Introduction
Waterhemp is one of the most troublesome summer annual broadleaf weed species in the pigweed family infesting agronomic crops across the midwestern United States (Hager et al. Reference Hager, Wax, Stoller and Bollero2002; Steckel and Sprague Reference Steckel and Sprague2004a). It is native to the central United States with a distribution ranging from Texas to Canada (Rosenbaum and Bradley Reference Rosenbaum and Bradley2013; Nordby et al. Reference Nordby, Hartzler and Bradley2007). It is a dioecious (i.e., male and female flowers on separate plants) and C4 plant with several unique characteristics, including an extended emergence window (May through September), rapid growth rate, and prolific seed production (Duff et al. Reference Duff, Al-Khatib and Peterson2009; Hartzler et al. Reference Hartzler, Buhler and Stoltenberg1999; Steckel et al. Reference Steckel, Sprague, Hager, Simmons and Bollero2003). Waterhemp is a highly competitive weed and can cause significant crop grain yield losses. For instance, Hager et al. (Reference Hager, Wax, Stoller and Bollero2002) reported up to 43% grain yield losses of soybean [Glycine max (L.) Merr] when waterhemp plants were allowed to compete up to 10 wk after soybean unifoliate expansion. Season-long competition of waterhemp plants reduced soybean yields by 37% to 44% (Steckel and Sprague Reference Steckel and Sprague2004a). Similarly, season-long interference of waterhemp reduced corn (Zea mays L.) grain yield by 11% to 74% (Steckel and Sprague Reference Steckel and Sprague2004b). Depending upon growing conditions and in the absence of crop competition, a single female waterhemp plant can produce >100,000 seeds. Waterhemp seeds remain viable in the soil for several years, resulting in large soil seedbanks (Hager et al. Reference Hager, Wax, Simmons and Stoller1997; Nordby et al. Reference Nordby, Hartzler and Bradley2007). In controlled seedbank burial studies, about 12% and 10% of the total waterhemp seedbank persisted after 3 and 4 yr of burial, respectively (Buhler and Hartzler Reference Buhler and Hartzler2001; Nordby et al. Reference Nordby, Hartzler and Bradley2007; Steckel et al. Reference Steckel, Sprague, Stoller, Wax and Simmons2007).
Waterhemp is highly prone to evolve herbicide resistance (Heap Reference Heap2024). Several waterhemp populations have been reported with resistance to seven different classes of herbicides, including inhibitors of acetolactate synthase (ALS), photosystem II (PS II), protoporphyrinogen oxidase (PPO), 4-hydroxyphenylpyruvate dioxygenase (HPPD), 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), very-long-chain fatty acid (VLCFA), and synthetic auxins (Bernards et al. Reference Bernards, Crespo, Kruger, Gaussoin and Tranel2012; Guo et al. Reference Guo, Riggins, Hausman, Hager, Riechers, Davis and Tranel2015; Hausman et al. Reference Hausman, Singh, Tranel, Riechers, Kaundun, Polge, Thomas and Hager2011; Heap Reference Heap2024; Patzoldt et al. Reference Patzoldt, Dixon and Tranel2003; Shoup et al. Reference Shoup, Al-Khatib and Peterson2003; Zelaya and Owen Reference Zelaya and Owen2005). Among all these reported cases, glyphosate resistance is quite common among waterhemp populations (Heap Reference Heap2024). Since its first confirmed occurrence in Missouri in 2005, glyphosate-resistant (GR) waterhemp has been reported from 21 states and one province, Ontario, in Canada (Heap Reference Heap2024). In addition, multiple herbicide resistance within waterhemp populations is also a significant concern (Heap Reference Heap2024). For instance, five-way (resistance to ALS, EPSPS, PS II, PPO, and HPPD inhibitors) and six-way (resistance to ALS, EPSPS, PS II, PPO, HPPD inhibitors, and synthetic auxins) multiple herbicide–resistant (MHR) waterhemp populations have been reported in Illinois and Missouri, respectively (Evans et al. Reference Evans, Strom, Riechers, Davis, Tranel and Hager2019; Shergill et al. Reference Shergill, Barlow, Bish and Bradley2018a). The rapid evolution and spread of MHR waterhemp populations further limits the number of alternative herbicide options available for their effective control (Bell et al. Reference Bell, Hager and Tranel2013; Faleco et al. Reference Faleco, Oliveira, Arneson, Renz, Stoltenberg and Werle2022: Legleiter and Bradley Reference Legleiter and Bradley2008; Schultz et al. Reference Schultz, Chatham, Riggins, Tranel and Bradley2015; Singh et al. Reference Singh, Garetson, McGinty, Dotray, Morgan, Nolte and Bagavathiannan2020).
