Hostname: page-component-848d4c4894-v5vhk Total loading time: 0 Render date: 2024-06-28T15:46:08.521Z Has data issue: false hasContentIssue false

Herbicide-Resistant Kochia (Bassia scoparia) in North America: A Review

Published online by Cambridge University Press:  07 December 2018

Vipan Kumar
Affiliation:
Assistant Professor, Kansas State University, Agricultural Research Center, Hays, KS, USA
Prashant Jha*
Affiliation:
Associate Professor, Montana State University, Southern Agricultural Research Center, Huntley, MT, USA
Mithila Jugulam
Affiliation:
Associate Professor, Kansas State University, Department of Agronomy, Manhattan, KS, USA
Ramawatar Yadav
Affiliation:
Graduate Research Assistant, Montana State University, Southern Agricultural Research Center, Huntley, MT, USA
Phillip W. Stahlman
Affiliation:
Emeritus Professor, Kansas State University, Agricultural Research Center, Hays, KS, USA
*
Author for correspondence: Prashant Jha, Associate Professor, Montana State University, Southern Agricultural Research Center, Huntley, MT, 59037. (Email: [email protected])
Rights & Permissions [Opens in a new window]

Abstract

Kochia [Bassia scoparia (L.) A. J. Scott] is a problematic annual broadleaf weed species in the North American Great Plains. Bassia scoparia inherits unique biological characteristics that contribute to its propensity to evolve herbicide resistance. Evolution of glyphosate resistance in B. scoparia has become a serious threat to the major cropping systems and soil conservation practices in the region. Bassia scoparia populations with resistance to four different herbicide sites of action are a concern for growers. The widespread occurrence of multiple herbicide–resistant (HR) B. scoparia across the North American Great Plains has renewed research efforts to devise integrated weed management strategies beyond herbicide use. In this review, we aim to compile and document the growing body of literature on HR B. scoparia with emphasis on herbicide-resistance evolutionary dynamics, distribution, mechanisms of evolved resistance, agronomic impacts, and current/future weed management technologies. We focused on ecologically based, non-herbicidal strategies such as diverse crop rotations comprising winter cereals and perennial forages, enhanced crop competition, cover crops, harvest weed seed control (HWSC), and tillage to manage HR B. scoparia seedbanks. Remote sensing using hyperspectral imaging and other sensor-based technologies would be valuable for early detection and rapid response and site-specific herbicide resistance management. We propose research priorities based on an improved understanding of the biology, genetic diversity, and plasticity of this weed that will aid in preserving existing herbicide resources and designing sustainable, integrated HR B. scoparia mitigation plans.

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
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 in any medium, provided the original work is properly cited.
Copyright
© Weed Science Society of America, 2018

Introduction

Kochia [Bassia scoparia (L.) A. J. Scott] is an invasive summer annual native to eastern and central Europe and western Asia (Ball et al. Reference Ball, Cudney, Dewey, Elmore, Lym, Morishita, Parker, Swan, Whitson and Zollinger2000; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009). Bassia scoparia is a monoecious diploid (2n = 18) that belongs to the “Chenopodiaceae” family. European immigrants first introduced this species as an ornamental plant to North America in the mid- to late 1800s (Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009; Georgia Reference Georgia1914). By 2007, B. scoparia was widespread across several states in the United States and in Canadian provinces (Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009; Meades et al. Reference Meades, Hay and Brouillet2000; USDA-NRCS 2008). Infestation of B. scoparia is common in cultivated fields, gardens, roadsides, grasslands, ditch banks, pastures, and rangeland (Forcella Reference Forcella1985; Frankton and Mulligan Reference Frankton and Mulligan1987; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009).

Bassia scoparia exhibits unique biological characteristics, including C4 growth habit, low innate seed dormancy (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009; Kumar and Jha Reference Kumar and Jha2017), low seed persistence in the soil (≤2 yr), early and rapid emergence, and high tolerance to abiotic stresses (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009; Kumar et al. Reference Kumar, Jha, Dille and Stahlman2018a; Schwinghamer and Van Acker Reference Schwinghamer and Van Acker2008). Bassia scoparia produces protogynous flowers, ensuring a high level of outcrossing and a high genetic diversity within or among populations (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016; Mengistu and Messersmith Reference Mengistu and Messersmith2002; Stallings et al. Reference Stallings, Thill, Mallory-Smith and Shafii1995).

In recent years, B. scoparia has become one of the most problematic weeds in croplands and non-croplands across the region (Eberlein and Fore Reference Eberlein and Fore1984; Forcella Reference Forcella1985; Heap Reference Heap2018; Wicks et al. Reference Wicks, Martin, Haack and Mahnken1994). Bassia scoparia at densities of 240 to 520 plants m−2 reduced spring wheat (Triticum aestivum L.) grain yield by up to 60% (Friesen et al. Reference Friesen, Mayert and Morrison1991a, Reference Friesen, Mayert and Morrison1991b, Reference Friesen, Mayer and Morrison1991c). In another study, B. scoparia at densities of 14 plants m−2 reduced wheat grain yield by 10% to 25% (Friesen et al. Reference Friesen, Mayert and Morrison1990a, Reference Friesen, Mayert and Morrison1990b, Reference Friesen, Mayert and Morrison1990c). The presence of B. scoparia at wheat harvest not only contaminates wheat grain, but also reduces the harvesting efficiency, because uncontrolled or late-emerging B. scoparia plants are normally green at wheat harvest. Furthermore, uncontrolled B. scoparia can potentially add more than 100,000 seeds m−2 to the soil seedbank after wheat harvest (Kumar and Jha Reference Kumar and Jha2015d).

Sugar beet (Beta vulgaris L.) is among the least competitive crops to B. scoparia. Even at a low density of 0.2 to 0.5 plants m−1 row, B. scoparia can reduce sugar beet root yields by 18% to 32% (Mesbah et al. Reference Mesbah, Miller, Fornstrom and Legg1994; Schweizer Reference Schweizer1973). At a B. scoparia density of 3 plants m−1 of row, sugar beet root yield was reduced by 78%. Weatherspoon and Schweizer (Reference Weatherspoon and Schweizer1971) reported up to a 95% reduction in sugar beet root yield with a season-long interference of B. scoparia. Season-long interference of B. scoparia at densities of 0.3, 1, 3, and 6 plants m−1 of row reduced common sunflower (Helianthus annuus L.) achene yield by 7%, 10%, 20%, and 27%, respectively (Durgan et al. Reference Durgan, Dexter and Miller1990). Up to 76% yield reductions in sunflower has been reported when B. scoparia plants emerged with sunflower (Lewis and Gulden Reference Lewis and Gulden2014). Bassia scoparia interference in soybean [Glycine max (L.) Merr.], sorghum [Sorghum bicolor (L.) Moench ssp. bicolor], and corn (Zea mays L.) can reduce grain yields by 30%, 38%, and 40%, respectively (Waite et al. Reference Waite, Thompson, Peterson, Currie, Olson, Stahlman and Khatib2013; Wicks et al. Reference Wicks, Martin and Mahnken1993, Reference Wicks, Martin, Haack and Mahnken1994).

The problem is further exacerbated due to the widespread occurrence of B. scoparia populations with evolved resistance to several different herbicide sites of action. Since 1976, when the first case of B. scoparia resistance to atrazine (photosystem II [PSII] inhibitor) was reported, there has been a steady increase in the number of herbicide-resistance cases in B. scoparia (Heap Reference Heap2018). Increasing reports of herbicide-resistant (HR) B. scoparia have renewed interests of academic weed scientists and industry in an improved understanding of the biology, ecology, and multitactic strategies to manage this weed. Several studies have recently been published on evolution of herbicide resistance and biochemical/physiological mechanisms of evolved resistance, ecological investigations of the life-history traits and fitness, and alternative strategies to manage HR B. scoparia. This article aims to document the current state of knowledge on HR B. scoparia that can serve as a resource for future research and extension needs to manage the problem.

Chronology and Distribution of HR Bassia scoparia

The first case of B. scoparia resistance to atrazine in the United States was documented in 1976 from cornfields in Kansas and along railroads in Idaho and Iowa (Heap Reference Heap2018). Subsequently, resistance to atrazine was found along railroad rights-of-way from 11 additional states in the United States (Bandeen et al. Reference Bandeen, Stephenson and Cowett1982; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009). The first case of B. scoparia resistance to acetolactate synthase (ALS)-inhibiting herbicides was reported from a wheat field in Kansas in 1987, just 5 yr after the commercialization of this herbicide chemistry in wheat (Primiani et al. Reference Primiani, Cotterman and Saari1990; Saari et al. Reference Saari, Cotterman and Primiani1990). A field survey conducted in 1992 from cropland and non-cropland areas indicated that 46%, 55%, and 45% of B. scoparia samples from Colorado, Idaho, and Montana, respectively, were resistant to ALS inhibitors (Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009). In Canada, B. scoparia populations resistant to ALS inhibitors were first reported in Manitoba (>10 field sites) and Saskatchewan (>50 field sites) in 1988 and from a wheat field in Alberta in 1989 (Heap Reference Heap2018; Morrison and Devine Reference Morrison and Devine1994). The majority of B. scoparia populations resistant to ALS inhibitors in the Canadian prairies were from semiarid grassland fields (Beckie et al. Reference Beckie, Hall and Tardif2001, Reference Beckie, Leeson, Thomas, Brenzil, Holzgang, Lozinski and Shirriff2008; Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009). In a field survey conducted in southern Manitoba in 2004, 93 out of 112 B. scoparia samples were found resistant to ALS inhibitors (Friesen et al. Reference Friesen, Beckie, Warwick and Van Acker2009). Similarly, Beckie et al. (Reference Beckie, Warwick, Sauder, Lozinski and Shirriff2011) reported ALS inhibitor–resistant B. scoparia in 85% of the fields surveyed in western Canada. Multiple resistance to PSII and ALS inhibitors was first reported in B. scoparia populations along roadsides from Indiana and in wheat/corn from Illinois in 1995 (Chodova and Mikulka Reference Chodova and Mikulka2000; Foes et al. Reference Foes, Liu, Vigue, Stoller, Wax and Tranel1999).

