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Multiple herbicide resistance in waterhemp (Amaranthus tuberculatus) accessions from Wisconsin

Published online by Cambridge University Press:  10 November 2022

Felipe A. Faleco
Affiliation:
Graduate Student, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
Maxwel C. Oliveira
Affiliation:
Postdoctoral Researcher, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
Nicholas J. Arneson
Affiliation:
Outreach Program Manager, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
Mark Renz
Affiliation:
Professor, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
David E. Stoltenberg
Affiliation:
Professor, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
Rodrigo Werle*
Affiliation:
Assistant Professor, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA
*
Author for correspondence: Rodrigo Werle, Assistant Professor, Department of Agronomy, University of Wisconsin-Madison, 1575 Linden Dr., Madison, WI, 53706. Email: [email protected]
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Abstract

A comprehensive, Wisconsin state-wide assessment of waterhemp response to a diverse group of herbicide sites of action has not been conducted. Our objective was to characterize the response of a state-wide collection of waterhemp accessions to postemergence (POST) and preemergence (PRE) herbicides commonly used in corn and soybean in Wisconsin. Greenhouse experiments were conducted with more than 80 accessions from 27 counties. POST treatments included 2,4-D, atrazine, dicamba, fomesafen, glufosinate, glyphosate, imazethapyr, and mesotrione at 1× and 3× label rates. PRE treatments included atrazine, fomesafen, mesotrione, metribuzin, and S-metolachlor at 0.5×, 1×, and 3× label rates. Ninety-eight percent and 88% of the accessions exhibited ≥50% plant survival after exposure to imazethapyr and glyphosate POST 3× rate, respectively. Seventeen percent, 16%, and 3% of the accessions exhibited ≥50% plant survival after exposure to 2,4-D, atrazine, and dicamba, respectively, applied POST at the 1× rate. Survival of all accessions was ≤25% after exposure to 2,4-D or dicamba applied POST at the 3× rate, or glufosinate, fomesafen, and mesotrione applied POST at either rate evaluated. No plant of any accession survived exposure to glufosinate at either rate. Forty-five percent and 3% of the accessions exhibited <90% plant density reduction after exposure to atrazine applied PRE at the 3× rate and fomesafen PRE at the 1× rate, respectively. Plant density reduction of all accessions was ≥96% after exposure to fomesafen applied PRE at the 3× rate, or metribuzin, S-metolachlor, and mesotrione applied PRE at the 1× rate. Our results suggest that waterhemp resistance to imazethapyr and glyphosate applied POST is widespread in Wisconsin, whereas resistance to 2,4-D, atrazine, and dicamba applied POST is present to a lower extent. One accession (A75, Fond du Lac County) exhibited multiple resistance to imazethapyr, atrazine, glyphosate, and 2,4-D when applied POST. Overall, atrazine applied PRE was ineffective for waterhemp control in Wisconsin. Proactive resistance management and the use of effective PRE and POST herbicides are fundamental for waterhemp management in Wisconsin.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is a work of the US Government and is not subject to copyright protection within the United States. Published by Cambridge University Press on behalf of the Weed Science Society of America.
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© University of Wisconsin-Madison, 2022

Introduction

Waterhemp is ranked as one of the most common and most troublesome weed species in the Midwestern United States, particularly in corn and soybean fields (Tranel Reference Tranel2021; Van Wychen Reference Van Wychen2019, Reference Van Wychen2020). With great adaptability and ability to rapidly evolve herbicide resistance, waterhemp was the first weed species to evolve resistance to herbicides that inhibit protoporphyrinogen oxidase (PPO) and hydroxyphenyl pyruvate dioxygenase (HPPD; Hausman et al. Reference Hausman, Singh, Tranel, Riechers, Kaundun, Polge, Thomas and Hager2011; Shoup et al. Reference Shoup, Al-Khatib and Peterson2003). Currently, in the United States, waterhemp has evolved resistance to seven herbicide sites of action (SOAs): acetolactate synthase (ALS), auxin mimics, photosynthesis at photosystem II – serine 264 binders (PS II), enolpyruvyl shikimate phosphate synthase (EPSPS), PPO, very long-chain fatty acid synthesis (VLCFA), and HPPD (Heap Reference Heap2022; Tranel Reference Tranel2021). Moreover, a single waterhemp accession has been documented to be resistant to six SOAs (Shergill et al. Reference Shergill, Barlow, Bish and Bradley2018).

Waterhemp has become a steadily increasing concern in Wisconsin (Hammer et al. Reference Hammer, Drewitz, Conley and Stoltenberg2016; Stoltenberg Reference Stoltenberg2018). In 2018, 85% of Wisconsin counties had reported its presence, a 25% increase compared with 2009 (Renz Reference Renz2018; Zimbric et al. Reference Zimbric, Stoltenberg, Renz and Werle2018). The first report of waterhemp herbicide resistance in Wisconsin was in 1999 when a population was confirmed to be resistant to ALS inhibitors (Zimbric et al. Reference Zimbric, Stoltenberg, Renz and Werle2018). In 2013, two waterhemp accessions were confirmed to be resistant to glyphosate (Butts and Davis Reference Butts and Davis2015). In 2018, the Wisconsin Cropping Systems Weed Science Survey (Werle and Oliveira Reference Werle and Oliveira2018), with 286 respondents across 54 counties, reported waterhemp to be among the most troublesome weeds in Wisconsin cropping systems. Moreover, respondents perceived waterhemp as the weed species with the most frequent occurrence of glyphosate resistance. Currently, waterhemp in Wisconsin has been confirmed to be resistant to ALS-, EPSPS-, and PPO-inhibitor herbicides (Zimbric et al. Reference Zimbric, Stoltenberg, Renz and Werle2018). Glyphosate-resistance has been confirmed in 28 counties, and multiple resistance to glyphosate and PPO inhibitors has been confirmed in 10 counties (Hammer et al. Reference Hammer, Drewitz, Conley and Stoltenberg2016; Zimbric et al. Reference Zimbric, Stoltenberg, Renz and Werle2018).

The combination of effective postemergence (POST) and preemergence (PRE) herbicides, and multiple modes of action, as part of integrated weed management (IWM) program, is important to delay herbicide resistance evolution, preserve the usefulness of newly developed herbicide-resistant crops, and for the long-term economic success and sustainability of agricultural production (Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barret2012). In addition, the adoption of epidemiological approaches for herbicide monitoring and management, which systematically studies the extent, distribution, and determinants of a harmful organism, can greatly contribute to our efforts to understand the emergence, selection, and spread of herbicide resistance (Comont and Neve Reference Comont and Neve2021). A comprehensive, Wisconsin state-wide assessment of waterhemp response to a diverse group of herbicide SOAs has not been conducted. Therefore, our objective was to characterize the response of a Wisconsin state-wide collection of waterhemp accessions to POST and PRE herbicides commonly used in corn and soybean crops. We hypothesized that ALS, EPSPS, and PPO inhibitors would be ineffective on most accessions, whereas auxin mimics, and inhibitors of PS II, glutamine synthetase, VLCFA, and HPPD would be effective.