Waterhemp populations were first observed in crop fields in 2014 in the central and western parts of New York state (Brown and Hunter Reference Brown and Hunter2019; M. Stanyard, personal communication). Some of these populations were believed to have arrived via used farm equipment purchased from midwestern states (Hunter and Sosnoskie Reference Hunter and Sosnoskie2024). Currently, waterhemp populations are distributed across 20 counties in New York state, infesting a large acreage of field and specialty crops, including corn (Zea mays L.), soybean [Glycine max (L.) Merr.], alfalfa (Medicago sativa), snap beans and dry beans (Phaseolus spp.), squashes (Cucurbita spp.), and others (Marschner Reference Marschner2024). The majority of conventional field crop producers (mainly corn and soybean) in New York state rely on glyphosate applications in burndown (prior to crop seeding), in-season, and postharvest situations for season-long weed control (M. Stanyard, personal observation). In recent yrs, waterhemp populations surviving glyphosate applications have become quite evident in soybean and corn fields in New York. During the 2023 growing season, waterhemp control failures were observed in two separate soybean fields in Seneca County in central New York following repeated applications of glyphosate at rates >1,200 g ha−1. In response to control failures, these waterhemp populations were collected from growers’ fields to evaluate them for suspected resistance to glyphosate. Furthermore, limited information exists on the effectiveness of alternative postemergence herbicides to control these putative GR waterhemp populations from New York state. Therefore, the main objectives of this research were to 1) confirm and characterize the level of glyphosate resistance in selected waterhemp populations and 2) investigate the efficacy of alternative postemergence herbicides to control these GR populations in New York.
Materials and Methods
Plant Materials
About 25 plants from two putative GR waterhemp populations surviving glyphosate application at 1,260 g ha−1 were collected in late summer 2023. The first field, referred to as NY1, was located near Seneca Falls, while the second field, referred to as NY2, was located near Junius. Both fields are in Seneca County, approximately 15 km apart. Both fields were historically under corn-soybean rotations with repeated glyphosate use. To obtain seeds for the experiments, field-collected waterhemp plants from both NY1 and NY2 populations were separately grown in two separate greenhouses at Cornell University in Ithaca, NY, in 10-L pots, and were allowed to mature during fall 2023. The first-generation seeds from both waterhemp populations harvested at maturity were used in subsequent greenhouse experiments. Furthermore, seeds of a previously known glyphosate-susceptible waterhemp population (NE_SUS) from a field site near Clay Center, Nebraska, were used (Sarangi et al. Reference Sarangi, Sandell, Knezevic, Aulakh, Lindquist, Irmak and Jhala2015).
