinations were applied to

15-cm plants, all rates of 2,4-D improved the control of common waterhemp compared to applications of glufosinate alone at 0.45 and 0.59 kg/Ha (Table 3.6). Similarly, the

60 addition of any rate of glufosinate to 0.56 kg 2,4-D/Ha provided higher control of common waterhemp than 0.56 kg/Ha 2,4-D alone. However, glufosinate plus 2,4-D combinations provided similar levels of common cocklebur and giant ragweed control as any rate of 2,4-D or glufosinate alone at the 15-cm application timing, indicating that increased rates or herbicide combinations are not needed for the control of these dicot species.

At the 30-cm application timing, all rates of 2,4-D in combination with any rate of glufosinate provided higher control of common waterhemp than any rate of glufosinate alone (Table 3.6). Also, any rate of glufosinate added to 2,4-D at 0.84 and 1.12 kg/Ha controlled common waterhemp more effectively than these rates of 2,4-D alone.

Although the majority of the glufosinate plus 2,4-D combinations provided similar or increased levels of common cocklebur control than applications of either glufosinate or

2,4-D alone, there were instances when antagonism was observed. Reduced control of

30-cm common cocklebur plants occurred with 0.59 kg/Ha glufosinate plus 0.56, 0.84, and 1.12 kg 2,4-D/Ha in comparison to applications of either rate of 2,4-D alone.

However, when the rate of glufosinate was increased to 0.73 kg/Ha in combination with either rate of 2,4-D, this antagonism was overcome. This is similar to findings by Koger et al. (2007), who found that by increasing the rate of glufosinate, antagonism by MSMA was overcome. As with common cocklebur, the majority of glufosinate plus 2,4-D combinations provided similar or increased levels of giant ragweed control at the 30-cm timing than applications of either glufosinate or 2,4-D alone. However, antagonism was also observed with the 0.73 kg/Ha glufosinate plus 0.56 kg/Ha 2,4-D combination which was overcome by increasing the rate of 2,4-D.

Control of monocot species was much lower than that of dicots with single applications of glufosinate or 2,4-D, regardless of weed height (Table 3.7). Applications of glufosinate or 2,4-D alone provided from 0 to 22% control of Asiatic dayflower, from

0 to 78% control of large crabgrass, and from 0 to 19% control of barnyardgrass.

Increasing the rate of glufosinate did not increase the control of Asiatic dayflower or barnyardgrass, regardless of application timing. However, increasing the rate of glufosinate from 0.45 to 0.59 or 0.73 kg/Ha provided higher control of large crabgrass when applied to 15-cm plants, but at the 30-cm application timing, only the 0.73 kg/Ha glufosinate rate provided higher large crabgrass control than 0.45 kg/Ha.

At the 15-cm application timing, the observed percentages were higher than the expected values for Asiatic dayflower control, indicating that synergism was observed with all glufosinate plus 2,4-D combinations (Table 3.7). All rate and herbicide combinations improved control of Asiatic dayflower compared to applications of glufosinate and 2,4-D alone. A similar response was observed with these combinations when applied to 30-cm asiatic dayflower plants, although the overall levels of control were lower with 30- compared to 15-cm applications. Asiatic dayflower is a difficult weed to control and there are few herbicide options that provide effective control (Owen and Zeleya 2005; Ulloa and Owen. 2009). The extended emergence pattern and natural tolerance of this species to glyphosate leaves few options for control in most soybean production systems. Ulloa and Owen (2009) reported single applications of 0.86-kg glyphosate in field research provided 50% control, and even poorer control was found under greenhouse conditions. Even when applications were made to two-leaved asiatic dayflower, single glyphosate applications at rates of 3.36-kg/Ha only provided 28%

62 control (Ulloa and Owen 2009). The results from these experiments indicate that higher levels of control of this problematic species may be obtained with glufosinate plus 2,4-D combinations compared to current POST alternatives in GR soybeans.

The tendency towards antagonism of large crabgrass control with glufosinate and

2,4-D combinations that was observed in field experiments was verified in these greenhouse experiments, especially with applications made to 15-cm plants (Table 3.7).

At the 30-cm application timing, only the highest rates of glufosinate and 2,4-D were antagonistic compared to applications of glufosinate alone. Reports of antagonism on large crabgrass have also been reported with 2,4-D and sethoxydim combinations (Young

1996). Antagonism with 2,4-D and fenoxaprop combinations has also been reported by

Mueller et al. (1989) on johnsongrass. Numerous experiments have been conducted to better understand the mechanism of action of growth regulators with conflicting reports.