Materials and Methods

Waterhemp Seed Collection

In the summer of 2018, the Wisconsin Cropping Systems Weed Science Program, in partnership with key collaborators (i.e., University of Wisconsin-Madison Nutrient and Pest Management Program, University of Wisconsin-Madison Division of Extension, Wisconsin Soybean Marketing Board, and Wisconsin Corn Promotion Board), released a protocol requesting stakeholders (i.e., farmers, agronomists, industry representatives, Extension educators, etc.) to collect seed samples from 20 waterhemp female plants from Wisconsin fields with unsatisfactory waterhemp management before crop harvest. Seed samples were pooled and composed the accession for that specific geographic location. Eighty-eight waterhemp accessions from 27 counties were collected and submitted by stakeholders to the Wisconsin Cropping Systems Weed Science Program (Figure 1) along with management information of the sampled fields from 2014 to 2018 (information presented in Supplementary Table S1). Seeds from each waterhemp accession were threshed, cleaned through a seed blower separator (Oregon Seed Blower; Hoffman Manufacturing, Inc., Corvallis, OR), and coldly stratified to improve seed germination. In the cold stratification procedure, all seeds of each accession were placed in a glass container with a thin layer of water, just enough to make seeds float, and stored in a dark environment at 5 C for 2 wk (adapted from Kohlhase et al. Reference Kohlhase, Edwards and Owen2018). After this period, seeds were washed with water using a soil sieve mesh to retain the seeds, and dried on paper towels at room temperature for 24 h. Seeds were placed in plastic bags and stored at 5 C until the onset of experiments, which were conducted at the University of Wisconsin-Madison Walnut Street Greenhouses (43.076194°N, 89.423611°W), Madison, WI.

Figure 1. Geographic distribution of the 88 waterhemp accessions from 27 Wisconsin counties collected and submitted by stakeholders to the Wisconsin Cropping Systems Weed Science Program.

Waterhemp Response to POST Herbicides

The experiments were organized in a randomized complete block design with eight replications per treatment, and repeated over time (two experimental runs). Treatments were arranged as A × H × D factorial with A representing the number of accessions, H the number of herbicides, and D the number of herbicide rates (1× and 3× the recommended label rates). Eight herbicides were evaluated (Table 1). The A and H factors evaluated at the same time varied across experiments due to seed availability and to allow for the research objectives to be accomplished promptly, particularly in 2020 during the COVID-19 global pandemic. Glyphosate, imazethapyr, and atrazine were evaluated in separate experiments on 88, 85, and 81 accessions, respectively. From the 81 accessions with enough seeds remaining, 29 were evaluated in the same experiment for dicamba and 2,4-D; and 26 were evaluated in the same experiment for glufosinate, fomesafen, and mesotrione. Each experiment included a nontreated control (NTC) of each accession.

Table 1. Postemergence herbicide treatments used to evaluate the response of waterhemp accessions. a

a Abbreviations: ALS, acetolactate synthase; AM, auxin mimic; AMS ammonium sulfate; EPSPS, enolpyruvyl shikimate phosphate synthase; GS, glutamine synthetase; HPPD, hydroxyphenyl pyruvate dioxygenase; HSOC, high surfactant oil concentrate; L, liquid; SL, soluble liquid; SC, soluble concentrate; POST, postemergence; PPO, protoporphyrinogen oxidase; PS II, photosynthesis at photosystem II – serine 264 binders; SOA, site of action; WSSA, Weed Science Society of America.

b Group represents the herbicide SOA as classified by the WSSA.

c The 1× herbicide adjuvant rates were based on the respective herbicide label crop use directions for POST application in corn or soybean, and recommendations for controlling waterhemp when specified.

d A dash (-) indicates adjuvant was not included.

Waterhemp seeds were planted at 1.5-cm depth in potting mix (Promix® HP Mycorrhizae; Premier Tech Horticulture, Rivière-du-Loup, QC, Canada) contained in 23-cm-diam disposable aluminum pans. Seedlings at the true 2-leaf stage were transplanted into 656-ml pots (D40H Deepots™; Stuewe & Sons Inc., Tangent, OR) filled with potting mix. The experimental unit was one seedling per pot. POST herbicide treatments were applied when plants reached 5 to 10 cm in height using a single-nozzle research track spray chamber (DeVries Manufacturing, Hollandale, MN) equipped with AI9502EVS or DG9502EVS nozzle (TeeJet Technologies®; Spraying Systems Co., Wheaton, IL) for systemic and contact herbicides, respectively. Due to vapor drift concerns within an enclosed environment (greenhouse), the dicamba and 2,4-D herbicide treatments were applied at the University of Wisconsin-Madison Arlington Agricultural Research Station (43.3026°N, 89.3454°W). Waterhemp plants were transported to this field location on the morning of the application and returned to the greenhouse at the end of the day to allow for herbicide absorption while minimizing unintended vapor drift issues. A CO2-pressurized backpack spray boom with four TTI110015 nozzles (TeeJet Technologies®) was used for the application. A carrier volume of 140 L ha−1 was used in all applications (spray chamber and backpack). Plants were maintained in the greenhouse at 20 to 35 C with a natural ventilation system. Natural lighting was supplemented with 400-W high-pressure sodium light bulbs simulating a 16-h photoperiod. Plants were watered daily and fertigated weekly with 20-10-20 water-soluble fertilizer (Peters Professional®; ICL Fertilizers, Dublin, OH) delivering 500 ppm of nitrogen and potassium, respectively, and 250 ppm of phosphorus.

At 21 d after treatment (DAT), plant survival was assessed visually as dead (no green tissue; assessed value of 0) or alive (green tissue and evidence of regrowth; assessed value of 1; Figure 2). Accessions with ≥50% (± standard error) plant survival were classified as resistant to each herbicide × rate treatment (adapted from Schultz et al. Reference Schultz, Chatham, Riggins, Tranel and Bradley2015 and Vennapusa et al. Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018; adopted by Faleco et al. Reference Faleco, Oliveira, Arneson, Renz, Stoltenberg and Werle2022). Aboveground biomass was harvested, and force air-dried at 52 C to constant mass. The biomass data were converted into percent biomass reduction compared to the NTC using Equation 1 (adapted from Wortman Reference Wortman2014). Seed production of survivor plants was not determined.

(1) $${{Biomass}}\; {{Reduction}}\;\left( \% \right) = \left( {1 - \;{{BEU} \over {\overline {BNTC} }}} \right) \times 100$$

Figure 2. Plant survival rating used for herbicide resistance classification for waterhemp response to postemergence-applied herbicides.

where $BEU$ represents the biomass of the experimental unit and $\overline {BNTC\;} $ represents the biomass mean of the NTC for the respective accession.

Waterhemp Response to PRE Herbicides

The experiments were organized in a randomized complete block design, with four replications per treatment and repeated over time (two experimental runs). Treatments were arranged as A × H × D factorial with A representing the number of accessions, H the number of herbicides, and D the number of herbicide rates (0.5×, 1×, and 3× the recommended label rate). Five herbicides were evaluated (Table 2). The A and H factors evaluated at the same time varied across experiments as described above. Fomesafen, S-metolachlor, and mesotrione were evaluated in the same experiment on 30 accessions. Atrazine and metribuzin were evaluated in the same experiment on 29 accessions. Each experiment included an NTC of each accession.

Table 2. Preemergence herbicide treatments used to evaluate the response of waterhemp accessions. a

a Abbreviations: DF, dry flowable; EC, emulsifiable concentrate; HPPD, hydroxyphenyl pyruvate dioxygenase; L, liquid; PPO, protoporphyrinogen oxidase; PS II, photosynthesis at photosystem II – serine 264 binders; SL, soluble liquid; SC, soluble concentrate; SOA site of action; VLCFA, very long-chain fatty acid synthesis; WSSA, Weed Science Society of America.

b Group represents the herbicide SOA as classified by the WSSA.

c The 1× herbicide rate was based on the respective herbicide label crop use directions for preemergence application in corn or soybean on medium not highly erodible soils with 3.0% organic matter, and recommendations for controlling waterhemp when specified.