Glyphosate Dose-Response Experiments
Greenhouse experiments were conducted at the Guterman bioclimatic laboratory at Cornell University in Ithaca during spring 2024. Seeds of the NY1, NY2, and NE_SUS waterhemp populations were planted, separately, on the surface of 54 × 34 × 6-cm germination flats filled with a Cornell greenhouse potting mixture (mixture of Canadian peat moss, vermiculite, perlite, dolomite lime, Jack’s 10-5-10 media mix plus II and calcium sulfate). Waterhemp seedlings from each population were separately transplanted into 10-cm-square plastic pots (Greenhouse Megastore, Danville, IL) containing the same potting mixture as the germination trays. Experiments were set up in a randomized complete block (blocked by population) design with 15 replications (one plant per pot = one replication) and repeated. Greenhouse conditions were set at 27/24 ± 3 C day/night temperatures with 16/8 h day/night photoperiods; the supplemental photoperiod was obtained with metal halide lamps (450 µmol m−2 s−1). Young waterhemp seedlings (7 to 10 cm tall) from each population were sprayed with the isopropylamine salt of glyphosate (Durango™, Corteva Agrisciences, Indianapolis, IN) at doses of 0, 319, 638, 1,276 (field-use rate, 1×), 2,552, 5,104, 10,208, and 20,416 g ha−1 combined with ammonium sulfate (AMS) at 20 g L−1. Treatments were applied using a stationary cabinet spray chamber (Research Track Sprayer, De Vries Manufacturing, Hollandale, MN) equipped with a flat-fan 8002XR nozzle tip (TeeJet Technologies, Glendale Heights, IL) calibrated to deliver 141 L ha−1 of spray solution at 276 kPa. All treated plants were returned to the greenhouse and watered daily to avoid moisture stress and maintain adequate growth. At 21 d after treatment (DAT), waterhemp plants were harvested at the soil level and dried at 65 C for 5 d to determine the aboveground shoot dry weight. The aboveground shoot dry weight reduction was calculated as percentage of the nontreated control.
Effectiveness of Alternative Postemergence Herbicides
Greenhouse experiments were conducted at the Guterman greenhouse facility at Cornell University during spring 2024 and repeated to evaluate the effectiveness of alternative postemergence herbicides for control of GR common waterhemp populations from New York. Seedlings from NY1, NY2, and NE_SUS common waterhemp populations were grown in germination trays and then transplanted in 10-cm-square pots containing Cornell potting mixture as previously described. A randomized complete block design was used with 15 replications (one plant per pot) for each selected postemergence herbicide and population combination. A total of nine postemergence herbicides (Table 1) were evaluated in this study. A nontreated control for each population was included for treatment comparison. The selected postemergence herbicides were applied at their field-use rates for corn and/or soybean. Herbicide application procedures and plant growth conditions were similar to those described in the glyphosate dose-response experiments. All selected postemergence herbicides were applied to 8- to 10-cm-tall common waterhemp plants. Percent visual control and shoot dry weights of each common waterhemp population were determined at 21 DAT. For each population, shoot dry weights were expressed as a percentage of the nontreated control.
Table 1. Alternative postemergence herbicides tested for controlling glyphosate-resistant and glyphosate-susceptible waterhemp populations in the greenhouse study.a
a Abbreviations: ALS, acetolactate synthase; EPSPS, 5-enolpyruvylshikimate-3-phosphate synthase; GSI, glutathione synthetase; HPPD, 4-hydroxyphenylpyruvate dioxygenase; PPO, Protoporphyrinogen oxidase; PS II, photosystem II.
b Crop oil concentrate at 10 ml L−1 was included.
c Ammonium sulfate at 20 g L−1 was included.