While some research suggests the mechanism of action of growth regulators cause the plant to grow themselves to death, other research has found overdoses of auxin leads to a deregulation in plant growth (Gilbert 1946; Grossmann 2010). There have also been a variety of receptor proteins and transport inhibitors reported to have a role in the processes leading to plant susceptibility to growth regulator herbicides like 2,4-D (Kelly and Riechers 2007; Vanneste and Friml 2009;Woodward and Bartel 2005). Although there is still some uncertainty surrounding the exact mechanism of action and the many plant processes that are affected by 2,4-D, it is likely that the disruption of cells could reduce the absorption and/or translocation of glufosinate when these two herbicides are applied in combination on certain grass species (Croon et al. 1989; Culpepper et al. 1999;

Duke1992; Grossmann 2010; Olson 1982; Pereira and Crabtree 1986;). Since the

63 disruption of cells by 2,4-D generally occurs within the first 1- to 4-hours after application, it seems most likely that this is the time interval where glufosinate is impacted the most, as maximum glufosinate absorption rates have been found to occur within 24 hours after application (Grossman 2010; Steckel et al. 1997). The result can be less inhibition of glutamine synthetase, leading to reductions in ammonia accumulation and therefore reduced levels of weed control.

Although there were some glufosinate plus 2,4-D combinations that acted synergistically on barnyardgrass, especially with higher rates of glufosinate at the 30-cm timing, control of this species never exceeded 39% with any herbicide or combination of herbicides. Additionally, there was no difference in the control of barnyardgrass with any treatment at the 15- or 30-cm application timings. This is similar to reports from other authors who have also observed poor control of barnyardgrass with glufosinate

(Koger et al. 2007; Price et al. 2008). Price et al. (2008) observed from 5 to 64% control of barnyardgrass control with glufosinate tank mixes while Koger et al. reported only

38% control with sequential glufosinate applications.

Overall, results from these experiments indicate that sequential POST herbicide programs that incorporate 2,4-D amine with glufosinate can enhance the control of problematic species like common waterhemp compared to sequential POST programs of glufosinate alone, especially when the initial applications are made to taller weeds.

Additionally, these results indicate that, perhaps with the exception of large crabgrass, these glufosinate plus 2,4-D combinations should provide similar levels of grass weed control as glufosinate alone. However, sequential POST programs applied later to taller weeds will reduce the level of weed control, and can potentially lead to yield reductions.

Although there are some instances of antagonism of glufosinate plus 2,4-D on large crabgrass and common cocklebur, combinations of 2,4-D and glufosinate bring added utility by improving the control of problematic weeds like Asiatic dayflower and common waterhemp, and often allow for wider windows of application to these and other annual broadleaf weeds.

LITERATURE CITED

Akobundu, I.O., R.D. Sweet, and W.B. Duke. 1975. A method of evaluating herbicide combinations and determining herbicide synergism. Weed Sci. 23:20-25.

Anderson, D.D., F.W. Roeth, and A.R. Martin. 1996. Occurrence and control of triazine- resistant common waterhemp (Amaranthus rudis) in field corn (Zea mays). Weed Technol. 10:570-575.

M.L. Bernards, R.J. Crespo, G.R. Kruger, R.E. Gaussoin, P.J. Tranel. 2012. Confirmation of a 2,4-D resistant waterhemp (Amaranthus tuberculatus) population in Nebraska. Weed Sci. Soc. Am. Abstr. 237.

Bradley, K.W., E.S. Hagood Jr., and P.H. Davis. 2003. Evaluation of Postemergence herbicide combinations for long-term trumpetcreeper (Campsis radicans) control in corn (Zea Mays). Weed Technol. 17:718-723.

Carmer, S.G., W.E. Nyquist, and W.M. Walker. 1989. Least significant differences for combined analysis of experiments with two or three-factor treatment designs. Agron. J. 81:665-672.

Colby, S.R. 1967. Calculating synergistic and antagonistic responses of herbicide combinations. Weeds 15:20-22.

Coetzer, E., K. Al-Khatib, and T.M. Loughin. Glufosinate efficacy, absorption, and translocation in amaranth as affected by relative humidity and temperature. 2001. Weed Sci. 49:8-11.

Croon, K.A., M.L. Ketchersid, and M.C. Merkle. 1989. Effect of bentazon, imazaquin, and chlorimuron on the absorption and translocation of the methyl ester of haloxyfop. Weed Sci. 37:645-650.