Experimental units consisted of approximately 190 seeds (measured by volume) planted 1.5 cm deep in 360-ml pot (8.9 cm Kord Traditional Square Pot; The HC Companies, Twinsburg, OH) filled with nonsterilized field soil (silty clay loam; 6.4 pH; 3.0% organic matter; 18% sand, 53% silt, and 30% clay by weight). The soil was watered immediately after planting and before herbicide application to facilitate seed germination. Preemergence herbicide treatments were applied using the spray chamber and carrier volume described above, equipped with a AI9502EVS nozzle (TeeJet Technologies®). Plants were watered daily and fertigated weekly with 20-10-20 water-soluble fertilizer (Peters Professional®) delivering 500 ppm of nitrogen and potassium, respectively, and 250 ppm of phosphorus. The daily watering promoted PRE herbicide activation in soil following application. Environmental conditions in the greenhouse were the same as described above for the POST experiments.

At 28 DAT, emerged plants per experimental unit were counted. The count data were converted into percent plant density reduction compared with the NTC using Equation 2 (adapted from Wortman Reference Wortman2014).

(2) $${{Plant}} \ {{Density}} \ {{Reduction}}\;\left( \% \right) = \left( {1 - \;{{{{PCEU}}} \over {\overline {{{PCNTC}}} }}} \right) \times 100$$

where $\;PCEU$ represents the plant counts of the experimental unit and $\overline {PCNTC} $ represents the plant counts mean of the NTC for the respective accession.

Herbicide × rate treatments that provided <90% (± standard error) plant density reduction were classified as ineffective for each accession (adapted from Vennapusa et al. Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018; adopted by Faleco et al. Reference Faleco, Oliveira, Arneson, Renz, Stoltenberg and Werle2022).

Assessment of Targe-Site Resistance for EPSPS- and PPO-inhibitor Herbicides

Target-site resistance for EPSPS- and PPO-inhibitor herbicides was assessed for the 26 accessions evaluated in the fomesafen POST experiment, using leaf tissue from five plants per accession. These accessions were also evaluated in the glyphosate POST experiment. The assessments were conducted by the University of Illinois Plant Clinic (Urbana, IL) using the methodology described by Chatham et al. (Reference Chatham, Bradley, Kruger, Martin, Owen, Peterson, Mithila and Tranel2015), which identifies EPSPS gene amplification for glyphosate resistance, and the methodology described by Wuerffel et al. (Reference Wuerffel, Young, Lee, Tranel, Lightfoot and Young2015), which identifies ΔG210 protoporphyrinogen oxidase mutation for PPO resistance.

Statistical Analyses

A generalized linear mixed model with Gaussian distribution was fitted to the biomass reduction data (POST experiment) and plant density reduction data (PRE experiment) using the glmmTMB package version 1.0.2.1 (Brooks et al. Reference Brooks, Kristensen, Van Bethem, Magnusson, Berg, Nielsen, Skaug, Marchler and Bolker2017). Analysis of variance type II Wald Chi-square was performed followed by Tukey’s honestly significant difference test (α = 0.05) pairwise comparisons using the emmeans package version 1.5.4 (Lenth Reference Lenth2020). To have a general assessment of the response of waterhemp accessions from Wisconsin to the POST and PRE herbicide treatments, herbicide and rate were considered as fixed effects, whereas accession and experimental run as random effects. Both response variables were logit-transformed to improve normality assumptions (Barnes et al. Reference Barnes, Knezevic, Lawrence, Irmak, Rodriguez and Jhala2020; Davies et al. Reference Davies, Hull, Moss and Neve2019, Reference Davies, Onkokesung, Brazier-Hicks, Edwards and Moss2020; Striegel et al. Reference Striegel, Eskridge, Lawrence, Knezevic, Kruger, Proctor, Hein and Jhala2020; Warton and Hui Reference Warton and Hui2011). Back transformed means are presented for ease of result interpretation. Statistical analyses were performed using R software version 4.0.3 (R Core Team 2020) and RStudio software version 1.4.1103 (RStudio Team 2021).

Results and Discussion

Waterhemp Response to POST Herbicides

Ninety-eight percent and 88% of the accessions exhibited ≥50% plant survival after exposure to imazethapyr and glyphosate POST at the 3× rate, respectively (Figure 3). Seventeen percent, 16%, and 3% of the accessions exhibited ≥50% plant survival after exposure to 2,4-D, atrazine, and dicamba POST at the 1× rate, respectively. Survival of all accessions was ≤25% after exposure to 2,4-D or dicamba POST at the 3× rate, or glufosinate, fomesafen, and mesotrione POST at either rate evaluated in this study. No plant of any accession survived exposure to glufosinate at either rate.

Figure 3. Waterhemp plant survival (± standard error) in response to postemergence-applied herbicides. Accessions with survival ≥50% (represented by the red line) were classified as resistant to each herbicide × rate treatment. Data from the 26 accessions evaluated for all herbicides applied postemergence are presented.

Among the 26 accessions evaluated for all herbicides at the 1× rate applied POST, 58% exhibited ≥50% survival after exposure to imazethapyr and glyphosate (Figure 4; herbicide treatments applied separately, not tank mixed); 12% after exposure to imazethapyr, glyphosate, and atrazine; and other 12% after exposure to imazethapyr, glyphosate, and 2,4-D. One accession (A75, Fond du Lac County) exhibited ≥50% survival after exposure to imazethapyr, atrazine, glyphosate, and 2,4-D POST at the 1× rate.

Figure 4. Geographic distribution of Wisconsin waterhemp accessions exhibiting herbicide resistance 1× rate applied postemergence. Herbicide treatments were applied separately (not tank mixed). Data from the 26 accessions evaluated for all herbicides applied postemergence are presented.

ANOVA exhibited a significant two-way interaction between herbicide and rate for biomass reduction (P <0.0001). For the POST 1× rate, biomass reduction did not differ among glufosinate, mesotrione, and fomesafen (≥97%; Figure 5), which was greater than for atrazine, 2,4-D, and dicamba (95%, 95%, 94%, respectively), followed by glyphosate (35%) and imazethapyr (27%). For the POST 3× rate, biomass reduction did not differ among glufosinate, mesotrione, fomesafen, 2,4-D, dicamba, and atrazine (≥97%), which was greater than for glyphosate (69%) and imazethapyr (33%).

Figure 5. Waterhemp biomass reduction represented by the two-way interaction between postemergence-applied herbicide and rate. Accessions were considered as a random effect. The blue boxes represent the 95% confidence intervals. Treatments with the same letters did not differ according to Tukey’s honestly significant difference test at α = 0.05.

Resistance to ALS, PS II, and EPSPS inhibitors in waterhemp has been widely reported in the United States (Evans et al. Reference Evans, Strom, Riechers, Davis, Tranel and Hager2019; Heap Reference Heap2022; Sarangi et al. Reference Sarangi, Stephens, Barker, Patterson, Gaines and Jhala2019; Singh et al. Reference Singh, Garetson, McGinty, Dotray, Morgan, Nolte and Bagavathiannan2020; Vieira et al. Reference Vieira, Samuelson, Alves, Gaines, Werle and Kruger2018). Murphy et al. (Reference Murphy, Larran, Ackley, Loux and Tranel2019) reported that atrazine and glyphosate resistance was very frequent among waterhemp accessions evaluated from Ohio, whereas lactofen resistance was less frequent. In their study, a target-site resistance mechanism was observed for lactofen and glyphosate, but not for atrazine. Vennapusa et al. (Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018) reported that atrazine applied POST was ineffective in the majority of waterhemp accessions evaluated from Nebraska, with the non-target site resistance (NTSR) mechanism via glutathione S-transferase present. Schryver et al. (Reference Schryver, Soltani, Hooker, Robinson, Tranel and Sikkema2017) confirmed imazethapyr, glyphosate, and atrazine resistance in 100%, 82%, and 76% of the accessions from Ontario, Canada. In their experiment, 61% of the accessions were resistant to all three herbicides. Moreover, several waterhemp accessions have been confirmed to be resistant to multiple SOAs, including auxin mimics (Bernards et al. Reference Bernards, Crespo, Kruger, Gaussoin and Tranel2012; Crespo et al. Reference Crespo, Wingeyer, Kruger, Riggins, Tranel and Bernards2017; Schultz et al. Reference Schultz, Chatham, Riggins, Tranel and Bradley2015), with a single waterhemp accession being resistant to six herbicide SOAs (Shergill et al. Reference Shergill, Barlow, Bish and Bradley2018).