Statistical Analyses
Data from both experiments were checked for ANOVA assumptions using the Shapiro-Wilk and Levene tests with the UNIVARIATE and GLM procedures, respectively, in SAS (v.9.3; SAS, Cary, NC) and all data met ANOVA assumptions. Data were subjected to ANOVA using the MIXED procedure in SAS software to test the significance of fixed effects (population, treatment [i.e., glyphosate dose or alternative postemergence herbicide], and their interactions). Random effects in the model were experiment run and replications nested within experimental runs. For both studies, data were combined across experimental runs due to nonsignificant experimental run by treatment interactions (P = 0.235 for glyphosate dose response experiment; P = 0.412 for alternative postemergence herbicide experiment). Shoot dry weights (% of nontreated) of each common waterhemp population from the dose-response study were regressed against glyphosate doses using a three-parameter log-logistic model (Ritz et al. Reference Ritz, Baty, Streibig and Gerhard2015):
$$y = d/\left\{ {1 + {\rm{exp}}\left[ {b\left( {\log \left( x \right) - \log \left( e \right)} \right)} \right]} \right\}$$
where y is the shoot dry weight reduction (% of nontreated), d is the maximum shoot dry weight, e is the glyphosate dose required for 50% reduction in shoot dry weights (referred to as GR50 values, respectively), x is the glyphosate dose, and b represents the slope of each curve. The Akaike information criterion was used to select the nonlinear three-parameter model. A lack-of-fit test (P = 0.247) indicated that the selected nonlinear model accurately described the shoot dry weight response of each waterhemp population (Ritz et al. Reference Ritz, Baty, Streibig and Gerhard2015). All nonlinear regression parameter estimates, standard errors, and GR90 values (glyphosate dose required for a 90% reduction in shoot dry weights) were determined by using the drc package in R software (Ritz et al. Reference Ritz, Baty, Streibig and Gerhard2015). On the basis of GR50 values, the resistance index (referred as R/S ratio) for each waterhemp population from New York was estimated by dividing the GR50 value for each GR waterhemp population from New York by the GR50 value of the NE_Sus population. For effectiveness of alternative postemergence herbicides, the data on percent visual control and shoot dry weights (% of nontreated) were arcsine-transformed before analysis to improve homogeneity of variance and normality of residuals. Nontransformed means are presented in tables based on the interpretations of the transformed data. Means were separated using Fisher’s protected LSD test at α = 0.05.
Results and Discussion
Glyphosate Dose Response
Results from the dose-response studies highlighted that two waterhemp populations (NY1 and NY2) from Seneca County, NY, were resistant to glyphosate (Table 2). The glyphosate dose that reduced shoot dry weights by 50% (GR50 values) for the NY1 and NY2 populations ranged from 1,685 to 2,502 g ha−1, which was significantly higher (based on 95% CI) than that of the NE_SUS population (299 g ha−1). Based on GR50 values, the NY1 population was 8.3-fold resistant and the NY2 population was 5.6-fold resistant to glyphosate, compared with the NE_Sus population (Table 2; Figure 1). All tested plants of both NY1 and NY2 populations revealed a uniform glyphosate resistance trait as indicated by survival (although stunted) of both populations at 1× and 2× rates. Furthermore, the estimated glyphosate dose that reduced 90% shoot dry weights (GR90 values) of the NY1 and NY2 populations ranged from 18,672 to 23,630 g ha−1, which was greater than that of the NE_Sus population (2,957 g ha−1), and the field-use rate (1,276 g ha−1). Based on the GR90 values, the NY1 and NY2 waterhemp populations were, respectively, 6.3-fold and 7.9-fold more resistant to glyphosate than the NE_Sus population (Table 2; Figure 1).
Table 2. Regression parameter estimates of the three-parameter log-logistic equation fitted to the shoot dry weight (% of nontreated) of glyphosate-resistant and -susceptible waterhemp populations from New York and Nebraska, respectively, at 21 d after treatment (with various glyphosate doses in a greenhouse study.
a NY1 and NY2 are putative glyphosate-resistant waterhemp populations collected from two separate soybean fields in the 2023 growing season from Seneca County, NY. NE_Sus is a known glyphosate-susceptible waterhemp population collected from a field site near Clay Center, Nebraska.
b Parameter d is the upper limit, b is the slope of each curve, and GR50 is the effective dose (g ha−1) of glyphosate required for 50% shoot dry weight reduction (% of nontreated) for each waterhemp population; CI is the confidence interval.
c R/S is the ratio of GR50 values of each putative glyphosate-resistant population relative to that of GR50 value of a susceptible population.
Figure 1. Shoot dry weight response (% of nontreated) of glyphosate-resistant (NY1 and NY2) and glyphosate-susceptible (NE_ Sus) waterhemp populations treated with various doses of glyphosate at 21 d after treatment in a greenhouse study conducted at the Cornell University Guterman bioclimatic laboratory in Ithaca, NY. Symbols indicate actual values of shoot dry weights (% of nontreated), and lines indicate predicted values of shoot dry weights (% of nontreated) obtained from the three-parameter log-logistic model. Vertical bars indicate model-based standard errors (plus and minus) of the predicted mean.