The rapid spread of populations with resistance to PSII and ALS inhibitors increased the dependence on the use of auxinic herbicides, primarily dicamba and fluroxypyr, for B. scoparia control in wheat or corn grown in the Great Plains region. However, in 1995, populations resistant to dicamba and/or fluroxypyr were reported from wheat–chemical fallow fields in Montana and North Dakota (Cranston et al. Reference Cranston, Kern, Hackett, Miller, Maxwell and Dyer2001; Nandula and Manthey Reference Nandula and Manthey2002). Among all HR traits in B. scoparia, the rate of spread of auxinic resistance has been the slowest (Jha et al. Reference Jha, Kumar, Garcia and Reichard2015a). Since 1995, dicamba-resistant (DR) B. scoparia has been reported from six states in the U.S. Great Plains and in the Mountain West, including Montana, Idaho, North Dakota, Nebraska, Colorado, and Kansas (Heap Reference Heap2018). The discovery of B. scoparia populations with resistance to dicamba and fluroxypyr is a relatively new event in Canada, with reports from a few wheat production fields in Saskatchewan (H Beckie, personal communication). The auxinic-resistant B. scoparia populations from Canada were also resistant to ALS inhibitors, including thifensulfuron and tribenuron used in wheat (Heap Reference Heap2018).

After the decline in the price of glyphosate, growers relied heavily on glyphosate for weed control in the fallow phase of winter wheat–fallow or winter wheat–sorghum–fallow rotations across the U.S. Great Plains (Fenster and Wicks Reference Fenster and Wicks1982; Kumar et al. Reference Kumar, Jha and Reichard2014). On an average, each fallow field received three to four applications of glyphosate per season (spring to summer) before winter wheat planting in the fall. This continuous use of glyphosate had selected B. scoparia populations with evolved resistance to glyphosate. The first confirmation of glyphosate-resistant (GR) B. scoparia was from fallow fields in western Kansas in 2007 (Godar et al. Reference Godar, Stahlman, Jugulam and Dille2015; Heap Reference Heap2018; Waite et al. Reference Waite, Thompson, Peterson, Currie, Olson, Stahlman and Khatib2013). Since then, GR B. scoparia has been confirmed in 10 U.S. states and 3 Canadian provinces (Beckie et al. Reference Beckie, Blackshaw, Low, Hall, Sauder, Martin, Brandt and Shirriff2013; Godar et al. Reference Godar, Stahlman, Jugulam and Dille2015; Hall et al. Reference Hall, Beckie, Low, Shirriff, Blackshaw, Kimmel and Neeser2014; Kumar et al. Reference Kumar, Jha and Reichard2014; Waite et al. Reference Waite, Thompson, Peterson, Currie, Olson, Stahlman and Khatib2013; Wiersma et al. Reference Wiersma, Gaines, Preston, Hamilton, Giacomini, Buell, Leach and Westra2015). The majority of these GR populations originated in wheat–fallow systems. However, recent surveys from Montana, Wyoming, Colorado, Nebraska, Idaho, and Oregon indicate the occurrence of GR populations in GR corn–sugar beet rotations (Gaines et al. Reference Gaines, Barker, Patterson, Westra, Westra, Wilson, Jha, Kumar and Kniss2016; Kumar et al. Reference Kumar, Felix, Morishita and Jha2018b). In Canada, GR B. scoparia was first documented in 2011 from cereal production fields in southern Alberta (Beckie et al. Reference Beckie, Blackshaw, Low, Hall, Sauder, Martin, Brandt and Shirriff2013; Hall et al. Reference Hall, Beckie, Low, Shirriff, Blackshaw, Kimmel and Neeser2014). Furthermore, a majority of those GR B. scoparia populations were also resistant to ALS inhibitors (Hall et al. Reference Hall, Beckie, Low, Shirriff, Blackshaw, Kimmel and Neeser2014; Kumar et al. Reference Kumar, Jha, Giacomini, Westra and Westra2015).

In Montana, random field surveys for HR B. scoparia conducted from 2013 to 2016 found 45 field sites with GR, 15 with DR, and 10 sites with the presence of GR and DR (multiply resistant) B. scoparia (PJ, unpublished data). More than 95% of those surveyed B. scoparia populations were also resistant to ALS inhibitors (PJ unpublished data). Similarly, multiyear (2011 to 2014) random field surveys conducted in eastern Colorado identified 86 sites with GR, 25 sites with DR, and 29 sites with GR plus DR B. scoparia populations (Westra Reference Westra2016). Bassia scoparia populations with multiple resistance to glyphosate and dicamba have also been identified in western Kansas (Brachtenbach Reference Brachtenbach2015). More recently, populations with cross-resistance to dicamba and fluroxypyr have been reported from wheat fields in Montana, Nebraska, and Kansas (Jha et al. Reference Jha, Kumar and Lim2015b; Kumar et al. Reference Kumar, Stahlman, Currie, Engel and Boyer2018c; LeClere et al. Reference LeClere, Wu, Westra and Sammons2018). Additionally, a B. scoparia population with multiple resistance to glyphosate, ALS inhibitors, PSII inhibitors, and dicamba has recently been documented from a cornfield in Garden City, KS (Varanasi et al. Reference Varanasi, Godar, Currie, Dille, Thompson, Stahlman and Jugulam2015), indicating the widespread occurrence and severity of the problem.

Level of Herbicide Resistance in Bassia scoparia

Resistance to PSII Inhibitors

The level of resistance to PSII inhibitors was reported in B. scoparia accessions from North Dakota and Minnesota. The resistant populations exhibited 16-fold resistance to tebuthiuron and diuron but only up to 4-fold higher resistance to metribuzin compared with a known susceptible accession (Mengistu et al. Reference Mengistu, Christoffers and Lym2005). However, those populations exhibited a negative cross-resistance and were susceptible to bromoxynil.

Resistance to ALS Inhibitors

Bassia scoparia populations from Kansas were up to 354-fold more resistant to the four sulfonylurea herbicides, namely, chlorsulfuron, metsulfuron, sulfometuron, and thifensulfuron, compared with a susceptible population (Saari et al. Reference Saari, Cotterman and Primiani1990). A B. scoparia population from Illinois had 500- to >28,000-fold levels of resistance to atrazine, imazethapyr, thifensulfuron, and chlorsulfuron (Foes et al. Reference Foes, Liu, Vigue, Stoller, Wax and Tranel1999). Three populations from Montana exhibited up to a 196-fold resistance to chlorsulfuron and metsulfuron herbicides and were 2- to 6-fold cross-resistant to imazamethabenz, imazethapyr, imazapyr, and imazaquin herbicides (Sivakumaran et al. Reference Sivakumaran, Mulugeta, Fay and Dyer1993). Kumar et al. (Reference Kumar, Jha, Giacomini, Westra and Westra2015) confirmed B. scoparia populations from Montana with up to 30-fold resistance to a premixture of thifensulfuron + tribenuron + metsulfuron. In a more recent survey from Montana, up to 267-fold resistance to thifensulfuron, tribenuron, and metsulfuron were observed in several B. scoparia populations (PJ, unpublished data).

Resistance to Glyphosate

Three B. scoparia populations collected from southern Alberta wheat–fallow fields exhibited 4- to 7-fold resistance to glyphosate (Beckie et al. Reference Beckie, Blackshaw, Low, Hall, Sauder, Martin, Brandt and Shirriff2013). GR B. scoparia from wheat–fallow fields in Montana had 4.6- to 11-fold resistance to glyphosate (Kumar et al. Reference Kumar, Jha and Reichard2014). A population from Sheridan County, NE, had 6- and 15-fold resistance to glyphosate and tribenuron, respectively (Rana and Jhala Reference Rana and Jhala2016). GR B. scoparia populations collected from Kansas, Colorado, North Dakota, and South Dakota had 3.5- to 13.5-fold resistance to glyphosate (Godar et al. Reference Godar, Stahlman, Jugulam and Dille2015; Wiersma et al. Reference Wiersma, Gaines, Preston, Hamilton, Giacomini, Buell, Leach and Westra2015). Similarly, the B. scoparia populations collected from sugar beet fields in Idaho and Oregon exhibited 2.0- to 9.6-fold resistance to glyphosate (Kumar et al. Reference Kumar, Felix, Morishita and Jha2018b).

Resistance to Synthetic Auxins

An inbred B. scoparia line derived from a field population collected in Montana during 1995 had a 4.6-fold resistance to dicamba relative to an inbred susceptible line (Cranston et al. Reference Cranston, Kern, Hackett, Miller, Maxwell and Dyer2001). Three B. scoparia populations from Montana identified from wheat fields in 2011 had 1.3- to 6.8-fold and 1.4- to 5.7-fold resistance to dicamba and fluroxypyr, respectively, compared with a susceptible population (Jha et al. Reference Jha, Kumar and Lim2015b). In Nebraska, B. scoparia populations with an 18-fold difference in dicamba resistance between the least and most susceptible populations were found (Crespo et al. Reference Crespo, Bernards, Sbatella, Kruger, Lee and Wilson2014). In a recent report, an inbred DR B. scoparia line selected from a field population near Henry, NE, had 38-, 12-, and 13-fold resistance to dicamba, 2,4-D, and fluroxypyr herbicides, respectively (LeClere et al. Reference LeClere, Wu, Westra and Sammons2018). Based on the shoot dry weight response (GR50 values), 11 populations that were collected from western Kansas had an 8-fold difference in susceptibility to dicamba (Brachtenbach Reference Brachtenbach2015).

Mechanisms of Herbicide Resistance

Resistance to PSII Inhibitors

PSII inhibitors, such as atrazine, bromoxynil, and substituted urea (diuron and tebuthiuron), compete with plastoquinone for binding on the D1 protein in PSII during electron transport, thereby, affecting the production of reducing power (NADPH) and ATP; ultimately, the plant starves to death (Trebst and Draber Reference Trebst and Draber1986). Mutations in the psbA gene that encodes D1 protein result in amino acid substitutions conferring resistance to PSII inhibitors. PSII-inhibitor resistance in B. scoparia accessions from North Dakota and Minnesota, as a result of a Val-219-Ile substitution in the psbA gene, was found to confer a high resistance to diuron and tebuthiuron and a moderate resistance to metribuzin and atrazine (Mengistu et al. Reference Mengistu, Christoffers and Lym2005). Conversely, a B. scoparia population from Illinois, was found to show a high level of resistance to atrazine because of a point mutation resulting in a Ser-264-Gly substitution in the psbA gene (Foes et al. Reference Foes, Liu, Vigue, Stoller, Wax and Tranel1999). More recently, in a multiple-HR population from Kansas, a high level of resistance to atrazine because of a Ser-264-Gly substitution was also reported (Varanasi et al. Reference Varanasi, Godar, Currie, Dille, Thompson, Stahlman and Jugulam2015). The other amino acid substitutions that are known to confer resistance to PSII inhibitors, such as Val-219-Ser and Ala-251-Val were not found in this population (Varanasi et al. Reference Varanasi, Godar, Currie, Dille, Thompson, Stahlman and Jugulam2015).