Between 2014 and 2018, ALS inhibitors were applied at least once in 67% of the fields where the accessions with ≥50% survival after exposure to imazethapyr at the 3× rate applied POST were sampled, with predominance of flumetsulam (commercial tank mix with acetochlor and clopyralid) applied PRE in corn, and imazethapyr (commercial tank mix with glyphosate) applied POST in soybean (Supplementary Table S1). Widespread occurrence of ALS inhibitor resistance in waterhemp is a good example of how important it is to preserve herbicide SOAs. This resistance began appearing in several Midwest U.S. states in the early 1990s and became widespread within about 5 yr after rapid adoption of this SOA for waterhemp management (Heap Reference Heap2022; Tranel Reference Tranel2021). In recent years, this resistance has been the norm rather than the exception, being present in essentially every field accession of waterhemp and in naturalized riparian populations from Ohio (Tranel Reference Tranel2021; Waselkov Reference Waselkov2013). Moreover, research has demonstrated that the ALS inhibitor resistance fitness cost may vary depending on the weed species. For instance, Werle et al. (Reference Werle, Jhala, Yerka, Anita Dille and Lindquist2016, Reference Werle, Begcy, Yerka, Mower, Dweikat, Jhala and Lindquist2017) reported a lack of strong ALS inhibitor resistance fitness cost in shattercane [Sorghum bicolor (L.) Moench ssp. drummondii (Nees ex Steud.) de Wet ex Davidse] and johnsongrass [Sorghum halepense (L.) Pers.]. On the other hand, Wu et al. (Reference Wu, Davis and Tranel2018) reported ALS inhibitor resistance fitness cost in waterhemp, but not for resistance to PS II, EPSPS, PPO, and HPPD inhibitors.

In our study, elevated survival after exposure to atrazine applied POST was not very frequent (16% of the accessions exhibited ≥50% survival after exposure to atrazine at the 1× rate applied POST; Figure 3), nor was a lack of biomass reduction observed (95% biomass reduction at the 1× rate applied POST; Figure 5). Although atrazine is one of the most widely used corn herbicides in Wisconsin (USDA-NASS 2015, 2017, 2018, 2019), between 2014 and 2018, atrazine was applied at least once in only 35% of the fields from which the 81 accessions evaluated for atrazine were collected (Supplementary Table S1). In contrast, atrazine was applied at least once in 69% of the fields from which the accessions with ≥50% survival after exposure to atrazine at the 1× rate applied POST were sampled. We believe that the reduced use of atrazine in most of the sampled fields during this 5-yr period that preceded seed collection, and perhaps for a longer period, minimized selection pressure for atrazine resistance. Additionally, the Wisconsin rules and regulations for atrazine use are more restrictive than the Federal standards, such as establishing maximum application rates given soil texture and use pattern, and established atrazine prohibition areas (WI-DATCP 2021, ATCP 30.31). All the accessions with ≥50% survival after exposure to atrazine at the 1× rate applied POST were sampled from fields outside the established atrazine prohibition areas (Figure 4).

On the other hand, the selection pressure associated with the over-use of glyphosate may help to explain our findings that 88% of the accessions exhibited ≥50% survival after exposure to glyphosate at the 3× rate applied POST. Between 2014 and 2018, glyphosate was applied at least once in 90% of the fields from which these accessions were sampled (Supplementary Table S1). Glyphosate resistance is a good example of the critical need to reduce over-reliance on single approaches to weed management. The first case of glyphosate resistance in weeds was reported in 1996 as a rigid ryegrass (Lolium rigidum) accession evolved resistance after 15 yr of multiple glyphosate treatments (Pratley et al. Reference Pratley, Baines, Eberbach Pl and Broster1996, Reference Pratley, Urwin, Stanton, Baines, Broster, Cullis, Schafer, Bohn and Krueger1999). Around the same time, Powles et al. (Reference Powles, Lorraine-Colwill, Dellow and Preston1998) reported glyphosate resistance in a different rigid ryegrass accession collected from an orchard where glyphosate had been used two or three times a year for 15 yr to control weeds within rows of trees. Both authors strongly emphasized the importance of integrated weed management and careful use of selective herbicides to preserve the efficacy of glyphosate. Rosenbaum and Bradley (Reference Rosenbaum and Bradley2013) reported that glyphosate-resistant waterhemp were more likely to occur in fields with no other weed species present at the end of the season, continuous cropping of soybean, exclusive use of glyphosate for several consecutive seasons, and waterhemp plants showing obvious signs of surviving herbicide treatment compared to fields characterized with glyphosate-susceptible waterhemp. They suggested that these four site parameters, and certain combinations of them, serve as predictors of glyphosate resistance in future waterhemp populations.

The A20 and A75 accessions (≥50% survival after exposure 1× 2,4-D applied POST), and the A31 accession (≥50% survival after exposure 1× dicamba applied POST) were not exposed to any auxin mimic between 2014 to 2018 (Supplementary Table S1). These results may be a possible indicative for NTSR metabolic resistance, which means plants can evolve resistance to herbicides that had never been sprayed in the field (Rigon et al. Reference Rigon, Gaines, Kupper and Dayan2020; Shyam et al. Reference Shyam, Borgato, Peterson, Dille and Jugulam2021, Yu and Powles Reference Yu and Powles2014).

Waterhemp Response to PRE Herbicides

Forty-five percent and 3% of the accessions exhibited <90% plant density reduction after exposure to atrazine applied PRE at the 3× rate and fomesafen applied PRE at the 1× rate, respectively (Figure 6). Three percent of the accessions exhibited <90% plant density reduction after exposure to S-metolachlor or mesotrione applied PRE at the 0.5× rate. Plant density reduction of all accessions was ≥96% after exposure to fomesafen applied PRE at the 3× rate, or to metribuzin, S-metolachlor mesotrione applied PRE at the 1× rate.

Figure 6. Waterhemp plant density reduction (± standard error) in response to preemergence-applied herbicides. Treatments with plant density reduction <90% (represented by the red line) were classified as ineffective. Data from the 29 accessions evaluated for all herbicides applied preemergence are presented.

ANOVA exhibited a significant two-way interaction between herbicide and rate for plant density reduction (P <0.0001). At the 0.5× rate, plant density reduction did not differ for S-metolachlor, metribuzin, and mesotrione (≥97%; Figure 7), which was greater than that for fomesafen (96%), and atrazine (77%). At the 1× and 3× rates, plant density reduction for S-metolachlor, metribuzin, mesotrione, and fomesafen (≥97%) was greater than that for atrazine (≤93%).

Figure 7. Waterhemp plant density reduction represented by the two-way interaction between preemergence-applied herbicide and rate. Accessions were considered as a random effect. The blue boxes represent the 95% confidence intervals. Treatments with the same letters did not differ according to Tukey’s honestly significant difference test at α = 0.05.