Culpepper, A.S., D.L. Jordan, A.C. York, F.T. Corbin, and Y. Sheldon. 1999. Influence of adjuvants and bromoxynil on absorption of clethodim. Weed Technol. 13:536- 541.

Dalley, C.D., J.J. Kells, and K.A. Renner. 2004. Effect of glyphosate application timing and row spacing on corn (Zea mays) and soybean (Glycine max) yields. Weed Technol. 18:165-176.

Duke, S.O. 1992. Modes of action of herbicides used in cotton. Pages 403-437 in C.G. McWhorter and J.L. Abernathy, eds. Weeds of Cotton. Memphis, TN: The cotton foundation.

Everitt, J.D. and J.W. Keeling. 2007. Weed control and cotton (Gossypium hirsutum) response to preplant applications of dicamba, 2,4-D, and diflufenzopyr plus dicamba. Weed Technol. 21:506-510.

Everman, W.J., I.C. Burke, J.R. Allen, J. Collins, and J.W. Wilcut. 2007. Weed control and yield with glufosinate-resistant cotton weed management systems. Weed Technol. 21:695-701.

Flint, J.L., P.L. Cornelius, and M. Barrett. 1988. Analyzing herbicide interactions: a statistical treatment of Colby’s method. Weed Technol. 2:304-309.

Gonzini, L.C., S.E. Hart, and L.M. Wax. 1999. Herbicide combinations for weed management in glyphosate-resistant soybean (Glycine max). Weed Technol. 13:354-360.

Gower, S.A., M.M. Loux, J. Cardina, S.K. Harrison, P.L. Sprankle, N.J. Probst, T.T. Bauman, W. Bugg, W.S. Curran, R.S. Currie, R.G. Harvey, W.G. Johnson, J.J. Kells, M.D.K. Owen, D.L. Regehr, C.H. Slack, M. Spaur, C.L. Sprague, M. Vangessel and B.G. Young 2003. Effect of postemergence glyphosate application timing on weed control and grain yield in glyphosate-resistant corn: results of a 2- yr multistate study. Weed Technol. 17:821-828.

Grossman, K. 2010. Auxin herbicides: current status of mechanism and mode of action. Pest Manag. Sci. 66:113-120.

Guza, C.J., C.V. Ransom, and C.M. Smith. Glufosinate rates, timings, and additives for weed control in glufosinate-resistant sugar beet. J. Sugar Beet Research 40:29-51.

Hart, S.E., and D.J. Maxwell. 1997. Postemergence broadleaf weed control in corn. DeKalb, IL. Research report. Proc. North Cent.Weed Sci. Soc. 52:128-129.

Hartzler, R.G., D.D. Buhler, and D.E. Stoltenberg. 1999. Emergence characteristics of four annual weed species. Weed Sci. 47:578-584.

Hatzios, K. K., and D. Penner. 1985. Interactions of herbicides with other agrochemicals in higher plants. Rev. Weed Sci. 1:1-52.

Heap, I. 2010. The international survey of herbicide resistant weeds. Available www.weedscience.org. Accessed: February 18, 2012.

Hennigh, D.S., K.Al-Khatib, and M.R. Tuinstra. 2010. Postemergence weed control in acetolactate synthase-resistant grain sorghum. Weed Technol. 24:219-225.

Hillger, D.E., M.E. Schultz, D.C. Ruen, B.E. Maddy, A.S. Culpepper, M.M. Loux, and B.G. Young. 2009. Effect of weed size on control of weeds with 2,4-D + glyphosate tank mixes in corn. Proc. North Cent.Weed Sci. Soc. 64:121.

Hoss, N.E., K. Al-Khatib, D.E. Peterson, and T.M. Loughin. 2003. Efficacy of glyphosate, glufosinate, and imazethapyr on selected weed species. Weed Sci. 51:110-117.

Industry Task Force II on 2,4-D research data. 2005. Issue backgrounder. http://www.24d.org/background/Backgrounder-What-is-24D-Dec-2005.pdf. Accessed: January 14, 2010.

Isaacs, A., K. K. Hatzios, H.P. Wilson and J.M. Toler. 2006. Halosulfuron and 2,4-D mixtures’ effects on common lambsquarters (Chenopodium album). Weed Technol. 20:137-142.

Kelley, K.B., and D.E. Riechers. 2007. Recent developments in auxin biology and new opportunities for auxinic herbicide research. Pestic Biochem. Physiol. 89:1-11.

Knezevic, S.Z., A. Datta, J. Scott, R.N. Klein, and J. Golus. 2009. Problem weed control in glyphosate-resistant soybean with glyphosate tank mixes and soil-applied herbicides. Weed Technol. 23:507-512.