Resistance to ALS Inhibitors

The most common mechanism of resistance to ALS inhibitors in plants is due to point mutations spanning five highly conserved domains of the ALS gene (Yu and Powles Reference Yu and Powles2014). Bassia scoparia populations from Kansas exhibited cross-resistance to sulfonylureas, imidazolinones, and sulfonanilides because of reduced sensitivity of the ALS enzyme (Saari et al. Reference Saari, Cotterman and Primiani1990). Subsequently, B. scoparia populations from the western Great Plains were found resistant to the ALS inhibitor chlorsulfuron (Guttieri et al. Reference Guttieri, Eberlein and Thill1995); a point mutation in the ALS gene resulting in a variety of amino acid substitutions conferred resistance in those populations (Guttieri et al. Reference Guttieri, Eberlein and Thill1995). Later, a B. scoparia population resistant to multiple ALS inhibitors was found in Illinois, and a Trp-570-Leu substitution on the ALS gene was found to confer cross-resistance to ALS inhibitors in this population (Foes et al. Reference Foes, Liu, Vigue, Stoller, Wax and Tranel1999). ALS inhibitor–resistant B. scoparia populations from several western provinces in Canada have also been well characterized. It has been reported that amino acid substitutions at the Pro-197, Asp-376, and Trp-574 residues confer resistance (Warwick et al. Reference Warwick, Xu, Sauder and Beckie2008). This suggests multiple origins of these mutations resulting in the evolution of resistance to ALS inhibitors in B. scoparia populations collected from geographically diverse locations (Warwick et al. Reference Warwick, Xu, Sauder and Beckie2008). More recently, Pro-197-Thr and Trp-574-Leu substitutions were found to confer high levels of resistance to ALS inhibitors in multiple-HR B. scoparia populations from Kansas (Varanasi et al. Reference Varanasi, Godar, Currie, Dille, Thompson, Stahlman and Jugulam2015).

Resistance to Glyphosate

The first case of field-evolved resistance to glyphosate in B. scoparia was documented in Kansas (Godar et al. Reference Godar, Stahlman, Jugulam and Dille2015). The amplification of the EPSPS gene has been found to confer resistance to glyphosate in all B. scoparia populations that have been tested (Jugulam et al. Reference Jugulam, Niehues, Godar, Koo, Danilova, Friebe, Sehgal, Varanasi, Wiersma, Westra, Stahlman and Gill2014; Kumar et al. Reference Kumar, Jha, Giacomini, Westra and Westra2015; Wiersma et al. Reference Wiersma, Gaines, Preston, Hamilton, Giacomini, Buell, Leach and Westra2015). Furthermore, the EPSPS transcript expression positively correlated with EPSPS copies (Wiersma et al. Reference Wiersma, Gaines, Preston, Hamilton, Giacomini, Buell, Leach and Westra2015). Fluorescence in situ hybridization analysis demonstrated that the amplified EPSPS copies are located on two homologous chromosomes, and the EPSPS copies increased with continued glyphosate selection (Jugulam et al. Reference Jugulam, Niehues, Godar, Koo, Danilova, Friebe, Sehgal, Varanasi, Wiersma, Westra, Stahlman and Gill2014). The continuous variation in EPSPS copies resulting in increased glyphosate resistance suggests that the EPSPS copy number in B. scoparia increases through an adaptive process. Although EPSPS gene amplification appears to be the common mechanism of glyphosate resistance in B. scoparia, it is possible that other mechanisms could confer resistance to this herbicide.

Resistance to Synthetic Auxins

Although the precise mechanism of action of auxinic herbicides is still not completely understood, recent research provides better knowledge about how these herbicides work in plants. Similar to the natural auxin indoleacetic acid (IAA), auxinic herbicides are thought to bind to the transport inhibitor response 1 and/or its homologues, leading to a rapid degradation of Aux/IAA repressors and expression of an auxin-responsive gene (Guilfoyle Reference Guilfoyle2007; Mithila et al. Reference Mithila, Hall, Johnson, Kelley and Riechers2011; Tan et al. Reference Tan, Calderon-Villalobos, Sharon, Zheng, Robinson, Estelle and Zheng2007). Grossmann (Reference Grossman2010) suggested that in addition to unregulated auxin response, the auxinic herbicide–sensitive dicots are killed due to the hyperaccumulation of ethylene, ABA, and reactive oxygen species. Any alterations in genes involved in auxinic herbicide signal transduction can potentially contribute to resistance mechanisms in auxinic herbicide–resistant dicot weeds.

The mechanism of auxinic herbicide resistance, specifically dicamba resistance in B. scoparia, has been characterized. It appears that dicamba resistance in B. scoparia can evolve via multiple mechanisms (Cranston et al. Reference Cranston, Kern, Hackett, Miller, Maxwell and Dyer2001; Dyer et al. Reference Dyer, Goss and Buck2002; Kern et al. Reference Kern, Chaverra, Cranston and Dyer2005; LeClere et al. Reference LeClere, Wu, Westra and Sammons2018; Pettinga et al. Reference Pettinga, Ou, Patterson, Jugulam, Westra and Gaines2017). It was suggested that reduced uptake, translocation, or increased metabolism of dicamba might not contribute to resistance in B. scoparia (Cranston et al. Reference Cranston, Kern, Hackett, Miller, Maxwell and Dyer2001). However, Dyer et al. (Reference Dyer, Goss and Buck2002) suggested that a mutation in the auxin receptor(s) might affect endogenous auxin binding and alter auxin-mediated responses, such as gravitropism and root growth inhibition. Later, it was found that compared with a dicamba-sensitive population, the DR B. scoparia population had delayed phenotypic response, such as shoot gravitropism, apical dominance, or root growth inhibition in the absence of dicamba (Goss and Dyer Reference Goss and Dyer2003). Furthermore, in that DR B. scoparia population, genes involved in cell wall modification (e.g., xyloglucan endotransglycosylase) and a gene/protein with unknown function were found to express differentially compared with a dicamba-sensitive population (Kern et al. Reference Kern, Chaverra, Cranston and Dyer2005). More recently, a transcriptome sequencing study on an inbred DR B. scoparia population from Nebraska has revealed a glycine to asparagine amino acid change within a highly conserved region of an AUX/IAA protein, KsIAA16 (LeClere et al. Reference LeClere, Wu, Westra and Sammons2018). Also, a double mutation in the auxin coreceptor gene Aux/IAA was identified, which conferred a low dicamba affinity in the Aux/IAA protein complex, enabling B. scoparia plants to cope with high levels of dicamba in cells (LeClere et al. Reference LeClere, Wu, Westra and Sammons2018). In another study using the same DR B. scoparia inbred line as LeClere et al. (Reference LeClere, Wu, Westra and Sammons2018), there was a 2-fold higher transcription of chalcone synthase (CHS) gene that regulates synthesis of the flavonols quercetin and kaempferol (Pettinga et al. Reference Pettinga, Ou, Patterson, Jugulam, Westra and Gaines2017). It has been proposed that greater flavonol synthesis resulting from increased CHS transcription would compete with the intercellular transport of dicamba molecules, which is regulated by the ATP-binding cassette subfamily B membrane transporters, thereby impairing the dicamba translocation in DR B. scoparia plants. Stress-induced (e.g., UV light or pathogen elicitors) transcription of CHS has been found to bestow a higher tolerance to abiotic or biotic stress (Dao et al. Reference Dao, Linthorst and Verpoorte2011). It was also proposed that the restricted auxin translocation with a higher upregulation of CHS might potentially have fitness costs in B. scoparia (Pettinga et al. Reference Pettinga, Ou, Patterson, Jugulam, Westra and Gaines2017). Subsequently, LeClere et al. (Reference LeClere, Wu, Westra and Sammons2018) confirmed that the presence of a dicamba resistance allele contributes to fitness penalty in this population. A previous genetic analysis of this B. scoparia inbred reported that a single gene with a high level of dominance controls dicamba resistance (Preston et al. Reference Preston, Belles, Westra, Nissen and Ward2009).

Pollen- and Seed-mediated Gene Flow in Bassia scoparia

Bassia scoparia is a genetically highly diverse species. High levels of both self- and cross-pollination have been shown to occur in this species (Thill et al. Reference Thill, Mallory-Smith, Saari, Cotterman, Primiani and Saladini1991), and considerable pollen-mediated gene flow and efficient seed dispersal facilitate both short- and long-distance gene flow (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016). A single B. scoparia plant can produce more than 100,000 seeds that can be dispersed long distances via the tumble mechanism, contributing to a rapid gene flow within and among populations (Baker et al. Reference Baker, Withrow, Brown and Beck2010; Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016; Christoffoleti et al. Reference Christoffoleti, Westra and Moore1997; Kumar and Jha Reference Kumar and Jha2015d). A substantial gene flow contributed to the high genetic diversity within and among B. scoparia populations from Montana, North Dakota, and Minnesota (Dyer et al. Reference Dyer, Birdsall and Zwaan1993a; Mengistu and Messersmith Reference Mengistu and Messersmith2002). Pollen-mediated gene flow for the spread of glyphosate resistance and seed-mediated gene flow of ALS-inhibitor resistance have been investigated in Canadian B. scoparia populations (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016). The results indicated that the gene transfer from GR to non-GR B. scoparia populations was from 5.3% to 7.5% and decreased significantly at a distance of 96 m. The study also suggested that the direction of wind at the time of pollination significantly influenced the pollen-mediated gene flow in this species (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016). On the other hand, seed-mediated gene flow of the ALS-inhibitor resistance varied with the tumbling speed of the mature plant and the distance traveled (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016). Gene flow between B. scoparia plants resistant and susceptible to ALS inhibitors was shown to occur at a maximum rate of 13% with a distance of 1.5 m and was substantially reduced (1.4%) at 29 m (Mallory-Smith et al. Reference Mallory-Smith, Thill and Stallings1993; Stallings et al. Reference Stallings, Thill, Mallory-Smith and Shafii1995). It was also reported that the pollen-mediated gene flow was 3-fold greater in the Canadian B. scoparia populations (96 m) compared with those from the western United States (26 m) (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016; Mallory-Smith et al. Reference Mallory-Smith, Thill and Stallings1993; Stallings et al. Reference Stallings, Thill, Mallory-Smith and Shafii1995). Mulugeta et al. (Reference Mulugeta, Maxwell, Fay and Dyer1994) reported that B. scoparia pollen can be deposited at a distance of 150 m from the source. Overall, because of the high frequency of both pollen- and seed-mediated gene flow in B. scoparia, there is a high risk of spread of single, cross-, or multiple-herbicide resistance alleles in this species.