Preemergence herbicides have a very important role to play in integrated weed management. However, biotic and abiotic factors such as interactions among weather, soil, microorganisms, and herbicide, might affect the performance of PRE herbicides (Dao and Lavy Reference Dao and Lavy1978; Fang et al. Reference Fang, Lian, Wang, Cai and Yu2015; Houot et al. Reference Houot, Topp, Yassir and Soulas2000; Jing et al. Reference Jing, Lan, Wen, Jing, Hao and Jun2020; Takeshita et al. Reference Takeshita, Mendes, Alonso and Tornisielo2019). For example, Vennapusa et al. (Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018) reported more effective waterhemp control with atrazine applied PRE rather than POST, although it was still unsatisfactory in both cases. In contrast, our study found greater atrazine performance when it was applied POST rather than PRE. Comparing the soil characteristics from the study by Vennapusa et al. Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018 (loam, 6.4 pH, 1.7% organic matter) vs. the characteristics of soil in our study (silty clay loam, 6.4 pH, 3.0% organic matter; 18% sand, 53% silt, and 30% clay by weight), our soil contained a greater amount of organic matter and clay. Higher amounts of organic matter and/or clay is generally associated with increased adsorption of S-triazines (Talbert and Fletchall Reference Talbert and Fletchall1965), and therefore, we believe this condition might help to elucidate our results.

The use of reduced PRE herbicide rates as an attempt to reduce costs, herbicide carryover, and/or environmental impacts may increase the selection pressure and lead to rapid herbicide resistance evolution (Belz Reference Belz2020; Manalil et al. Reference Manalil, Busi, Renton and Powles2011; Maxwell and Mortimer Reference Maxwell, Mortimer, Powles and Holtum1994; Norsworthy Reference Norsworthy2012; Tehranchian et al. Reference Tehranchian, Norsworthy, Powles, Bararpour, Bagavathiannan, Barber and Scott2017; Vieira et al. Reference Vieira, Luck, Amundsen, Werle, Gaines and Kruger2020). Our results suggest that herbicides applied PRE at the 0.5× label rate might provide reduced waterhemp control. Consequently, the reliance on herbicides applied POST may increase and, in the end, the short-term economic benefits associated with using reduced herbicide rates are quickly outweighed by the future costs related to herbicide resistance evolution and spread (Gressel Reference Gressel, De Prado, Jorrín and García-Torres1997).

Assessment of Targe-Site Resistance for EPSPS- and PPO-inhibitor Herbicides

Fifty percent of the 26 accessions evaluated exhibited both EPSPS gene amplification and ΔG210 protoporphyrinogen oxidase mutation, 35% exhibited only the EPSPS gene amplification, 4% exhibited the ΔG210 protoporphyrinogen oxidase mutation only, and 11% did not exhibit these target-site alterations (data not shown).

Comparing the target-site assessment results to the glyphosate POST experiment, all accessions containing the EPSPS gene amplification also exhibited ≥50% plant survival after exposure to glyphosate applied POST at the 1× rate, supporting our resistance classification methodology. Three accessions (A15, A57, and A76) exhibited ≥50% plant survival after exposure to glyphosate applied POST at the 1× rate but did not exhibit the EPSPS gene amplification. This evidence warrants further investigation of other glyphosate resistance mechanisms, such as amino acid substitution (P106S) and reduced glyphosate translocation (Bell et al. Reference Bell, Hager and Tranel2013; Nandula et al. Reference Nandula, Ray, Ribeiro, Pan and Reddy2013).

Comparing the target-site assessment results to the fomesafen POST experiment, 54% of the 26 accessions evaluated exhibited the ΔG210 protoporphyrinogen oxidase mutation, whereas no accession exhibited ≥50% plant survival after exposure to fomesafen applied POST at the 1× rate. We believe that these accessions might have a low-level resistance to PPO inhibitors that we were not able to detect in the POST experiment. Oliveira et al. (Reference Oliveira, Giacomini, Arsenijevic, Vieira, Tranel and Werle2021) also observed high mortality of Palmer amaranth (Amaranthus palmeri S. Watson) in greenhouse conditions, even with most of the accessions containing the ΔG210 protoporphyrinogen oxidase mutation. They suggested several factors that may help to understand this phenomenon, such as having 1× as the lowest herbicide rate, ideal greenhouse conditions for herbicide application and performance compared to the field, or the opposite, with limited root growth due to pot size affecting plant ability to overcome herbicide effects. This warrants further investigation.

Best management practices, as proposed by Norsworthy et al. (Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barret2012), are of paramount importance for long-term sustainability of weed management, particularly in cases of NTSR. Avoiding new introductions of waterhemp, preventing established infestations from reproducing, and preventing seed movement are important; equipment cleaning and weed-free crop seeds may help in this context. Enhancing crop competitiveness, routinely scouting fields, diversifying and mixing herbicide SOAs as often as possible, and respecting the labeled herbicide rates and recommended weed sizes are necessary. Continued community efforts, education, training, economic incentives, and policies are of critical importance to move farmers to more sustainable weed management systems (Liu et al. Reference Liu, Neve, Glasgow, Wuerffel, Owen and Kaundun2020; Moss Reference Moss2019; Peterson et al. Reference Peterson, Collavo, Ovejero, Shivrain and Walsh2018). Research, development, and successful implementation of innovative weed management tools such as biopesticides, computer vision, decision tools, robotics, and machine learning may also play important roles in near future and mitigate the reliance on herbicides (Arakeri et al. Reference Arakeri, Kumar, Barsaiya and Sairam2017; Coleman et al. Reference Coleman, Stead, Rigter, Xu, Johnson, Brooker, Sukkarieh and Walsh2019; Fennimore and Cutulle Reference Fennimore and Cutulle2019; McCool et al. Reference McCool, Beattie, Firn, Lehnert, Kulk, Bawden, Russel and Perez2018; Panpatte and Ganeshkumar Reference Panpatte and Ganeshkumar2021; Westwood et al. Reference Westwood, Charudattan, Duke, Fennimore, Marrone, Slaughter, Swanton and Zollinger2018).

In conclusion, our results suggest that ≥88% of the accessions evaluated are resistant (≥50% survival) to both imazethapyr and glyphosate applied POST. Seventeen percent, 16%, and 3% of the accessions are resistant to 2,4-D, atrazine, and dicamba applied POST, respectively. All accessions were susceptible (<50% survival) to glufosinate, fomesafen, and mesotrione applied POST. The A75 accession (Fond du Lac County, WI) exhibited multiple resistance to imazethapyr, glyphosate, atrazine, and 2,4-D applied POST. Moreover, atrazine and fomesafen applied PRE were ineffective (<90% plant density reduction) for 45% and 3%, respectively, of the accessions evaluated. Metribuzin, S-metolachlor, and mesotrione applied PRE effectively controlled (≥90% plant density reduction) each accession at 1× and 3× rates. Herbicides applied PRE at the 0.5× rate provided reduced waterhemp control and might increase the reliance on herbicides applied POST. Proactive resistance management and the use of effective PRE and POST herbicides as part of an integrated weed management program, are fundamental for waterhemp management in Wisconsin.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/wet.2022.81

Acknowledgments

We thank the Wisconsin Soybean Marketing Board for funding Felipe Faleco’s graduate research assistantship, the stakeholders for collecting and sending seed samples, students and staff in the University of Wisconsin-Madison Cropping Systems Weed Science Program for their technical assistance with the greenhouse experiments, and Diane Elizabeth Plewa and the University of Illinois Plant Clinic for conducting the molecular analyses. No conflicts of interest have been declared.