Koger, C.H., A.J. Price, J.C. Faircloth, J.W. Wilcut, and S.P. Nichols. 2007. Effect of residual herbicides used in the last POST-directed application on weed control and cotton yield in glyphosate- and glufosinate-resistant cotton. Weed Technol. 21:378-383.

Koger, C.H., I.C. Burke, D.K. Miller, J.A. Kendig, K.N. Reddy, and J.W. Wilcut. 2007. MSMA antagonizes glyphosate and glufosinate efficacy on broadleaf and grass weeds. Weed Technol. 21:159-165.

Krausz, R.F., G. Kapusta, J.L. Mathews, J.L. Baldwin, and J. Maschoff. 1999. Evaluation of glufosinate-resistant corn (Zea mays) and glufosinate: Efficacy on annual weeds. Weed Technol. 13:691-696.

Kruger, G.R., V.M. Davis, S.C. Weller, and W.G. Johnson. 2008. Response and survival of rosette-stage horseweed (Conyza canadensis) after exposure to 2,4-D. Weed Sci. 56:748-752.

Kruger, G.R., V.M. Davis, S.C. Weller, and W.G. Johnson. 2010. Control of horseweed (Conyza canadensis) with growth regulator herbicides. Weed Technol. 24:425- 429.

Kumaratilake, A.R., and C. Preston. 2005. Low temperature reduces glufosinate activity and translocation in wild radish (Raphanus raphanistrum). Weed Sci. 53:10-16.

Loux, M. 2008. Can the DHT trait solve all of our glyphosate resistance problems? Proc. North Cent. Weed Sci. Soc. 63:86.

Martin, J.R., and C.R. Tutt. 2007. Johnsongrass control with postemergence corn herbicides applied alone of in tank mix combinations. Proc. North Cent. Weed. Sci. Soc. 62:12.

Mueller, T.C., W.W. Witt, and M. Barrett. 1989. Antagonism of johnsongrass (Sorghum halepense) control with fenoxaprop, haloxyfop, and sethoxydim by 2,4-D. Weed Technol. 3:86-89.

Mulugetta, D., and C. M. Boerboom. 2000. Critical time of weed removal in glyphosate- resistant Glycine max. Weed Sci. 48:35-42.

Nandula, V.K., and F.A. Manthey. 2002. Response of kochia (Kochia scoparia) inbreds to 2,4-D and dicamba. Weed Technol. 16:50-54.

Norsworthy, J.K., and M.J. Oliveria. 2007. Tillage and soybean effects on common cocklebur (Xanthium strumarium) emergence. Weed Sci. 55:474-480.

Olson, W. and J.D. Naewaja. 1982. Effect of MCPA on 14C-diclofop uptake translocation. Weed Sci. 30:59-63.

Owen, M.D.K., and I.A. Zelaya. 2005. Herbicide-resistant crops and weed resistance to herbicides. Pest Manag. Sci. 61:301-311.

Pereira, W. and G. Crabtree. 1986. Absorption, translocation, and toxicity of glyphosate and oxyfluorfen in yellow nutsedge (Cyperus esculentus). Weed Sci. 34:923-929.

Price, A.J., C.H. Koger, J.W. Wilcut, D. Miller, and E.V. Santen. 2008. Efficacy of residual and non-residual herbicides used in cotton production systems when applied with glyphosate, glufosinate, or MSMA. Weed Technol. 22:459-466.

Rundle, M.F., S.A. Walters, and B.G. Young. 2007. Efficacy of postemergence corn and soybean herbicides on volunteer horseradish (Armoracia rusticana). Weed Technol. 21:501-505.

Sankula, S. 2006. Quantification of the impacts on U.S. agriculture of biotechnology- derived crops planted in 2005. National Center for Food and Agricultural Policy.

Sarabi, V., M.H.R. Mohassel, and M.Valizadeh. 2011. Response of redroot pigweed (Amaranthus retroflexus) to tank mixtures of 2,4-D plus MCPA with foramsulfuron. Australian J. Crop Sci. 5:605-610.

Sellers, B.A., J.A. Ferrell, G.E. MacDonald, and W.N. Kline. 2009. Dogfennel (Eupatorium capillifolium) size at application affects herbicide efficacy. Weed Technol. 23:247-250.

Siebert, J.D., J.L. Griffin, and C.A. Jones. 2004. Red morningglory (Ipomoea coccinea) control with 2,4-D and alternative herbicides. Weed Technol. 18:38-44.