Ecological Perspectives

Seed Germination and Emergence Dynamics

Bassia scoparia seed exhibits zero to very little (<10%) innate dormancy and low persistence (≤2 yr) in the soil (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017). It is often the first weed species to emerge in the spring in the Great Plains region (Schwinghamer and Van Acker Reference Schwinghamer and Van Acker2008; Zorner et al. Reference Zorner, Zimdahl and Schweizer1984). Schwinghamer and Van Acker (Reference Schwinghamer and Van Acker2008) observed that B. scoparia seeds placed at the soil surface had greater seedling emergence compared with those buried at a depth of 10 mm or greater, and no emergence occurred from depths below 80 mm in the soil (Schwinghamer and Van Acker Reference Schwinghamer and Van Acker2008). A more recent study conducted across several states in the U.S. Great Plains found that burial depths of 0 to 10 cm did not influence the seed viability over time; however, seeds buried at depths >2.5 cm failed to emerge (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017).

Bassia scoparia emergence initiated at 50 cumulative growing-degree days (GDD Tbase 0 C) and continued through the summer in the Northern Great Plains (Schwinghamer and Van Acker Reference Schwinghamer and Van Acker2008). At a semiarid site near Akron, CO, a majority of B. scoparia emergence occurred between April 25 and May 9 (Anderson and Nielsen Reference Anderson and Nielsen1996). The average cumulative GDD needed for 10% emergence was 168 across 11 site-years from Garden City, Ness City, Hays, Stockton, and Manhattan in Kansas, while in southern Wyoming and western Nebraska (near Mitchell and Scottsbluff), only 90 cumulative GDD were needed (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017). In a common garden study conducted in Huntley, MT, B. scoparia populations collected from six different U.S. Great Plains states showed differential emergence patterns (Kumar et al. Reference Kumar, Jha, Dille and Stahlman2018a). Populations collected from Kansas, Oklahoma, and Montana showed an early onset of emergence. In contrast, a population from New Mexico had a delayed onset of emergence but a more rapid emergence rate, while populations from North Dakota had an extended emergence period. Those populations had two to four emergence peaks between mid-April and mid-July. The researchers concluded that the differential emergence pattern of B. scoparia populations reflects the coexistence of different emergence “biotypes”; hence, there is a need to adopt more location-specific, diversified weed control tactics to manage the weed seedbank (Kumar et al. Reference Kumar, Jha, Dille and Stahlman2018a).

Very few studies have been conducted to explore the germination and emergence dynamics of HR versus herbicide-susceptible B. scoparia. Populations with resistance to ALS inhibitors (SU herbicides) from Montana had an early and a rapid germination at 4.6 to 13.2 C compared with ALS inhibitor–susceptible populations (Dyer et al. Reference Dyer, Chee and Fay1993b). The higher germination rate of ALS inhibitor–resistant B. scoparia populations was attributed to higher free levels of branched-chain amino acids (2-fold higher) compared with ALS inhibitor–susceptible populations (Dyer et al. Reference Dyer, Chee and Fay1993b). Similarly, ALS inhibitor–resistant B. scoparia populations from Kansas and North Dakota had a faster seed germination rate (12 to 70 h earlier) and final cumulative germination (100 to 300 h earlier) than susceptible populations at 8 C (Thompson et al. Reference Thompson, Thill and Shafii1994). These studies indicate that ALS inhibitor–resistant populations will most likely emerge and establish earlier than the susceptible populations, emphasizing the need for early-season weed control to manage the ALS inhibitor–resistant B. scoparia.

Seeds of a B. scoparia inbred line from Montana with cross-resistance to dicamba and fluroxypyr (df-R), had a lower final cumulative germination than the susceptible inbred line (df-S) at a majority of constant (5 to 35 C) and alternating temperatures (5/10 to 25/30 C) (Kumar and Jha Reference Kumar and Jha2016). In addition, the df-R inbred line had a delayed onset of germination relative to the df-S inbred line, especially at low temperatures (Kumar and Jha Reference Kumar and Jha2016), indicating a higher thermal requirement for germination than the df-S inbred line. This study concluded that the df-R inbred line was relatively more dormant and would potentially be more persistent in the soil seedbank than the df-S line.

Four out of seven GR populations from Montana had a lower cumulative germination and took more time to complete 50% cumulative germination under all constant and alternating temperatures evaluated compared with the glyphosate-susceptible (GS) populations (Kumar and Jha Reference Kumar and Jha2017). Those four GR populations also had a delayed germination initiation, particularly at lower temperatures (5 to 10 C constant or 5/10 C alternating). Similarly, GR B. scoparia populations from Kansas had lower total cumulative germination percentages and slower germination rates than GS populations at 15 C (Osipitan and Dille Reference Osipitan and Dille2017). More recently, Beckie et al. (Reference Beckie, Blackshaw, Leeson, Stahlman, Gaines and Johnson2018) found that seed burial depth (0 to 10 cm) had no effect on the seed viability of GR populations compared with the GS populations over time, and time to 50% and 90% loss of seed viability averaged 210 and 232 d, respectively. In that study, GR populations were also found to germinate later and had a lower cumulative germination than GS populations (Beckie et al. Reference Beckie, Blackshaw, Leeson, Stahlman, Gaines and Johnson2018). These differential germination characteristics of GR versus GS or DR versus DS populations of B. scoparia may indicate coexistence of resistance and avoidance (escaping preseeding treatments) mechanisms. The delayed and reduced germination characteristics of these HR populations may represent options for managing the weed seedbank by altering the PRE soil-residual herbicide timing or tillage timing or by shifting the crop planting dates earlier to enhance crop competitiveness (Beckie et al. Reference Beckie, Blackshaw, Leeson, Stahlman, Gaines and Johnson2018; Kumar and Jha Reference Kumar and Jha2017).

Growth and Reproduction

A majority of the studies on growth and fecundity characteristics of HR versus susceptible B. scoparia populations have been conducted under greenhouse conditions with very limited data from field studies. In a greenhouse study, chlorsulfuron-resistant and chlorsulfuron-susceptible populations from North Dakota or Kansas had similar growth rates and seed production in the absence of competition (Christoffoleti et al. Reference Christoffoleti, Westra and Moore1997; Thompson et al. Reference Thompson, Thill and Shafii1994). Similarly, in a replacement series experiment, growth characteristics of ALS inhibitor–resistant populations from Alberta and Manitoba with a single point mutation (Trp-574 or Pro-197), did not differ from the susceptible populations (Légère et al. Reference Légère, Stevenson, Beckie, Warwick, Johnson, Hrynewich and Lozinski2013).

Bassia scoparia lines derived (after three generations of recurrent selection) from a single, segregating field population (common genetic background) with cross-resistance to dicamba and fluroxypyr (df-R) had reduced plant height, plant width, primary branches, total leaf area, stem diameter, and shoot dry weight compared with the df-S line in the absence of competition (Kumar and Jha Reference Kumar and Jha2016). In this study, the df-R B. scoparia had a 39% reduction in reproductive fitness, and the 1,000-seed weight (1.6 g) was lower compared with the df-S B. scoparia (2.6 g). The replacement series indices further revealed that the df-R was less competitive than the df-S when grown in an intraspecific competition at varying mixture proportions (Kumar and Jha Reference Kumar and Jha2016). Similar results have been observed concerning the fitness penalty of a DR inbred line from Nebraska (LeClere et al. Reference LeClere, Wu, Westra and Sammons2018). The results imply a possible fitness cost endowed by the auxinic resistance trait and that the frequency of df-R individuals is likely to decline in the population when the use of auxinic herbicides is interrupted by other weed control methods (Kumar and Jha Reference Kumar and Jha2016).

Studies on the growth and reproductive fitness of GR B. scoparia have shown mixed results. In a greenhouse study, Kumar and Jha (Reference Kumar and Jha2015b) found no differences in growth and fecundity traits between the GR (with 3 to 15 copies of the EPSPS gene) and GS (single copy of the EPSPS gene) B. scoparia populations collected from a wheat–fallow field in Montana. Similarly, GR and GS populations from Kansas did not exhibit any differences in plant height, biomass accumulation, and fecundity characteristics under field conditions (Osipitan and Dille Reference Osipitan and Dille2017). These studies suggest that GR B. scoparia individuals will most likely persist in field populations even if the growers discontinue glyphosate use. However, in a recent study, Martin et al. (Reference Martin, Benedict, Sauder, Wei, Da Costa, Hall and Beckie2017) evaluated the fitness costs of EPSPS gene amplification in B. scoparia by comparing susceptible and resistant full siblings from segregating F2 populations. Some GR B. scoparia plants with high EPSPS gene copy numbers had delayed emergence, delayed flowering, and reductions in viable seed count and seed weight compared with the susceptible plants. Nevertheless, a significant amount of variation in the magnitude of fitness cost was observed among the independent F2 crosses (across genetic backgrounds) (Martin et al. Reference Martin, Benedict, Sauder, Wei, Da Costa, Hall and Beckie2017). The authors concluded that B. scoparia with increased EPSPS gene copy number may be at a competitive disadvantage in some genetic backgrounds when glyphosate use is interrupted by other weed control methods.