Footnotes

Associate Editor: William Johnson, Purdue University

References

Arakeri, MP, Kumar, BPV, Barsaiya, S, Sairam, HV (2017) Computer vision based robotic weed control system for precision agriculture. Pages 1201–1205 in International conference on advances in computing, communications and informatics (ICACCI), Udupi, India, September 13–16, 2017CrossRefGoogle Scholar
Barnes, ER, Knezevic, SZ, Lawrence, NC, Irmak, S, Rodriguez, O, Jhala, AJ (2020) Control of velvetleaf (Abutilon theophrasti) at two heights with POST herbicides in Nebraska popcorn. Weed Technol 34:560567 CrossRefGoogle Scholar
Bell, MS, Hager, AG, Tranel, PJ (2013) Multiple resistance to herbicides from four site-of-action groups in waterhemp (Amaranthus tuberculatus). Weed Sci 61:460468 CrossRefGoogle Scholar
Belz, RG (2020) Low herbicide doses can change the responses of weeds to subsequent treatments in the next generation: metamitron exposed PSII-target-site resistant Chenopodium album as a case study. Pest Manag Sci 76:30563065 CrossRefGoogle ScholarPubMed
Bernards, ML, Crespo, RJ, Kruger, GR, Gaussoin, R, Tranel, PJ (2012) A waterhemp (Amaranthus tuberculatus) population resistant to 2,4-D. Weed Sci 60:379384 CrossRefGoogle Scholar
Brooks, ME, Kristensen, K, Van Bethem, KJ, Magnusson, A, Berg, CW, Nielsen, A, Skaug, HJ, Marchler, M, Bolker, BM (2017) glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J 9:378400 CrossRefGoogle Scholar
Butts, T, Davis, VM (2015) Glyphosate resistance confirmed in two Wisconsin common waterhemp (Amaranthus rudis) populations. University of Wisconsin-Madison Crop Weed Science Blog. https://wcws.cals.wisc.edu/documents/. Accessed: March 28, 2021Google Scholar
Coleman, GRY, Stead, A, Rigter, MP, Xu, Z, Johnson, D, Brooker, GM, Sukkarieh, S, Walsh, MJ (2019) Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control. Weed Technol 33:633650 CrossRefGoogle Scholar
Chatham, LA, Bradley, KW, Kruger, GR, Martin, JR, Owen, MD, Peterson, DE, Mithila, J, Tranel, PJ (2015) A Multistate Study of the Association Between Glyphosate Resistance and EPSPS Gene Amplification in Waterhemp (Amaranthus tuberculatus). Weed Sci 63:569577 CrossRefGoogle Scholar
Comont, D, Neve, P (2021) Adopting epidemiological approaches for herbicide resistance monitoring and management. Weed Res 61:8187 CrossRefGoogle Scholar
Crespo, RJ, Wingeyer, AB, Kruger, GR, Riggins, CW, Tranel, PJ, Bernards, ML (2017) Multiple-herbicide resistance in a 2,4-D–resistant waterhemp (Amaranthus tuberculatus) population from Nebraska. Weed Sci 65:743754 CrossRefGoogle Scholar
Dao, TH, Lavy, TL (1978) Atrazine adsorption on soil as influenced by temperature, moisture content and electrolyte concentration. Weed Sci 26:303308 CrossRefGoogle Scholar
Davies, LR, Hull, R, Moss, S, Neve, P (2019) The first cases of evolving glyphosate resistance in UK poverty brome (Bromus sterilis) populations. Weed Sci 67:4147 CrossRefGoogle Scholar
Davies, LR, Onkokesung, N, Brazier-Hicks, M, Edwards, R, Moss, S (2020) Detection and characterization of resistance to acetolactate synthase inhibiting herbicides in Anisantha and Bromus species in the United Kingdom. Pest Manag Sci 76:24732482 CrossRefGoogle ScholarPubMed
Evans, CM, Strom, SA, Riechers, DE, Davis, AS, Tranel, PJ, Hager, AG (2019) Characterization of a waterhemp (Amaranthus tuberculatus) population from Illinois resistant to herbicides from five site-of-action groups. Weed Technol 33:400410 CrossRefGoogle Scholar
Faleco, FA, Oliveira, MC, Arneson, NJ, Renz, M, Stoltenberg, DE, Werle, R (2022) Multiple resistance to imazethapyr, atrazine, and glyphosate in a recently introduced Palmer amaranth (Amaranthus palmeri) accession in Wisconsin. Weed Technol 36: 344351 CrossRefGoogle Scholar
Fang, H, Lian, J, Wang, H, Cai, L, Yu, Y (2015) Exploring bacterial community structure and function associated with atrazine biodegradation in repeatedly treated soils. J Hazard Mater 286:457465 CrossRefGoogle ScholarPubMed
Fennimore, SA, Cutulle, M (2019) Robotic weeders can improve weed control options for specialty crops. Pest Manag Sci 75:17671774 CrossRefGoogle ScholarPubMed
Gressel, J (1997) Burgeoning resistance requires new strategies. Pages 314 in De Prado, R, Jorrín, J, García-Torres, L, eds. Weed and Crop Resistance to Herbicides. Dordrecht: Springer CrossRefGoogle Scholar
Hammer, D, Drewitz, N, Conley, S, Stoltenberg, D (2016) Common waterhemp (Amaranthus rudis): confirmed herbicide resistance and spread across wisconsin. University of Wisconsin-Madison Integrated Pest and Crop Management Blog. https://ipcm.wisc.edu/blog/2016/10/common-waterhemp-amaranthus-rudis-confirmed-herbicide-resistance-and-spread-across-wisconsin/. Accessed: March 2, 2021Google Scholar
Hausman, NE, Singh, S, Tranel, PJ, Riechers, DE, Kaundun, SS, Polge, ND, Thomas, DA, Hager, AG (2011) Resistance to HPPD-inhibiting herbicides in a population of waterhemp (Amaranthus tuberculatus) from Illinois, United States. Pest Manag Sci 67:258261 CrossRefGoogle Scholar
Heap, I (2022) The International Herbicide-Resistant Weed Database. www.weedscience.org. Accessed: July 20, 2022Google Scholar
Houot, S, Topp, E, Yassir, A, Soulas, G (2000) Dependence of accelerated degradation of atrazine on soil pH in French and Canadian soils. Soil Biol Biochem 32:615625 CrossRefGoogle Scholar
Jing, S, Lan, MX, Wen, W, Jing, Z, Hao, Z, Jun, WY (2020) Adsorption characteristics of atrazine on different soils in the presence of Cd(II). Adsorpt Sci Technol 38:225239 CrossRefGoogle Scholar
Kohlhase, DR, Edwards, JW, Owen, MD (2018) Inheritance of 4-hydroxyphenylpyruvate dioxygenase inhibitor herbicide resistance in an Amaranthus tuberculatus population from Iowa, USA. Plant Sci 274:360368 CrossRefGoogle Scholar
Lenth, R (2020) emmeans: estimated marginal means, aka least-square means. R package version 1.5.4 https://CRAN.R-project.org/package=emmeans. Accessed: May 15, 2022Google Scholar
Liu, C, Neve, P, Glasgow, L, Wuerffel, RJ, Owen, MD, Kaundun, SS (2020) Modeling the sustainability and economics of stacked herbicide-tolerant traits and early weed management strategy for waterhemp (Amaranthus tuberculatus) control. Weed Sci 68:179185 CrossRefGoogle Scholar
Manalil, S, Busi, R, Renton, M, Powles, SB (2011) Rapid evolution of herbicide resistance by low herbicide dosages. Weed Sci 59:210217 CrossRefGoogle Scholar
Maxwell, BD, Mortimer, AM (1994) Selection for herbicide resistance. Pages 125 in Powles, SB, Holtum, JA, eds. Herbicide Resistance in Plants: Biology and Biochemistry (2nd ed.). Boca Raton, FL: CRC Press Google Scholar
McCool, C, Beattie, J, Firn, J, Lehnert, C, Kulk, J, Bawden, O, Russel, R, Perez, T (2018) Efficacy of mechanical weeding tools: a study into alternative weed management strategies enabled by robotics. IEEE Robot Autom Lett 3:11841190 Google Scholar
Moss, S (2019) Integrated weed management (IWM): why are farmers reluctant to adopt non-chemical alternatives to herbicides? Pest Manag Sci 75:12051211 CrossRefGoogle ScholarPubMed
Murphy, BP, Larran, AS, Ackley, B, Loux, MM, Tranel, PJ (2019) Survey of glyphosate-, atrazine- and lactofen-resistance mechanisms in Ohio waterhemp (Amaranthus tuberculatus) populations. Weed Sci 67:296302 CrossRefGoogle Scholar
Nandula, VK, Ray, JD, Ribeiro, DN, Pan, Z, Reddy, KN (2013) Glyphosate resistance in tall waterhemp (Amaranthus tuberculatus) from Mississippi is due to both altered target-site and nontarget-site mechanisms. Weed Sci 61:374383 CrossRefGoogle Scholar
Norsworthy, JK (2012) Repeated sublethal rates of glyphosate lead to decreased sensitivity in Palmer amaranth. Crop Manag 11:16 CrossRefGoogle Scholar
Norsworthy, JK, Ward, SM, Shaw, DR, Llewellyn, RS, Nichols, RL, Webster, TM, Bradley, KW, Frisvold, G, Powles, SB, Burgos, NR, Witt, WW, Barret, M (2012) Reducing the risks of herbicide resistance: best management practices and recommendations. Weed Sci 60(SPI):3162 CrossRefGoogle Scholar
Oliveira, M, Giacomini, D, Arsenijevic, N, Vieira, G, Tranel, P, Werle, R (2021) Distribution and validation of genotypic and phenotypic glyphosate and PPO-inhibitor resistance in Palmer amaranth (Amaranthus palmeri) from southwestern Nebraska. Weed Technol 35:6576 CrossRefGoogle Scholar
Panpatte, S, Ganeshkumar, C (2021) Artificial intelligence in agriculture sector: case study of blue river technology. Pages 147153 in Proceedings of The Second International Conference on Information Management and Machine Intelligence. Lecture Notes in Networks and Systems. Vol. 166. Singapore: Springer CrossRefGoogle Scholar
Peterson, MA, Collavo, A, Ovejero, R, Shivrain, V, Walsh, MJ (2018) The challenge of herbicide resistance around the world: a current summary. Pest Manag Sci 74:22462259 CrossRefGoogle ScholarPubMed
Powles, S, Lorraine-Colwill, DF, Dellow, JJ, Preston, C (1998) Evolved resistance to glyphosate in rigid ryegrass (Lolium rigidum) in Australia. Weed Sci 46:604607 CrossRefGoogle Scholar
Pratley, JE, Baines, P, Eberbach Pl, Incerti M, Broster, JC (1996) Glyphosate resistance in annual ryegrass. Page 122 in Proceedings of 11th Annual Conference of The Grassland Society of New South Wales. Wagga Wagga, NSW, Australia, July 10–11, 1996Google Scholar