Simpson, D.M., D.C. Rune, E.F. Scherer, M.A. Peterson, S.C. Ditmars, J.M. Ellis, J.S. Richburg, and D.T. Ellis. 2009. Performance of Dow Agrosciences herbicide tolerance trait in soybean. Proc. North Cent. Weed Sci. Soc. 64:21.

Steckel, G.J., L.M. Wax, F.W. Simmons, and W.H. Phillips II. 1997. Glufosinate efficacy on annual weeds is influenced by rate and growth stage. Weed Technol. 11:484- 488. Steckel, G.J., S.E. Hart, and L.M. Wax. 1997. Absorption and translocation of glufosinate on four weed species. Weed Sci. 45:378-381.

Steckel, L.E., C.C. Craig, R.M. Hayes. 2006. Glyphosate-resistant horseweed (Conyza canadensis) control with glufosinate prior to planting no-till cotton (Gossypium hirsutum). Weed Technol. 20:1047-1051.

Ulloa, S.M., and M.D.K. Owen. 2009. Response of Asiatic dayflower (Commelina communis) to glyphosate and alternatives in soybean. Weed Sci. 57:74-80.

[USDA] United States Department of Agriculture. 2009b. Agriculture Statistics Board. June Acreage Report. http://www.nass.usda.gov/Charts_and _Maps/graphics/cornac.gif. Accessed: January 15, 2010.

Van Acker, R. C, S. F. Wiese, and C. J. Swanton. 1993. Influence of interference from a mixed weed species stand on soybean (Glycine max (L.) Merr.) growth. Can. J. Plant Sci. 73:1293-1204.

Vanneste S., and J. Friml, Auxin: a trigger for change in plant development. Cell 136:1005-1016.

Waltz, A.L., A.R. Martin, and K.T. Horky. 2003. Weed control in grain sorghum. N. Cent. Weed Sci. Res. Rep. 60:45-46.

Woodward A.W., and B. Bartel. 2005. Auxin: regulation, action, and interaction. Ann. Bot. 95:707-735.

Young, B.G. 1996. Interactions of sethoxydim and corn (Zea mays) postemergence broadleaf herbicides on three annual grasses. Weed Technol. 10:914-922.

Young, B.G. 2006. Changes in herbicide use patterns and production practices resulting from glyphosate resistant crops. Weed Technol. 20:301-307.

Table 3.1. Dates of major field operations and soybean growth stage and weed height at the time of each herbicide application at the Boone and Calloway County sites in 2010 and 2011. Research location Boone Calloway 2010 2011 2010 2011

Seeding date 5/28 5/6 6/3 6/6

Dates of herbicide applications

10- to 15-cm weeds fb 10-cm weedsa 6/21 fb 7/6 7/6 fb 7/20 6/10 fb 6/24 7/5 fb 7/18

20- to 25-cm weeds fb 10-cm weeds 6/30 fb 7/13 7/8 fb 7/22 6/16 fb 6/28 7/11 fb 7/21

30- to 35-cm weeds fb 10-cm weeds 7/7 fb 7/13 7/12 fb 7/25 6/21 fb 7/ 2 7/14 fb 7/25

72 Soybean growth stages at application

10- to 15-cm weeds fb 10-cm weeds V3 fb R1 V5 fb R1 V4 fb R1 V6 fb R2

20- to 25-cm weeds fb 10-cm weeds V4 fb R2 V5 fb R2 V5 fb R1 V7 fb R2

30- to 35-cm weeds fb 10-cm weeds R1 fb R2 V6 fb R2 V6 fb R1 R1 fb R2

Average size (cm) of weeds at application

10- to 15-cm weeds fb 10-cm weeds 9 fb 10 10 fb 9 10 fb 10 10 fb 10

20- to 25-cm weeds fb 10-cm weeds 14 fb 10 19 fb 11 23 fb 11 25 fb 13

30- to 35-cm weeds fb 10-cm weeds 26 fb 15 28 fb 14 30 fb 20 33 fb 25 a Abbreviations: fb, followed by.