Management of HR Bassia scoparia

Fallow

Wheat–fallow is a predominant crop rotation in the dryland region of the U.S. Great Plains, primarily due to a limited soil moisture availability (less than 375 mm annual precipitation) for continuous cropping (Peterson and Westfall Reference Peterson and Westfall2004). In the absence of crop competition, B. scoparia poses a serious problem during the summer fallow (chemical fallow) phase of the rotation, as it depletes soil moisture, and can add a significant amount of seeds (≥250,000 seeds plant−1) to the soil seedbank (Lim et al. Reference Lim, Jha, Kumar, Leland and Jha2016). Growers often rely on herbicides for B. scoparia control in chemical fallow fields. Depending on the subsequent crop to be grown, soil-active herbicides including pendimethalin + dimethenamid, pyroxasulfone + pendimethalin, metribuzin, sulfentrazone, flumioxazin, isoxaflutole, and atrazine can be effectively used in the fall or early spring to control B. scoparia resistant to glyphosate, dicamba, and ALS inhibitors (Jha et al. Reference Jha, Kumar, Garcia and Reichard2015a; Kumar and Jha Reference Kumar and Jha2015a; Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018). Paraquat alone or in combination with linuron, metribuzin, or atrazine, saflufenacil + linuron, and diflufenzopyr + dicamba + 2,4-D can all be effectively used (recommended rate and timing) as POST burndown treatments in chemical fallow for controlling B. scoparia resistant to ALS inhibitors and glyphosate (Kumar and Jha Reference Kumar and Jha2015a); however, the options will be very limited with the presence of glyphosate, ALS inhibitors, and dicamba multiply resistant B. scoparia.

Wheat

Bassia scoparia is a poor competitor in a well-established wheat canopy; therefore, it is less challenging to manage in wheat, especially in winter wheat that attains vigorous growth by the time B. scoparia begins to emerge. Although there are very few PRE herbicides registered in wheat, POST herbicides with multiple sites of action, including bromoxynil + fluroxypyr, bromoxynil + pyrasulfotole, or bromoxynil + MCPA at the full labeled rates can provide up to 95% control of GR, ALS inhibitor–resistant, or DR B. scoparia (8- to 10-cm tall) in wheat (Kumar and Jha Reference Kumar and Jha2015a; Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018). Kumar and Jha (Reference Kumar and Jha2015d) reported that paraquat + atrazine, paraquat + linuron, and paraquat + metribuzin applied at the early bloom stage of B. scoparia were very effective for late-season control and seed prevention in postharvest wheat stubble.

Corn and Grain Sorghum

There are relatively more options for HR B. scoparia control with PRE soil-residual herbicides compared with POST herbicides in corn. PRE herbicides, including pyroxasulfone + atrazine, dicamba + pendimethalin, pyroxasulfone or dimethenamid-P + pendimethalin, flumioxazin + pyroxasulfone, saflufenacil + dimethenamid-P + pendimethalin, and isoxaflutole, can provide >90% residual control (8 wk after treatment) of B. scoparia populations resistant to ALS inhibitors, dicamba, or glyphosate in corn (Kumar and Jha Reference Kumar and Jha2015a; Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018). These herbicides can be tank mixed with paraquat or saflufenacil to obtain preplant burndown GR B. scoparia control in corn. Among POST herbicide options, dicamba + diflufenzopyr and tembotrione, topramezone, or mesotrione + atrazine would provide effective control of GR and ALS inhibitor–resistant B. scoparia populations in corn (Kumar and Jha Reference Kumar and Jha2015a; Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018; Tonks and Westra Reference Tonks and Westra1997). However, B. scoparia resistant to glyphosate, ALS inhibitors, PSII inhibitors, and dicamba will be quite difficult to manage with POST-only herbicide programs, which are limited to 4-hydroxphenylpyruvate dioxygenase (HPPD) inhibitors. Furthermore, atrazine and HPPD inhibitors cannot be used in corn rotated often with sugar beet or dry beans (Phaseolus spp.) (carryover concerns) in the Northern Great Plains.

Soybean

Before evolution of glyphosate resistance, B. scoparia populations resistant to ALS and PSII inhibitors were effectively managed by glyphosate in GR soybean. Evolution of GR B. scoparia in soybean has been reported from four U.S. states (Heap Reference Heap2018). To manage B. scoparia resistant to ALS inhibitors and glyphosate in soybean, it is crucial to start clean with a preplant burndown herbicide program using saflufenacil, glufosinate, or paraquat (Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018). To obtain 6 to 8 wk of residual control, PRE herbicides such as pyroxasulfone + flumioxazin, metribuzin, sulfentrazone, saflufenacil + dimethenamid-P + pendimethalin, dimethenamid-P or pyroxasulfone + pendimethalin should be included with the preplant burndown programs (Kumar and Jha Reference Kumar and Jha2015c). Among POST herbicides, protoporphyrinogen oxidase (PPO) inhibitors such as acifluorfen, lactofen, and fomesafen can provide 70% to 85% control of glyphosate and ALS inhibitor–resistant B. scoparia (Jha et al. Reference Jha, Varanasi, Kumar and Leland2014; Kumar et al. Reference Kumar, Jha and Reichard2014; Thompson et al. Reference Thompson, Peterson, Fick, Currie, Kumar and Slocombe2018); however, control with PPO inhibitors could be variable depending on B. scoparia size and environmental conditions (PJ, personal observation). Therefore, POST treatments of PPO inhibitor are recommended with the PRE soil-residual herbicides to obtain season-long control of GR and ALS inhibitor–resistant B. scoparia in soybean.

Sugar Beet

Due to the early emergence and high competitive ability of B. scoparia, its control in sugar beet production has always been a challenge (Kniss 2010; Kumar and Jha Reference Kumar and Jha2015a). After its commercialization in 2008, GR sugar beet has been rapidly adopted by growers and comprises >98% of the total sugar beet production in the region (Kniss Reference Kniss2010). In conventional (non-GR) sugar beet, growers had to make three to five herbicide applications in sugar beet that often resulted in unacceptable crop injury (Kniss Reference Kniss2010; Morishita Reference Morishita2018). In addition, non-GR sugar beet required one to three cultivations as well as hand weeding. Among POST herbicide options including triflusulfuron, desmedipham, phenmedipham, and clopyralid, triflusulfuron was the only effective herbicide for B. scoparia control in non-GR sugar beet; nevertheless, this herbicide was rendered ineffective as ALS inhibitor–resistant B. scoparia populations became widespread in sugar beet–growing areas of the U.S. Great Plains. Glyphosate provided excellent broad-spectrum weed control, including control of ALS inhibitor–resistant B. scoparia populations. Growers often rely on multiple (two to four) POST glyphosate applications for weed control in GR sugar beet fields (Kniss Reference Kniss2010; Kumar and Jha Reference Kumar and Jha2015c; Morishita Reference Morishita2018). This has enhanced selection pressure for evolution of GR weeds in sugar beet, with B. scoparia being the first weed to evolve resistance to glyphosate in sugar beet (Heap Reference Heap2018). Some of the soil-active herbicides that are labeled in sugar beet, including ethofumesate, dimethenamid-P, EPTC, S-metolachlor, and trifiuralin, are not very effective on B. scoparia and cannot be relied upon alone (Morishita Reference Morishita2018). Therefore, the evolution of GR B. scoparia in sugar beet fields in Montana, Wyoming, Colorado, Nebraska, Idaho, and Oregon has raised concerns among growers over the long-term sustainability of sugar beet production (Gaines et al. Reference Gaines, Barker, Patterson, Westra, Westra, Wilson, Jha, Kumar and Kniss2016; Kumar et al. Reference Kumar, Felix, Morishita and Jha2018b; Morishita Reference Morishita2018). As GR B. scoparia spreads within sugar beet–growing regions, there will simply not be any herbicide registered for sugar beet that will control this weed. Therefore, diverse ecological strategies need to be urgently implemented in sugar beet–based crop rotations.

Multiple Herbicide–Resistant Trait Technologies

Crop cultivars with “stacked” herbicide resistance traits have recently been commercialized for controlling GR and ALS inhibitor–resistant weeds. Few of those include DR and 2,4-D-resistant weed management system in soybean, corn, or cotton (Gossypium hirsutum L.). The Roundup Ready® 2 Xtend (Monsanto Company, 800 N. Lindbergh Blvd, St. Louis, MI 63167) system provides crop tolerance to POST applications of both glyphosate and dicamba. This technology in soybean will allow the use of dicamba (Xtendimax® [Monsanto Company] or Engenia® [BASF Corporation, 26 Davis Drive, Research Triangle Park, NC 27709], or Fexapan [E. I. du Pont de Nemours and Company, Chestnut Run Plaza, 974 Center Road, Wilmington, DE 19805]) in crop to control GR and PSII and ALS inhibitor–resistant weed populations. Several studies have reported excellent control of GR weeds with dicamba alone or in combination with glyphosate (Cahoon et al. Reference Cahoon, York, Jordan, Everman, Seagroves, Culpepper and Eure2015; Eubank et al. Reference Eubank, Poston, Nandula, Koger, Shaw and Reynolds2008; Everitt and Keeling Reference Everitt and Keeling2007; Spaunhorst et al. 2014; Vink et al. Reference Vink, Soltani, Robinson, Tardif, Lawton and Sikkema2012). These stacked-trait crops will provide new options with existing herbicides, but will not be the total weed management solution, because B. scoparia has already evolved resistance to dicamba in several states in the U.S. Great Plains (Heap Reference Heap2018). Furthermore, the utility of dicamba and 2,4-D on large landscapes needs to be carefully examined because of potential off-target movement of these herbicides via physical or vapor drift, which can potentially cause damage to other sensitive crops and vegetation (Bish and Bradley Reference Bish and Bradley2017; Culpepper et al. Reference Culpepper, Sosnoskie, Shugart, Leifheit, Curry and Gray2018; Everitt and Keeling Reference Everitt and Keeling2009; Johnson et al. Reference Johnson, Fisher, Jordan, Edmisten, Stewart and York2012).