Previous research reported a variable level of glyphosate resistance in waterhemp populations across several U.S. states. For instance, Singh et al. (Reference Singh, Garetson, McGinty, Dotray, Morgan, Nolte and Bagavathiannan2020) reported a high level resistance (17-fold) to glyphosate in a waterhemp population from Texas as compared with a susceptible population. Similarly, Legleiter and Bradley (Reference Legleiter and Bradley2008) reported 19-fold resistance to glyphosate in a waterhemp population from Missouri. Sarangi et al. (Reference Sarangi, Sandell, Knezevic, Aulakh, Lindquist, Irmak and Jhala2015) found 3-fold to 39-fold resistance to glyphosate in different waterhemp accessions collected in Nebraska. Our results are consistent with those published by Smith and Hallett (Reference Smith and Hallett2006), who previously reported up to 9-fold resistance to glyphosate in waterhemp accessions collected from Illinois, Iowa, and Missouri. More recently, GR waterhemp populations have also been identified in Idaho and in Ontario, Canada (Adjesiwor Reference Adjesiwor2022; Heap Reference Heap2024). The majority of these previously reported GR waterhemp populations were identified from GR crops, where glyphosate use was frequently used. The glyphosate use patterns were similar in New York, where soybean and corn producers rely heavily on glyphosate for in-season weed control with less reliance on preemergence-applied residual herbicides.
Effectiveness of Alternative Postemergence Herbicides
Waterhemp populations differed in their response to herbicides as evident from the visual control (P < 0.0001) and shoot dry weight reduction (P < 0.0001). The glyphosate-sensitive population NE_Sus was controlled by ≥98% with the labeled rates of all tested herbicides, except for mesotrione, which provided only 62% control 21 DAT (Table 3). Unsatisfactory control with meostrione further points toward potential HPPD-inhibitor resistance as well in this population. The evolution of HPPD-inhibitor-resistant waterhemp has already been confirmed in Iowa, Illinois, Nebraska, and North Carolina (Heap Reference Heap2024; McMullan and Green Reference McMullan and Green2011; Oliveira et al. Reference Oliveira, Jhala, Gaines, Irmak, Amundsen, Scott and Knezevic2017; Shergill et al. Reference Shergill, Bish, Jugulam and Bradley2018b).
Table 3. Percent visual control and shoot dry weight reduction (% of nontreated) of glyphosate-resistant and -susceptible waterhemp populations from New York and Nebraska with various postemergence herbicides at their labeled field-use rates 21 d after treatment.a,b
a NY1 and NY2 are putative glyphosate-resistant waterhemp populations collected from two separate soybean fields in the 2023 growing season from Seneca County, NY; NE_SUS is a known glyphosate-susceptible common waterhemp population collected from a field site near Clay Center, Nebraska.
b For percent control or shoot dry weight, means for a waterhemp population within a column followed by similar lowercase letters are not significantly different based on Fisher’s protected LSD test at P< 0.05; means for an herbicide within a row followed by similar uppercase letters are not significantly different based on Fisher’s protected LSD test at P < 0.05.
c Crop oil concentrate at 10 ml L−1 was included.
d Ammonium sulfate at 20 g L−1 was included.
The GR waterhemp populations from New York (NY1 and NY2) responded similarly to herbicides in this study. Both NY1 and NY2 populations were controlled ≥97% with 2,4-D, dicamba, glufosinate, and the 2,4-D + glufosinate mixture. Although 2,4-D and glufosinate applied alone were as effective as 2,4-D + glufosinate in controlling the GR waterhemp, herbicide mixtures can greatly minimize the chances of selection for herbicide resistance (Aulakh et al. Reference Aulakh, Chahal and Jhala2016; Benoit et al. Reference Benoit, Soltani, Hooker, Robinson and Sikkema2019b; Jhala et al. Reference Jhala, Sandell, Sarangi, Kruger and Knezevic2017; Kumar et al. Reference Kumar, Aulakh, Liu and Jhala2023; Willemse et al. Reference Willemse, Soltani, Benoit, Hooker, Jhala, Robinson and Sikkema2021). With lactofen, the average waterhemp control was 86% and 99% for the NY1 and NY2 populations, respectively. Aulakh et al. (Reference Aulakh, Chahal and Jhala2016) reported 98% or greater control of 10- to 20-cm-tall common waterhemp with two different lactofen formulations. Lactofen and glufosinate have also been found to be very effective against Palmer amaranth, a closely related pigweed species (Aulakh et al. Reference Aulakh, Chahal, Kumar, Price and Guillard2021; Kumar et al. Reference Kumar, Aulakh, Liu and Jhala2023).