Table 3.2. Influence of weed height and glufosinate plus 2,4-D rate combinations on late season annual grass and broadleaf weed control across four site-yearsd in Missouri.a Weed control Treatmentbc Timing Rate AMATA IPOHE XANST SETFA DIGSA ECHCG

kg/Ha ------% ------

Glufosinate 10- to 15-cm weeds 0.45 87 de 95 ab 80 g 99 ab 87 b-d 85 de 0.59 81 fg 91 a-d 86 c-g 99 a 87 c-e 87 de 0.73 85 de 94 a-d 84 fg 99 a 90 bc 90 b-e

Glufosinate 20- to 25-cm weeds 0.45 84 e-g 94 a-d 97 a 99 a 91 a-c 89 b-e 0.59 88 c-e 90 d 92 a-f 99 a 94 ab 93 bc 0.73 90 cd 90 cd 92 a-e 99 a 97 a 98 a

Glufosinate 30- to 35-cm weeds 0.45 79 g 90 b-d 94 ab 99 a 83 de 90 b-e 0.59 80 g 90 d 94 ab 99 a 85 de 93 b 0.73 79 g 89 d 93 a-e 99 a 85 c-e 92 b-d

Glufosinate + 2,4-D 10- to 15-cm weeds 0.45 + 0.56 94 bc 96 a-c 85 e-g 99 a 90 a-c 92 b-d

73 73 0.45 + 0.84 97 ab 97 a 87 b-g 98 b 86 c-e 93 b

0.45 + 1.12 97 ab 97 a 86 d-g 99 a 90 bc 89 c-e

Glufosinate + 2,4-D 20- to 25-cm weeds 0.45 + 0.56 98 ab 94 a-d 92 a-f 99 a 91 a-c 90 b-e 0.45 + 0.84 99 a 97 ab 95 a-d 99 a 90 bc 89 c-e 0.45 + 1.12 98 ab 96 a-c 96 a 99 a 88 c-e 90 b-e

Glufosinate + 2,4-D 30- to 35-cm weeds 0.45 + 0.56 96 ab 94 a-d 94 a-c 99 a 84 de 90 b-e 0.45 + 0.84 98 ab 95 a-d 98 a 99 a 83 e 92 b-d 0.45 + 1.12 98 ab 92 b-d 95 ab 99 a 82 e 89 b-e a Data were pooled by environment (location and year) using the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. Means followed by the same letter within a column are not statistically different according to Fisher’s Protected LSD (α= 0.05). b All treatments included ammonium sulfate at 3.38 kg/Ha. c All treatments followed with 0.45 kg/Ha glufosinate to 10-cm weeds. d Site-years: AMATA, Boone county 2010, Calloway county 2010 and 2011; XANST, Boone county 2010 and 2011; SETFA, Calloway county 2010 and 2011; DIGSA, Calloway county 2010 and 2011; ECHCG, Calloway county 2010 and 2011.

Table 3.3. Comparison of sequential POST programs containing glufosinate or glufosinate plus 2,4-D on late season annual grass and broadleaf weed control across four site-yearsd in Missouri. Weed controla Herbicide programsbc AMATA IPOHE XANST SETFA DIGSA ECHCG

------% ------

10-15 cm vs. 20-25 cma 90 vs 93* 95 vs 93 85 vs 94* 99 vs 99 89 vs 92* 89 vs 91

20-25 cm vs. 30-35 cmc 93 vs 89* 93 vs 92 94 vs 95 99 vs 99 92 vs 84* 91 vs 91

10-15 cm vs. 30-35 cm 90 vs 89 95 vs 92* 85 vs 95* 99 vs 99 89 vs 84* 89 vs 91

Gluf 10-15 cm vs. gluf 20-25 cm 84 vs 87 94 vs 91 83 vs 94* 99 vs 99 88 vs 94* 87 vs 93*

Gluf 20-25 cm vs. gluf 30-35 cm 87 vs 80* 91 vs 90 94 vs 94 99 vs 99 94 vs 85* 93 vs 92

Gluf 10-15 cm vs. gluf 30-35 cm 84 vs 80* 94 vs 90 83 vs 94* 99 vs 99 88 vs 85* 87 vs 92*

Gluf + 2,4-D 10-15 cm vs. gluf + 2,4-D 20-25 cm 96 vs 98 96 vs 95 86 vs 94* 99 vs 99 89 vs 89 91 vs 89

Gluf + 2,4-D 20-25 cm vs. gluf + 2,4-D 30-35 cm 98 vs 97 95 vs 94 94 vs 96 99 vs 99 89 vs 83* 89 vs 90

74 75

Gluf + 2,4-D 10-15 cm vs. gluf + 2,4-D 30-35 cm 96 vs 97 96 vs 94* 86 vs 96* 99 vs 99 89 vs 83* 91 vs 92

Gluf 10-15 cm vs. gluf + 2,4-D 10-15 cm 84 vs 96* 94 vs 96 83 vs 86 99 vs 99 88 vs 89 87 vs 91*