Pratley, J, Urwin, N, Stanton, R, Baines, P, Broster, J, Cullis, K, Schafer, D, Bohn, J, Krueger, R (1999) Resistance to glyphosate in Lolium rigidum I Bioevaluation. Weed Sci 47:405411 CrossRefGoogle Scholar
R Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Accessed: May 15, 2022Google Scholar
Renz, M (2018) Update on waterhemp and Palmer amaranth in Wisconsin. UW-Madison Integrated Pest and Crop Management Blog. https://ipcm.wisc.edu/blog/2018/08/update-on-waterhemp-and-palmer-amaranth-in-wisconsin/. Accessed: March 2, 2021Google Scholar
Rigon, CA, Gaines, TA, Kupper, A, Dayan, FE (2020) Metabolism-based herbicide resistance, the major threat among the non-target site resistance mechanisms. Outlooks Pest Manage 31:164168 CrossRefGoogle Scholar
Rosenbaum, KK, Bradley, KW (2013) A survey of glyphosate-resistant waterhemp (Amaranthus rudis) in Missouri soybean fields and prediction of glyphosate resistance in future waterhemp populations based on in-field observations and management practices. Weed Technol 27:656663 CrossRefGoogle Scholar
RStudio Team (2021) RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/. Accessed: May 15, 2022Google Scholar
Sarangi, D, Stephens, T, Barker, AL, Patterson, EL, Gaines, TA, Jhala, AJ (2019) Protoporphyrinogen oxidase (PPO) inhibitor–resistant waterhemp (Amaranthus tuberculatus) from Nebraska is multiple herbicide resistant: confirmation, mechanism of resistance, and management. Weed Sci 67:510520 CrossRefGoogle Scholar
Schryver, MG, Soltani, N, Hooker, DC, Robinson, DE, Tranel, PJ, Sikkema, PH (2017) Glyphosate-resistant waterhemp (Amaranthus tuberculatus var. rudis) in Ontario, Canada. Can J Plant Sci 97:10571067 Google Scholar
Schultz, JL, Chatham, LA, Riggins, CW, Tranel, PJ, Bradley, KW (2015) Distribution of herbicide resistances and molecular mechanisms conferring resistance in Missouri waterhemp (Amaranthus rudis sauer) populations. Weed Sci 63:336345 CrossRefGoogle Scholar
Shergill, LS, Barlow, BR, Bish, MD, Bradley, KW (2018) Investigations of 2,4-d and multiple herbicide resistance in a Missouri waterhemp (Amaranthus tuberculatus) population. Weed Sci 66:386394 CrossRefGoogle Scholar
Shoup, DE, Al-Khatib, K, Peterson, DE (2003) Common waterhemp (Amaranthus rudis) resistance to protoporphyrinogen oxidase-inhibiting herbicides. Weed Sci 51:145150 CrossRefGoogle Scholar
Shyam, C, Borgato, E, Peterson, D, Dille, JA, Jugulam, M (2021) Predominance of metabolic resistance in a six-way-resistant Palmer Amaranth (Amaranthus palmeri) population. Front Plant Sci 11:614618 CrossRefGoogle Scholar
Singh, V, Garetson, R, McGinty, J, Dotray, P, Morgan, G, Nolte, S, Bagavathiannan, M (2020) Distribution of herbicide-resistant waterhemp (Amaranthus tuberculatus) across row crop production systems in Texas. Weed Technol 34:129139 CrossRefGoogle Scholar
Stoltenberg, DE (2018) Current state of herbicide resistance in Wisconsin. Proceedings of the 2018 Wisconsin Agribusiness Classic. Madison, Wisconsin, January 9–11, 2018Google Scholar
Striegel, A, Eskridge, KM, Lawrence, NC, Knezevic, SZ, Kruger, GR, Proctor, CA, Hein, GL, Jhala, AJ (2020) Economics of herbicide programs for weed control in conventional, glufosinate-, and dicamba/glyphosate-resistant soybean across Nebraska. Agron J 112:51585179 CrossRefGoogle Scholar
Talbert, RE, Fletchall, OH (1965) The adsorption of some s-triazines in soils. Weeds 13:4652 CrossRefGoogle Scholar
Takeshita, V, Mendes, KF, Alonso, FG, Tornisielo, VL (2019 ) Effect of organic matter on the behavior and control effectiveness of herbicides in soil. Planta Daninha v37:e019214401 CrossRefGoogle Scholar
Tehranchian, P, Norsworthy, JK, Powles, S, Bararpour, MT, Bagavathiannan, MV, Barber, T, Scott, RC (2017) Recurrent sublethal-dose selection for reduced susceptibility of Palmer amaranth (Amaranthus palmeri) to dicamba. Weed Sci 65:206212 CrossRefGoogle Scholar
Tranel, PJ (2021) Herbicide resistance in Amaranthus tuberculatus . Pest Manag Sci 77:4354 CrossRefGoogle ScholarPubMed
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2015) Agricultural Chemical Use Program 2014 Corn and Potatoes Survey. Washington, DC: U.S. Department of Agriculture. https://www.nass.usda.gov/Data_and_Statistics/Pre-Defined_Queries/2014_Corn_and_Potatoes/. Accessed: March 5, 2021Google Scholar
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2017) Agricultural Chemical Use Program 2016 Corn and Potatoes Survey. Washington, DC: U.S. Department of Agriculture. https://www.nass.usda.gov/Data_and_Statistics/Pre-Defined_Queries/2016_Corn_and_Potatoes/index.php. Accessed: March 5, 2021Google Scholar
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2018) Agricultural Chemical Use Program 2017 Corn, Soybean, and Wheat Survey. Washington, DC: U.S. Department of Agriculture. https://www.nass.usda.gov/Data_and_Statistics/Pre-Defined_Queries/2017_Cotton_Soybeans_Wheat/index.php. Accessed: March 5, 2021Google Scholar
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2019) Agricultural Chemical Use Program 2018 Corn, Peanuts, and Soybeans Survey. Washington, DC: U.S. Department of Agriculture. https://www.nass.usda.gov/Data_and_Statistics/Pre-Defined_Queries/2018_Peanuts_Soybeans_Corn/. Accessed: March 5, 2021Google Scholar
Van Wychen, L (2019) Survey of the most common and troublesome weeds in broadleaf crops, fruits and vegetables in the United States and Canada. Weed Science Society of America National Weed Survey Dataset. https://wssa.net/wp-content/uploads/2019-Weed-Survey_broadleaf-crops.xlsx. Accessed: May 10, 2021Google Scholar
Van Wychen, L (2020) Survey of the most common and troublesome weeds in grass crops, pasture, and turf in the United States and Canada. Weed Science Society of America National Weed Survey Dataset. https://wssa.net/wp-content/uploads/2020-Weed-Survey_grass-crops.xlsx. Accessed: May 10, 2021Google Scholar
Vennapusa, AR, Faleco, F, Vieira, B, Samuelson, S, Kruger, GR, Werle, R, Jugulam, M (2018) Prevalence and mechanism of atrazine resistance in waterhemp (Amaranthus tuberculatus) from Nebraska. Weed Sci 66:595602 CrossRefGoogle Scholar
Vieira, BC, Luck, JD, Amundsen, KL, Werle, R, Gaines, TA, Kruger, GR (2020) Herbicide drift exposure leads to reduced herbicide sensitivity in Amaranthus spp. Sci Rep 10:2146 CrossRefGoogle ScholarPubMed
Vieira, BC, Samuelson, SL, Alves, GS, Gaines, TA, Werle, R, Kruger, GR (2018) Distribution of glyphosate-resistant Amaranthus spp. in Nebraska. Pest Manag Sci 74:23162324 CrossRefGoogle ScholarPubMed
Warton, DI, Hui, FK (2011) The arcsine is asinine: the analysis of proportions in ecology. Ecology 92:310 CrossRefGoogle ScholarPubMed
Waselkov, K (2013) Population genetics and phylogenetic context of weed evolution in the genus amaranthus: amaranthaceae. Thesis Dissertation, ETDs 1162. St. Louis, MO: Washington UniversityGoogle Scholar
Werle, R, Begcy, K, Yerka, MK, Mower, JP, Dweikat, I, Jhala, AJ, Lindquist, JL (2017) Independent evolution of acetolactate synthase–inhibiting herbicide resistance in weedy sorghum populations across common geographic regions. Weed Sci 65:164176.CrossRefGoogle Scholar
Werle, R, Jhala, AJ, Yerka, MK, Anita Dille, J, Lindquist, JL (2016) Distribution of herbicide-resistant shattercane and johnsongrass populations in sorghum production areas of Nebraska and northern Kansas. Agron J 108: 321328.CrossRefGoogle Scholar
Werle, R, Oliveira, M (2018) 2018 Wisconsin cropping systems weed science survey – where are we at? University of Wisconsin-Madison Weed Science Blog. https://www.wiscweeds.info/post/2018-wisconsin-cropping-systems-weed-science-survey/. Accessed: May 13, 2021Google Scholar
Westwood, JH, Charudattan, R, Duke, SO, Fennimore, SA, Marrone, P, Slaughter, DC, Swanton, C, Zollinger, R (2018) Weed management in 2050: perspectives on the future of weed science. Weed Sci 66:275285 CrossRefGoogle Scholar
[WI-DATCP] State of Wisconsin Department of Agriculture, Trade and Consumer Protection. ATCP 30.31 General restrictions and requirements for use of atrazine. Published under s. 35.93, Wis. Stats., by the Legislative Reference Bureau. https://docs.legis.wisconsin.gov/code/admin_code/atcp/020/30.pdf#page=7. Accessed: March 6, 2021 Google Scholar
Wortman, SE (2014). Integrating weed and vegetable crop management with multifunctional air-propelled abrasive grits. Weed Technol 28:243252 CrossRefGoogle Scholar
Wu, C, Davis, AS, Tranel, PJ (2018) Limited fitness costs of herbicide-resistance traits in Amaranthus tuberculatus facilitate resistance evolution. Pest Manag Sci 74:293301 CrossRefGoogle ScholarPubMed
Wuerffel, RJ, Young, JM, Lee, RM., Tranel, PJ, Lightfoot, DA, Young, BG (2015) Distribution of the ΔG210 protoporphyrinogen oxidase mutation in Illinois waterhemp (Amaranthus tuberculatus) and an improved molecular method for detection. Weed Sci 63:839845 CrossRefGoogle Scholar
Yu, Q, Powles, S (2014) Metabolism-based herbicide resistance and cross-resistance in crop weeds: A threat to herbicide sustainability and global crop production. Plant Physiol 166:11061118 CrossRefGoogle Scholar
Zimbric, JW, Stoltenberg, DE, Renz, M, Werle, R (2018) Herbicide resistance in Wisconsin: An overview. Pages 64–65 in Proceedings of the 73rd Annual Meeting of the North Central Weed Science Society. Philadelphia, PA, January 9–11, 2018Google Scholar
Figure 0