Nonchemical Approaches

Managing HR B. scoparia will require the use of mechanical and ecologically based approaches, such as tillage, increased crop competition, diverse crop rotations, and cover crops to manipulate B. scoparia seedbanks (Ball Reference Ball1992; Davis et al. Reference Davis, Cardina, Forcella, Johnson, Kegode, Lindquist, Luschei, Renner, Sprague and Williams2005; Kumar et al. Reference Kumar, Jha, Dille and Stahlman2018a). Among all these methods, the selection of improved crop rotations can potentially be the most effective cultural practice for managing B. scoparia seedbanks (Hume et al. Reference Hume, Tessier and Dyck1991; Johnson and Coble Reference Johnson and Coble1986; Kumar et al. Reference Kumar, Jha, Dille and Stahlman2018a). Selecting the most competitive crops such as cereals or corn in the rotation will be crucial in reducing seed inputs of B. scoparia. For instance, a 3-yr field study on the impact of crop canopy on B. scoparia seed reductions found that B. scoparia produced an average of 26,000 seeds plant−1 in fallow compared with only 134 and 104 seeds plant−1 in wheat and corn, respectively (Nyamusamba Reference Nyamusamba2014). The Bassia scoparia seedbank in the top 15-cm soil depth declined from 10 to 0 seed m−2 after 3 yr of continuous corn, whereas 500 and 800 seeds m−2 were observed after 3 yr of continuous pinto bean (Phaseolus vulgaris L.)/sugar beet –sugar beet–corn rotation, respectively (Ball Reference Ball1992). Those soil seedbank changes were mainly attributed to the competitive ability of the crop (corn being more competitive than pinto bean or sugar beet) and herbicide use pattern in each cropping sequence (Ball Reference Ball1992). It is unlikely that crop rotation itself will alter the R:S ratio of the weed seedbank (Davis et al. Reference Davis, Gibson, Bauman, Weller and Johnson2009). However, a well-designed crop rotation comprising winter cereals or perennial forages may provide an opportunity to reduce the overall density of weed seedlings being exposed to a herbicide, thereby delaying or preventing a significant increase in the R:S ratio. A diverse crop rotation could also reduce herbicide selection pressure by stimulating germination when nonchemical control practices can be used, for example, stale seedbed especially in late-planted crops such as dry beans in the irrigated regions of the U.S. Great Plains. These factors could be more important for a weed like B. scoparia with a short-lived seed, where R individuals could be reduced dramatically in just a few years (Jha, Kniss, and Lawrence, unpublished data).

No-till systems favor the germination of small-seeded weeds, including B. scoparia, because under no-till conditions, a majority of weed seeds lies on or near the soil surface where optimum germination conditions prevail (Anderson et al. Reference Anderson, Tanaka, Black and Schweizer1998; Schwinghamer and Van Acker Reference Schwinghamer and Van Acker2008). Bassia scoparia has become the most troublesome weed species in no-till production systems of the Great Plains (Heap Reference Heap2018). In a 3-yr study, B. scoparia seedbank declined more rapidly after 3 yr of moldboard plowing as compared with chisel plowing (Ball Reference Ball1992). The more rapid seedbank turnover in no-till versus conventional-till systems may expose a greater proportion of the weed seedbank to herbicides. This interaction with increased herbicide use may result in an increased risk of selection of rare resistance alleles in the weed population under no-till systems (Beckie et al. Reference Beckie, Leeson, Thomas, Brenzil, Holzgang, Lozinski and Shirriff2008). In a survey conducted on the risk assessment of herbicide resistance, 21% of the crop area with intensive tillage did not receive any herbicide application, whereas 99% of the crop area with no-tillage received at least one herbicide application. Consequently, the risk of evolution of weed resistance would be higher in no-till than conventional tillage systems (Beckie et al. Reference Beckie, Leeson, Thomas, Brenzil, Holzgang, Lozinski and Shirriff2008).

Cover crops suppress weeds by reducing early-season weed densities, growth, and seed production because of direct competition from the living cover crop biomass or from the plant residue after the cover crop is terminated (Al-Khatib et al. Reference Al-Khatib, Libbey and Boydston1997; Petrosino et al. Reference Petrosino, Dille, Holman and Roozeboom2015; Teasdale et al. Reference Teasdale, Pillai and Collins2005). Cover crop residues can trap weed seeds, prevent soil–seed contact required for germination, and provide optimum habitat for increased weed seed predation compared with the bare soil, thereby influencing the persistence of weed seeds in the soil (Cardina and Sparrow Reference Cardina and Sparrow1996; Teasdale et al. Reference Teasdale, Pillai and Collins2005). Bassia scoparia density was reduced by 78% to 94% and the biomass was reduced by 98% in fall-planted cover crops, such as Austrian winter pea (Pisum sativum L.), hairy vetch (Vicia villosa Roth), winter triticale (Triticosecale rimpaui C. Yen & J. L. Yang), and mixtures of hairy vetch and winter triticale and of Austrian winter pea and winter triticale compared with the density and biomass in fallow (Petrosino Reference Petrosino2010; Petrosino et al. Reference Petrosino, Dille, Holman and Roozeboom2015). However, spring-planted cover crops such as lentil (Lens culinaris Medik.), pea, and mixtures of lentil/triticale and pea/triticale did not affect B. scoparia density and biomass compared with fallow plots in the same study (Petrosino et al. Reference Petrosino, Dille, Holman and Roozeboom2015). In a greenhouse study, adding white mustard (Sinapis alba L.) plant residue to the soil at 20 g per 400 g air-dried soil reduced B. scoparia emergence by 54% (Al-Khatib et al. Reference Al-Khatib, Libbey and Boydston1997). In field experiments, 90% to 99% reductions in early- and late-season B. scoparia densities were observed with a yellow sweetclover [Melilotus officinalis (L.) Lam.] green manure compared with fallow plots (Blackshaw et al. Reference Blackshaw, Moyer, Doram and Boswall2001). This strategy would potentially reduce reliance on herbicide inputs and allow competitive crops to be established before B. scoparia emergence. However, research on quantifying the effect of cover crops on B. scoparia emergence patterns and seedbank dynamics is lacking.

The efficacy and economics of harvest weed seed control (HWSC) technologies (reviewed in Walsh et al. Reference Walsh, Newman and Powles2013) in managing HR B. scoparia populations need to be evaluated in the North American Great Plains cropping systems. As a non-herbicidal weed management tool, HWSC can be an important component of an integrated weed management program to reduce weed seed inputs and reduce the reliance on herbicides, thereby delaying the evolution of HR weeds (Walsh and Powles Reference Walsh and Powles2014). HWSC methods would hold great promise for managing B. scoparia, which can retain 99.8% of the seeds at wheat harvest in the North American Great Plains (Burton et al. Reference Burton, Beckie, Willenborg, Shirtliffe, Schoenau and Johnson2017). A high level of seed destruction (99.8%) of B. scopariawas obtained using an Harrington Seed Destructor cage mill in barley (Hordeum vulgare L.) chaff (Tidemann et al. Reference Tidemann, Hall, Harker and Beckie2017). Bassia scoparia has an indeterminate growth habit and plants are immature at the time of cereal harvest (Kumar and Jha Reference Kumar and Jha2015a). To maximize the efficiency of HWSC, harvest height should be lower than the current cutting height of ∼15 to 20 cm to revent regrowth of the portion of the plant that is left behind and that can potentially add ~100,000 seeds m−2 if not controlled postharvest (Burton et al. Reference Burton, Beckie, Willenborg, Shirtliffe, Schoenau and Johnson2017; Kumar and Jha Reference Kumar and Jha2015a). In addition, the plant can disperse those seeds long distances through the tumbling mechanism in the fall, ensuring rapid movement of resistance alleles (Beckie et al. Reference Beckie, Blackshaw, Hall and Johnson2016).

The ideal strategy for mitigating HR B. scoparia should embrace a “zero-seed threshold” approach at a cropping-systems level. Therefore, the long-term herbicide-resistance management programs should encourage the use of more diversified crop rotations, tillage, cover crops, and HWSC. The goal should be to identify ecological trends in B. scoparia population dynamics as influenced by multitactic cultural practices, which can be recommended to producers.

Precision Weed Management

In the past few decades, sensor-based technologies have gained wide-scale attention in agriculture. Major advancements in automation include the development of remote-sensing technologies, sophisticated cameras, robots, and unmanned aerial vehicles (UAVs). Site-specific weed management using these automated, sensor-based technologies hold promise. These technological advances can also help in identification of HR weed populations. For instance, GR and GS Palmer amaranth (Amaranthus palmeri S. Watson) populations were distinguished using differences in reflectance across the near-UV, visible, and near-IR spectrum (Reddy et al. Reference Reddy, Huang, Lee, Nandula, Fletcher, Thomson and Zhao2014). Further work using hyperspectral reflectance properties has shown the ability to differentiate between GS and GR Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] populations and between GR and DR B. scoparia from susceptible populations (Lee et al. Reference Lee, Huang, Nandula and Reddy2014; Nugent et al. Reference Nugent, Shaw, Jha, Scherrer, Donelick and Kumar2018). These optical sensor–based technologies along with automated UAVs have broader implications for wide-scale field mapping and early detection of HR weed populations, including HR B. scoparia (Nugent et al. Reference Nugent, Shaw, Jha, Scherrer, Donelick and Kumar2018).

Light-activated sensor-controlled (LASC) or Weed Seeker® sprayers have shown tremendous success in site-specific weed control and in reducing herbicide costs by 30% to 70% in fallow (Ahrens Reference Ahrens1994; Biller Reference Biller1998; Blackshaw et al. Reference Blackshaw, Molnar and Linidwall1998; Jha et al. Reference Jha, Varanasi, Kumar and Leland2014; Riar et al. Reference Riar, Ball, Yenish and Burke2011). In addition, the LASC sprayer has shown 25% reductions in herbicide cost for selective weed control in cereals and pea compared with a broadcast application (Dammer and Wartenberg Reference Dammer and Wartenberg2007). Up to 70% reductions in herbicide use have been achieved with the LASC sprayer compared with conventional broadcast applications in soybean (Hanks and Beck Reference Hanks and Beck1998).

Summary and Future Directions

Several factors, including agronomic practices and the unique biological characteristics of B. scoparia, make control of this weed species challenging. Adoption of conservation tillage systems favor rapid emergence of small-seeded weeds like B. scoparia from the soil surface (Dille et al. Reference Dille, Stahlman, Du, Geier, Riffel, Currie, Wilson, Sbatella, Westra, Kniss, Moechnig and Cole2017). Heavy reliance on herbicides in no-till cropping systems, especially chemical fallow-based and frequent use of glyphosate in GR crops, coupled with a high genetic diversity, facilitated evolution of multiple-herbicide resistance in B. scoparia. In addition, B. scoparia was found to evolve resistance to the same chemistry of herbicide via multiple mechanisms (e.g., DR B. scoparia). This may warrant diversified tactics for managing this troublesome weed. Our research on DR B. scoparia indicates that intensive cropping and weed management practices favor the shift in the population to late-emerging weed cohorts and a common selection of herbicide-resistance and avoidance mechanisms (Kumar and Jha Reference Kumar and Jha2016, Reference Kumar and Jha2017). There is a research gap in understanding the impact of ecologically based weed management strategies on the seedbank dynamics of B. scoparia. In this context, long-term field studies in Montana, Wyoming, and Nebraska are underway to develop a bioeconomic model to understand the effect of diverse cultural and mechanical strategies on mitigating HR B. scoparia seedbanks. In another study across the three-state region, a hydrothermal time model will be developed to predict regional B. scoparia emergence patterns and to test the impact of non-herbicide management strategies (cover crops, stale seedbed, and improved crop rotations) that have a high likelihood of decreasing B. scoparia seedbanks, thereby reducing reliance on herbicides.