Gluf 20-25 cm vs. gluf + 2,4-D 20-25 cm 87 vs 98* 91 vs 95* 94 vs 94 99 vs 99 94 vs 89* 93 vs 89*

Gluf 30-35 cm vs. gluf + 2,4-D 30-35 cm 80 vs 97* 90 vs 94 94 vs 96 99 vs 99 85 vs 83 92 vs 90 a A priori orthogonal contrasts. Contrasts are significant (P < 0.05) if denoted with *. b Abbreviations: Gluf, glufosinate; 10-15 cm, 10- to 15-cm weeds; 20-25 cm, 20- to 25-cm weeds; 30-35 cm, 30- to 35-cm weeds. c All treatments followed with 0.45 kg/ha glufosinate to 10-cm weed regrowth and included ammonium sulfate at 3.38 kg/Ha. d Site-years: AMATA, Boone county 2010, Calloway county 2010 and 2011; XANST, Boone county 2010 and 2011; SETFA, Calloway county 2010 and 2011; DIGSA, Calloway county 2010 and 2011; ECHCG, Calloway county 2010 and 2011.

Table 3.4. Soybean yield response to sequential POST programs containing glufosinate or glufosinate plus 2,4-D across four site-yearsc in Missouri.a Treatmentb Timing Rate Yield

-- kg/Ha -- ---kg/Ha---

Glufosinate 10- to 15-cm weeds 0.45 2653 a-e 0.59 2881 ab 0.73 2693 a-e

Glufosinate 20- to 25-cm weeds 0.45 2592 c-e 0.59 2810 a-c 0.73 2660 a-e

Glufosinate 30- to 35-cm weeds 0.45 2880 ab 0.59 2727 a-d 0.73 2790 a-d

Glufosinate + 2,4-D 10- to 15-cm weeds 0.45 + 0.56 2793 a-d 0.45 + 0.84 2893 a 0.45 + 1.12 2740 a-d

Glufosinate + 2,4-D 20- to 25-cm weeds 0.45 + 0.56 2628 a-e 0.45 + 0.84 2436 e 0.45 + 1.12 2521 de

Glufosinate + 2,4-D 30- to 35-cm weeds 0.45 + 0.56 2601 b-e 0.45 + 0.84 2688 a-e 0.45 + 1.12 2539 c-e

Untreated control 1467 f

Weed-free control 2904 a a Data were pooled by environment (location and year) by the PROC MIXED procedure in SAS. Means are presented on the back-transformed scale. Means followed by the same letter within a column are not statistically different according to Fisher’s Protected LSD (α= 0.05). b All treatments followed with 0.45 kg/Ha glufosinate to 10-cm weed regrowth and included ammonium sulfate at 3.38 kg ai/Ha. c Site-years: Yield, Boone county 2010 and 2011, Calloway county 2010 and 2011.

Table 3.5. Comparison of sequential POST programs containing glufosinate or glufosinate plus 2,4-D on soybean yield across four site-yearsd in Missouri. Herbicide Programsbc Yielda

----- kg/Ha -----

10-15 cm vs. 20-25 cm 2775 vs 2608

20-25 cm vs. 30-35 cm 2608 vs 2704

10-15 cm vs. 30-35 cm 2775 vs 2704 *

Gluf 10-15 cm vs. Gluf 20-25 cma 2742 vs 2687 *

Gluf 20-25 cm vs. Gluf 30-35 cm 2687 vs 2798 *

Gluf 10-15 cm vs. Gluf 30-35 cm 2742 vs 2798

Gluf + 2,4-D 10-15 cm vs. gluf + 2,4-D 20-25 cm 2808 vs 2528 *

Gluf + 2,4-D 20-25 cm vs. gluf + 2,4-D 30-35 cm 2528 vs 2610

Gluf + 2,4-D 10-15 cm vs. gluf + 2,4-D 30-35 cm 2808 vs 2610 *

Gluf 10-15 cm vs. gluf + 2,4-D 10-15 cm 2742 vs 2808 *

Gluf 20-25 cm vs. gluf + 2,4-D 20-25 cm 2687 vs 2528 *

Gluf 30-35 cm vs. gluf + 2,4-D 30-35 cm 2798 vs 2610

a A priori orthogonal contrasts. Contrasts are significant (P < 0.05) if denoted with *. b Abbreviations: Gluf, glufosinate; 10-15 cm, 10- to 15-cm weeds; 20-25 cm, 20- to 25-cm weeds; 30-35 cm, 30- to 35-cm weeds. c All treatments followed with 0.45 kg/ha glufosinate to 10-cm weed regrowth and included ammonium sulfate at 3.38 kg/Ha. d Site-years: Yield, Boone county 2010 and 2011, Calloway county 2010 and 2011.