With the labeled rates of atrazine, chlorimuron + thifensulfuron, or mesotrione, both NY1 and NY2 populations were controlled by <60%, indicating a high probability of multiple resistance to ALS-, HPPD-, and PS II-inhibitor herbicides. Waterhemp biotypes that are resistant to atrazine, chlorimuron, and mesotrione have already been reported from Illinois, Iowa, and North Carolina (Heap Reference Heap2024). Furthermore, waterhemp biotypes that are cross-resistant to mesotrione, tembotrione, and topramezone have been reported from Illinois and Nebraska (McMullan and Green Reference McMullan and Green2011; Oliveira et al. Reference Oliveira, Jhala, Gaines, Irmak, Amundsen, Scott and Knezevic2017).
Consistent with visual control ratings, shoot dry weight reduction 21 DAT revealed similar differences among alternative postemergence herbicides within and across waterhemp populations (Table 3). For instance, all postemergence herbicides reduced shoot dry weights (% of nontreated) of the NE_Sus population by 97% to 100%, except for mesotrione (67%). Consistent with visual control ratings, the highest shoot dry weight reductions (90% to 100%) of NY1 and NY2 waterhemp populations were achieved with dicamba, glufosinate, lactofen, 2,4-D alone or in mixture with glyphosate or glufosinate. Compared with the NE_Sus population, the shoot dry weight reductions of NY1 and NY2 populations were significantly lower with postemergence-applied atrazine (52% to 59%), chlorimuron + thifensulfuron (63% to 67%), and mesotrione (50% to 54%) at 21 DAT (Table 3).
MHR amaranths are perceived to be a major production constraint in North America (Aulakh et al. Reference Aulakh, Chahal, Kumar, Price and Guillard2021, Reference Aulakh, Kumar, Brunharo, Veron and Price2024; Benoit et al. Reference Benoit, Hedges, Schryver, Soltani, Hooker, Robinson, Laforest, Soufiane, Tranel, Giacomini and Sikkema2019a; Jhala et al. Reference Jhala, Sandell, Sarangi, Kruger and Knezevic2017; Khort and Sprague Reference Khort and Sprague2017; Kumar et al. Reference Kumar, Aulakh, Liu and Jhala2023; Schryver et al Reference Schryver, Soltani, Hooker, Robinson, Tranel and Sikkema2017; Tranel Reference Tranel2021; Vyn et al. Reference Vyn, Swanton, Weaver and Sikkema2006). Waterhemp has evolved resistance to seven herbicide sites-of-action in the United States (Bernards et al. Reference Bernards, Crespo, Kruger, Gaussoin and Tranel2012; Bobadilla et al. Reference Bobadilla, Giacomini, Hager and Tranel2021; Evans et al. Reference Evans, Strom, Riechers, Davis, Tranel and Hager2019; Faleco et al. Reference Faleco, Oliveira, Arneson, Renz, Stoltenberg and Werle2022; Heap Reference Heap2024; Sarangi et al. Reference Sarangi, Sandell, Knezevic, Aulakh, Lindquist, Irmak and Jhala2015; Shergill et al. Reference Shergill, Barlow, Bish and Bradley2018a; Thinglum et al. Reference Thinglum, Riggins, Davis, Bradley, Al-Khatib and Tranel2011; Vennapusa et al. Reference Vennapusa, Faleco, Vieira, Samuelson, Kruger, Werle and Jugulam2018). Recently, a waterhemp biotype resistant to six herbicide sites of action (Groups 2, 4, 5, 9, 14, and 27 as categorized by the Weed Science Society of America) has been confirmed in Missouri, with 16% of individual plants possessing genes for six-way resistance (Shergill et al. Reference Shergill, Bish, Jugulam and Bradley2018b).