The genetic plasticity and epigenetic adaptability of B. scoparia in response to climate change and biotic or abiotic stresses imposed by crop management practices need to be investigated. Whole-genome sequencing of B. scoparia will help in elucidating the molecular and genetic basis of stress adaptability of this species, including rapid evolution of resistance to multiple herbicides (T Gaines, personal communication). New, stacked herbicide-tolerant crop technologies may aid in managing HR B. scoparia in the short term. However, with the presence of B. scoparia populations with resistance to four herbicide sites of action, there is an urgent need to develop ecological weed management strategies at a cropping-system level based on an improved understanding of the biology, plasticity, and genetic diversity of this weed. Modeling the effectiveness of multitactic weed management strategies at different spatial scales (landscape levels) to delay or preclude herbicide resistance in B. scoparia will aid in attaining cooperative management goals.

Author ORCID

Vipan Kumar, https://orcid.org/0000-0002-8301-5878.

Acknowledgments

This work was jointly supported by the USDA National Institute of Food and Agriculture (Hatch Projects MON00658 and KS534) and USDA Western SARE (Project No. EW16-029, Montana State University Subaward No. 150893-00001-207). This publication is contribution no. 18-621-J from the Kansas Agricultural Experiment Station, Manhattan, KS. No conflicts of interest have been declared.