Table 3.6. Control of 15- and 30-cm dicot plants 3 weeks after treatment (WAT) with glufosinate and 2,4-D alone or in combination in greenhouse experiments.a Weed speciesbc AMATA XANST AMBTR Herbicide Rate 15 30 15 30 15 30

-- kg/Ha ------% Visual control 3 WAT ------

Glufosinate 0.45 75 37 96 88 96 77 0.59 76 63 92 90 97 76 0.73 92 52 95 93 100 93

2,4-D 0.56 78 90 100 100 100 98 0.84 95 67 100 100 100 97 1.12 95 73 100 100 100 100

77 Glufosinate + 2,4-D 0.45 + 0.56 98 (94) 82 (93) 97 (100) 97 (100) 99 (100) 98 (99) 0.45 + 0.84 97 (99) 96 (89) 99 (100) 98 (100) 100 (100) 97 (98) 0.45 + 1.12 95 (99) 93 (87) 100 (100) 100 (100) 100 (100) 100 (100) 0.59 + 0.56 100 (97) 97 (95) 98 (100) 94 (100) - 100 (100) 99 (99) 0.59 + 0.84 98 (100) 87 (93) 100 (100) 90 (100) - 100 (100) 97 (98) 0.59 + 1.12 100 (99) 99 (90) 100 (100) 96 (100) - 100 (100) 100 (100) 0.73 + 0.56 100 (97) 87 (91) 100 (100) 98 (100) 100 (100) 89 (100) - 0.73 + 0.84 100 (98) 87 (89) 100 (100) 97 (100) 100 (100) 99 (100) 0.73 + 1.12 100 (99) 97 (89) 100 (100) 97 (100) 100 (100) 100 (100)

LSD (0.05) 17 7 8 a Abbreviations: WAT, weeks after treatment; AMATA, common waterhemp; XANST, common cocklebur; AMBTR, giant ragweed. b Values in parentheses are the expected values of the two herbicides in combination, as calculated by the Colby (1967) equation. c Synergism of the herbicide combination denoted with [+] and antagonism with [-] when the difference between observed and expected control exceeded the LSD test statistic (α=0.05).

Table 3.7. Control of 15- and 30-cm monocot plants 3 weeks after treatment (WAT) with glufosinate and 2,4-D alone or in combination in greenhouse experiments.a Weed speciesbc COMCO DIGSA ECHCG Herbicide Rate 15 30 15 30 15 30

-- kg/Ha ------% Visual control 3 WAT ------

Glufosinate 0.45 6 9 46 25 5 14 0.59 15 14 75 38 13 13 0.73 22 18 78 55 19 19

2,4-D 0.56 0 11 0 0 0 0 0.84 1 22 0 0 0 0 1.12 1 21 0 0 0 0

78 Glufosinate + 2,4-D 0.45 + 0.56 68 (6) + 35 (18) + 49 (46) 27 (25) 15 (5) 15 (14) 0.45 + 0.84 83 (7) + 44 (28) + 49 (46) 27 (25) 15 (5) 23 (14) 0.45 + 1.12 82 (7) + 44 (28) + 45 (46) 32 (25) 14 (5) 15 (19) 0.59 + 0.56 70 (15) + 31 (23) 71 (75) 30 (38) 26 (13) + 22 (13) 0.59 + 0.84 70 (16) + 53 (32) + 56 (75) - 33 (38) 16 (13) 26 (13) + 0.59 + 1.12 92 (16) + 55 (31) + 53 (75) - 35 (38) 17 (13) 30 (13) + 0.73 + 0.56 92 (22) + 51 (27) + 69 (78) - 42 (55) 39 (19) + 29 (19) + 0.73 + 0.84 73 (22) + 46 (35) 62 (78) - 43 (55) 26 (19) 35 (13) + 0.73 + 1.12 86 (22) + 60 (35) + 61 (78) - 35 (55) - 38 (19) + 33 (19) +

LSD (0.05) 12 17 11 a Abbreviations: WAT, weeks after treatment; COMCO, Asiatic dayflower; DIGSA, large crabgrass; ECHCG, barnyardgrass. b Values in parentheses are the expected values of the two herbicides in combination, as calculated by the Colby (1967) equation. c Synergism of the herbicide combination denoted with [+] and antagonism with [-] when the difference between observed and expected control exceeded the LSD test statistic (α=0.05).