Figure 1. Geographic distribution of the 88 waterhemp accessions from 27 Wisconsin counties collected and submitted by stakeholders to the Wisconsin Cropping Systems Weed Science Program.

Figure 1

Table 1. Postemergence herbicide treatments used to evaluate the response of waterhemp accessions.a

Figure 2

Figure 2. Plant survival rating used for herbicide resistance classification for waterhemp response to postemergence-applied herbicides.

Figure 3

Table 2. Preemergence herbicide treatments used to evaluate the response of waterhemp accessions.a

Figure 4

Figure 3. Waterhemp plant survival (± standard error) in response to postemergence-applied herbicides. Accessions with survival ≥50% (represented by the red line) were classified as resistant to each herbicide × rate treatment. Data from the 26 accessions evaluated for all herbicides applied postemergence are presented.

Figure 5

Figure 4. Geographic distribution of Wisconsin waterhemp accessions exhibiting herbicide resistance 1× rate applied postemergence. Herbicide treatments were applied separately (not tank mixed). Data from the 26 accessions evaluated for all herbicides applied postemergence are presented.

Figure 6

Figure 5. Waterhemp biomass reduction represented by the two-way interaction between postemergence-applied herbicide and rate. Accessions were considered as a random effect. The blue boxes represent the 95% confidence intervals. Treatments with the same letters did not differ according to Tukey’s honestly significant difference test at α = 0.05.

Figure 7

Figure 6. Waterhemp plant density reduction (± standard error) in response to preemergence-applied herbicides. Treatments with plant density reduction <90% (represented by the red line) were classified as ineffective. Data from the 29 accessions evaluated for all herbicides applied preemergence are presented.

Figure 8

Figure 7. Waterhemp plant density reduction represented by the two-way interaction between preemergence-applied herbicide and rate. Accessions were considered as a random effect. The blue boxes represent the 95% confidence intervals. Treatments with the same letters did not differ according to Tukey’s honestly significant difference test at α = 0.05.

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