In this study, NE_Sus, NY1, and NY2 populations were controlled by 86% to 99% with the labeled rates of 2,4-D, dicamba, glufosinate, or lactofen applied alone. This indicates that an array of effective postemergence herbicide sites of action exists, particularly for the management of these GR populations. However, a reduced sensitivity to atrazine and chlorimuron + thifensulfuron in NY1 and NY2 and to mesotrione in NE_SUS, NY1, and NY2 populations was observed. This is not surprising because waterhemp populations that are resistant to ALS, EPSPS, PS II inhibitors have been widely reported in the United States (Heap Reference Heap2024). Waterhemp populations with confirmed resistance to 2,4-D, dicamba, and lactofen (Benoit et al. Reference Benoit, Hedges, Schryver, Soltani, Hooker, Robinson, Laforest, Soufiane, Tranel, Giacomini and Sikkema2019a; Heap Reference Heap2024; Shergill et al. Reference Shergill, Barlow, Bish and Bradley2018a) and reduced sensitivity to dicamba and glufosinate have also been reported elsewhere (Hamberg et al. Reference Hamberg, Yadav, Owen and Licht2023).
Practical Implications
This research confirms the first report of GR waterhemp populations in New York. In addition, the results highlight the possibility of ALS-, HPPD- and PS II-inhibitor resistance in GR waterhemp populations (i.e., multiple resistance) that further need to be investigated in a whole-plant dose-response study. Future studies will investigate the physiological, molecular, or genetic basis of glyphosate resistance, inheritance pattern, and associated fitness penalty (if any) in GR waterhemp populations (NY1 and NY2) from New York. Nonetheless, confirmation of GR waterhemp populations poses a serious concern for producers in New York and in the northeastern United States. Producers should make all possible efforts to adopt best management practices to manage GR waterhemp populations (Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barret2012). Among postemergence herbicides, 2,4-D alone or combined with glyphosate or glufosinate, dicamba, glufosinate, and lactofen provided effective control of two GR waterhemp populations from New York, with responses to these herbicides being equivalent to the susceptible population (NE_Sus). Growers can use these herbicides for effective control of the GR waterhemp populations that were tested in a corn-soybean rotation. Multi-location field trials are currently in progress across New York to investigate various soil-applied preemergence herbicides alone or with postemergence herbicides for control of GR waterhemp populations in corn and soybean. Combining preemergence and postemergence emergence herbicides with diverse sites of action has often provided season-long control of herbicide-resistant weeds (Aulakh et al. Reference Aulakh, Price, Enloe, van Santen, Wehtje and Patterson2012, Reference Aulakh, Price, Enloe, Wehtje and Patterson2013; Benoit et al. Reference Benoit, Soltani, Hooker, Robinson and Sikkema2019b; Jhala et al. Reference Jhala, Sandell, Sarangi, Kruger and Knezevic2017; Khort and Sprague Reference Khort and Sprague2017). Employing the stacked gene herbicide-resistant technologies in tandem with ecological weed management tactics such as cover cropping, implementing a competitive crop rotation, tillage, and harvest weed seed control techniques are mandatory for managing GR waterhemp and preventing its further spread.
Acknowledgments
We thank the growers in Seneca County, New York, for contacting us and requesting that we investigate suspected resistant waterhemp populations and for their valuable assistance in sample collection. We also thank Henrique Scatena, Preetaman Bajwa, and Emily Nelson for their assistance in data collection in greenhouse experiments.
Funding
Financial support for this research was provided by the New York Corn and Soybean Growers Association Soybean Checkoff program via grant 168758.
Competing Interests
The authors declare they have no conflicts of interest.
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