References

Ahrens, WH (1994) Relative costs of a weed-activated versus conventional sprayer in northern Great Plains fallow. Weed Technol 8:5057 Google Scholar
Al-Khatib, K, Libbey, C, Boydston, R (1997) Weed suppression with Brassica green manure crops in green pea. Weed Sci 45:439445 Google Scholar
Anderson, RL, Nielsen, DC (1996) Emergence pattern of five weeds in the central Great Plains. Weed Technol 10:744749 Google Scholar
Anderson, RL, Tanaka, DL, Black, AL, Schweizer, EE (1998) Weed community and species response to crop rotation, tillage, and nitrogen. Weed Technol 12:531536 Google Scholar
Baker, DV, Withrow, JR, Brown, CS, Beck, KG (2010) Tumbling: use of diffuse knapweed (Centaurea diffusa) to examine an understudied dispersal mechanism. Invasive Plant Sci Manag 3:301309 Google Scholar
Ball, DA (1992) Weed seedbank response to tillage, herbicides, and crop rotation sequence. Weed Sci 40:654659 Google Scholar
Ball, DA, Cudney, D, Dewey, SA, Elmore, CL, Lym, RG, Morishita, DW, Parker, R, Swan, DG, Whitson, TD, Zollinger, RK (2000) Weeds of The West. 9th ed. Newark, CA: Western Society of Weed Science. Pp 270271 Google Scholar
Bandeen, JD, Stephenson, GR, Cowett, ER (1982) Discovery and distribution of herbicide-resistant weeds in North America. Pages 930 in LeBaron HM, Gressel J, eds. Herbicide Resistance in Plants. New York: Wiley Google Scholar
Beckie, H, Blackshaw, R, Hall, L, Johnson, E (2016) Pollen- and seed-mediated gene flow in kochia (Kochia scoparia). Weed Sci 64:624633 Google Scholar
Beckie, HJ, Blackshaw, RE, Leeson, JY, Stahlman, PW, Gaines, TA, Johnson, EN (2018) Seedbank persistence, germination and early growth of glyphosate-resistant Kochia scoparia . Weed Res 58:177187 Google Scholar
Beckie, HJ, Blackshaw, RE, Low, R, Hall, LM, Sauder, CA, Martin, S, Brandt, EN, Shirriff, SW (2013) Glyphosate- and acetolactate synthase inhibitor-resistant kochia (Kochia scoparia) in western Canada. Weed Sci 61:310318 Google Scholar
Beckie, HJ, Hall, LM, Tardif, FJ (2001) Herbicide resistance in Canada—where are we today? Pages 136 in Blackshaw RE, Hall LM, eds. Integrated Weed Management: Explore the Potential. SainteAnne-de-Bellevue, QC, Canada: Expert Committee on Weeds Google Scholar
Beckie, HJ, Leeson, JY, Thomas, AG, Brenzil, CA, Holzgang, G, Lozinski, C, Shirriff, S (2008) Weed resistance monitoring in the Canadian Prairies. Weed Technol 22:530543 Google Scholar
Beckie, HJ, Warwick, SI, Sauder, CA, Lozinski, C, Shirriff, S (2011) Occurrence and molecular characterization of acetolactate synthase (ALS) inhibitor–resistant kochia (Kochia scoparia) in western Canada. Weed Technol 25:170175 Google Scholar
Biller, RH (1998) Reduced input of herbicides by use of optoelectronic sensors. J Agric Eng Res 71: 357362 Google Scholar
Bish, MD, Bradley, KW (2017) Survey of Missouri pesticide applicator practices, knowledge, and perceptions. Weed Technol 31:165177 Google Scholar
Blackshaw, RE, Molnar, LJ, Linidwall, CW (1998) Merits of a weed-sensing sprayer to control weeds in conservation fallow and cropping systems. Weed Sci 46:120126 Google Scholar
Blackshaw, RE, Moyer, JR, Doram, RC, Boswall, AL (2001) Yellow sweetclover, green manure, and its residues effectively suppress weeds during fallow. Weed Sci 49:406413 Google Scholar
Brachtenbach, DA (2015) Kochia scoparia Response to Dicamba and Effective Management Practices for Soybeans. MS thesis. Manhattan, KS: Kansas State University. 53 pGoogle Scholar
Burton, NR, Beckie, HJ, Willenborg, CJ, Shirtliffe, SJ, Schoenau, JJ, Johnson, EN (2017) Seed shatter of six economically important weed species in producer fields in Saskatchewan. Can J Plant Sci 97:266276 Google Scholar
Cahoon, CW, York, AC, Jordan, DL, Everman, WJ, Seagroves, RW, Culpepper, AS, Eure, PM (2015) Palmer amaranth (Amaranthus palmeri) management in dicamba-resistant cotton. Weed Technol 29:758770 Google Scholar
Cardina, J, Sparrow, DH (1996) A comparison of methods to predict weed seedling populations from the soil seedbank. Weed Sci 44:4651 Google Scholar
Chodova, D, Mikulka, J (2000) Resistance to imazapyr and cross resistance to selected sulfonylurea herbicides in kochia (Kochia scoparia S-L.). Rostl Vyroba 46:4954 Google Scholar
Christoffoleti, PJ, Westra, PB, Moore, F (1997) Growth analysis of sulfonylurea-resistant and -susceptible kochia (Kochia scoparia). Weed Sci 45:691695 Google Scholar
Cranston, HJ, Kern, AJ, Hackett, JL, Miller, EK, Maxwell, BD, Dyer, WE (2001) Dicamba resistance in kochia. Weed Sci 49:164170 Google Scholar
Crespo, RJ, Bernards, ML, Sbatella, GM, Kruger, GR, Lee, DJ, Wilson, RG (2014) Response of Nebraska kochia (Kochia scoparia) accessions to dicamba. Weed Technol 28:151162 Google Scholar
Culpepper, AS, Sosnoskie, LM, Shugart, J, Leifheit, N, Curry, M, Gray, T (2018) Effects of low-dose applications of 2,4-D and dicamba on watermelon. Weed Technol 32:267272 Google Scholar
Dammer, KH, Wartenberg, G (2007) Sensor-based weed detection and application of variable herbicide rates in real time. Crop Prot 26:270277 Google Scholar
Dao, TTH, Linthorst, HJM, Verpoorte, R (2011) Chalcone synthase and its functions in plant resistance. Phytochem Rev 10:397 Google Scholar
Davis, AS, Cardina, J, Forcella, F, Johnson, GA, Kegode, G, Lindquist, JL, Luschei, EC, Renner, KA, Sprague, CL, Williams, MM II (2005) Environmental factors affecting seed persistence of annual weeds across the U.S. corn belt. Weed Sci 53:860868 Google Scholar
Davis, VM, Gibson, KD, Bauman, TT, Weller, SC, Johnson, WG (2009). Influence of weed management practices and crop rotation on glyphosate-resistant horseweed (Conyza canadensis) population dynamics and crop yield-years III and IV. Weed Sci 57:417426 Google Scholar
Dille, JA, Stahlman, PW, Du, J, Geier, PW, Riffel, JD, Currie, RS, Wilson, RG, Sbatella, GM, Westra, P, Kniss, AR, Moechnig, MJ, Cole, RM (2017) Kochia emergence profiles across the central Great Plains. Weed Sci 65:614625 Google Scholar
Durgan, BR, Dexter, AG, Miller, SD (1990) Kochia (Kochia scoparia) interference in sunflower (Helianthus annuus). Weed Technol 4:5256 Google Scholar
Dyer, WE, Birdsall, JK, Zwaan, AM (1993a) Phylogenetic analysis of Kochia scoparia (L.) Schrad. populations. Weed Sci Soc Am Abstr 33:179 Google Scholar
Dyer, WE, Chee, PW, Fay, PK (1993b) Rapid germination of sulfonylurea-resistant Kochia scoparia (L.) Schrad. accession is associated with elevated seed levels of branched chain amino acids. Weed Sci 41:1822 Google Scholar
Dyer, WE, Goss, GA, Buck, P (2002) Auxin-mediated responses in dicamba-resistant Kochia scoparia . Page 29 in Proceedings of the Western Society of Weed Science. Salt Lake City, UT: Western Society of Weed Science Google Scholar
Eberlein, CV, Fore, ZQ (1984) Kochia biology. Weeds Today 15:57 Google Scholar
Eubank, TW, Poston, DH, Nandula, VK, Koger, CH, Shaw, DR, Reynolds, DB (2008) Glyphosate-resistant horseweed (Conyza canadensis) control using glyphosate-, paraquat-, and glufosinate-based herbicide programs. Weed Technol 22:1621 Google Scholar
Everitt, JD, Keeling, JW (2007) Weed control and cotton (Gossypium hirsutum) response to preplant applications of dicamba, 2,4-d, and diflufenzopyr plus dicamba. Weed Technol 21:506510 Google Scholar
Everitt, JD, Keeling, JW (2009) Cotton growth and yield response to simulated 2,4-D and dicamba drift. Weed Technol 23:503506 Google Scholar
Fenster, CR, Wicks, GA (1982) Fallow systems for winter wheat in western Nebraska. Agron J 74:913 Google Scholar
Foes, MJ, Liu, L, Vigue, G, Stoller, EW, Wax, LM, Tranel, PJ (1999) A kochia (Kochia scoparia) biotype resistant to triazine and ALS-inhibiting herbicides. Weed Sci 47:2027 Google Scholar
Forcella, F (1985) Spread of kochia in the northwestern United States. Weeds Today 16(4): 46 Google Scholar
Frankton, C, Mulligan, GA (1987) Weeds of Canada. Ottawa, ON, Canada: Agriculture Canada Publ 948. 217 p Google Scholar
Friesen, LF, Beckie, HJ, Warwick, SI, Van Acker, RC (2009) The biology of Canadian weeds. 138. Kochia scoparia (L.) Schrad. Can J Plant Sci 89:141167 Google Scholar
Friesen, LF, Mayert, TSH, Morrison, IN (1990a) Control of Chlorsulfuron-Resistant Kochia in Spring Wheat. Expert Committee on Weeds (West. Sect.) Res. Rep. 467 pGoogle Scholar
Friesen, LF, Mayert, TSH, Morrison, IN (1990b) Control of Sulfonylurea-Susceptible Kochia at Two Growth Stages in Spring Wheat. Expert Committee on Weeds (West. Sect.) Res. Rep. 468 p Google Scholar
Friesen, LF, Mayert, TSH, Morrison, IN (1990c) Response of Chlorsulfuron-Resistant Kochia to Post-emergence Sulfonylurea Herbicides in Spring Wheat. Expert Committee on Weeds (West. Sect.) Res. Rep. 467 p Google Scholar
Friesen, LF, Mayert, TSH, Morrison, IN (1991a) Control of Chlorsulfuron-Resistant Kochia in Spring Wheat (Roblin). Expert Committee on Weeds (West. Sect.) Res. Rep. 822 p Google Scholar
Friesen, LF, Mayert, TSH, Morrison, IN (1991b) Control of Chlorsulfuron-Resistant Kochia in spring Wheat (Roblin) with Growth Regulator Herbicides. Expert Committee on Weeds (West. Sect.) Res. Rep. 822 p Google Scholar
Friesen, LF, Mayer, TSH, Morrison, IN (1991c) Response of Chlorsulfuron-Resistant Kochia to Post-emergence Sulfonylurea Herbicides in Spring Wheat (Roblin). Expert Committee on Weeds (West. Sect.) Res. Rep. 823 p Google Scholar
Gaines, TA, Barker, AL, Patterson, EL, Westra, P, Westra, EP, Wilson, RG, Jha, P, Kumar, V, Kniss, AR (2016) EPSPS gene copy number and whole-plant glyphosate resistance level in Kochia scoparia . PLoS ONE 11:e0168295 Google Scholar
Georgia, AE (1914) A Manual of Weeds. New York: Macmillan. 593 p Google Scholar
Godar, AS, Stahlman, PW, Jugulam, M, Dille, JA (2015) Glyphosate-resistant kochia (Kochia scoparia) in Kansas: EPSPS gene copy number in relation to resistance levels. Weed Sci 63:587595 Google Scholar
Goss, GA, Dyer, WE (2003) Physiological characterization of auxinic herbicide-resistant biotypes of kochia (Kochia scoparia). Weed Sci 51:839844 Google Scholar
Grossman, K (2010) Auxin herbicides: current status of mechanism and mode of action. Pest Manag Sci 66:113120 Google Scholar
Guilfoyle, T (2007) Sticking with auxin. Nature 446:621622 Google Scholar
Guttieri, MJ, Eberlein, CV, Thill, DC (1995) Diverse mutations in the acetolactate synthase gene confer chlorsulfuron resistance in kochia (Kochia scoparia) biotypes. Weed Sci 43:175178 Google Scholar
Hall, LM, Beckie, HJ, Low, R, Shirriff, SW, Blackshaw, RE, Kimmel, N, Neeser, C (2014) Survey of glyphosate-resistant kochia (Kochia scoparia L. Schrad.) in Alberta. Can J Plant Sci 94:127130 Google Scholar
Hanks, JE, Beck, JL (1998) Sensor-controlled hooded sprayer for row crops. Weed Technol 12:308314 Google Scholar
Heap, I (2018). The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: June 10, 2018 Google Scholar
Hume, L, Tessier, S, Dyck, FB (1991) Tillage and rotation influences on weed community composition in wheat (Triticum aestivum L.) in southwestern Saskatchewan. Can J Plant Sci 71:783789 Google Scholar
Jha, P, Kumar, V, Garcia, J, Reichard, N (2015a) Tank mixing pendimethalin with pyroxasulfone and chloroacetamide herbicides enhances in-season residual weed control in corn. Weed Technol 29:198206 Google Scholar
Jha, P, Kumar, V, Lim, CA (2015b) Variable response of kochia [Kochia scoparia (L.) Schrad.] to auxinic herbicides dicamba and fluroxypyr in Montana. Can J Plant Sci 95:965972 Google Scholar
Jha, P, Varanasi, A, Kumar, V, Leland, S (2014) Light activated sensor controlled sprayer (Weed Seeker®) for cost-effective weed control in post-harvest wheat stubble. Page 18 in Proceedings of the Western Society of Weed Science. Colorado Springs, CO: Western Society of Weed Science Google Scholar
Johnson, CW, Coble, HD (1986) Crop rotation and herbicide effects on the population dynamics of annual grasses. Weed Sci 34:452456 Google Scholar
Johnson, VA, Fisher, LR, Jordan, DL, Edmisten, KE, Stewart, AM, York, AC (2012) Cotton, peanut, and soybean response to sublethal rates of dicamba, glufosinate, and 2,4-D. Weed Technol 26:195206 Google Scholar
Jugulam, M, Niehues, K, Godar, AS, Koo, D-H, Danilova, T, Friebe, B, Sehgal, S, Varanasi, VK, Wiersma, AT, Westra, P, Stahlman, PW, Gill, BS (2014) Tandem amplification of a chromosomal segment harboring EPSPS locus confers glyphosate resistance in Kochia scoparia . Plant Physiol 166:12001207 Google Scholar
Kern, AJ, Chaverra, ME, Cranston, HJ, Dyer, WE (2005) Dicamba-responsive genes in herbicide-resistant and susceptible biotypes of kochia (Kochia scoparia). Weed Sci 53:139145 Google Scholar
Kniss, AR (2010) Comparison of conventional and glyphosate-resistant sugarbeet the year of commercial introduction in Wyoming. J Sugarbeet Res 47:127134 Google Scholar
Kumar, V, Felix, J, Morishita, D, Jha, P (2018b) Confirmation of glyphosate-resistant kochia (Kochia scoparia) from sugar beet fields in Idaho and Oregon. Weed Technol 32:2733 Google Scholar
Kumar, V, Jha, P (2015a) Effective preemergence and postemergence herbicide programs for kochia control. Weed Technol 29:2434 Google Scholar
Kumar, V, Jha, P (2015b) Growth and reproduction of glyphosate-resistant and susceptible populations of Kochia scoparia . PLoS ONE 11:e0147779 Google Scholar
Kumar, V, Jha, P (2015c) Influence of glyphosate timing on Kochia scoparia demographics in glyphosate-resistant sugar beet. Crop Prot 76:3945 Google Scholar
Kumar, V, Jha, P (2015d) Influence of herbicides applied postharvest in wheat stubble on control, fecundity, and progeny fitness of Kochia scoparia in the US Great Plains. Crop Prot 71:144149 Google Scholar
Kumar, V, Jha, P (2016) Differences in germination, growth, and fecundity characteristics of dicamba-fluroxypyr-resistant and susceptible Kochia scoparia . PLoS ONE 11:e0161533 Google Scholar
Kumar, V, Jha, P (2017) Effect of temperature on germination characteristics of glyphosate-resistant and glyphosate-susceptible kochia (Kochia scoparia). Weed Sci 65:361370 Google Scholar
Kumar, V, Jha, P, Dille, JA, Stahlman, PW (2018a) Emergence dynamics of kochia (Kochia scoparia) populations from the U.S. Great Plains: a multi-site-year study. Weed Sci 66:2535 Google Scholar
Kumar, V, Jha, P, Giacomini, D, Westra, E, Westra, P (2015) Molecular basis of evolved resistance to glyphosate and acetolactate synthase-inhibitor herbicides in kochia (Kochia scoparia) accessions from Montana. Weed Sci 63:758769 Google Scholar
Kumar, V, Jha, P, Reichard, N (2014) Occurrence and characterization of kochia (Kochia scoparia) accessions with resistance to glyphosate in Montana. Weed Technol 28:122130 Google Scholar
Kumar, V, Stahlman, PW, Currie, R, Engel, R, Boyer, G (2018c) Variable response of kochia accessions to dicamba and fluroxypyr in western Kansas. Kansas Agricultural Experiment Station Research Reports 4, 10.4148/2378-5977.7612 Google Scholar
LeClere, S, Wu, C, Westra, P, Sammons, RD (2018) Cross-resistance to dicamba, 2,4-D, and fluroxypyr in Kochia scoparia is endowed by a mutation in an AUX/IAA gene. Proc Natl Acad Sci USA, 10.1073/pnas.1712372115 Google Scholar
Lee, MA, Huang, Y, Nandula, VK, Reddy, KN (2014) Differentiating glyphosate-resistant and glyphosate-sensitive Italian ryegrass using hyperspectral imagery. Page 7 in Kim MS, Chao K, eds. Sensing for Agriculture and Food Quality and Safety VI. Proceedings Volume 9108. Baltimore, MD: SPIE Sensing Technology + Applications. https://doi.org/10.1117/12.2053072 Google Scholar
Légère, A, Stevenson, FC, Beckie, HJ, Warwick, SI, Johnson, EN, Hrynewich, B, Lozinski, C (2013) Growth characterization of kochia (Kochia scoparia) with substitutions at Pro197 or Trp574 conferring resistance to acetolactate synthase–inhibiting herbicides. Weed Sci 61:267276 Google Scholar
Lewis, DW, Gulden, RH (2014) Effect of kochia (Kochia scoparia) interference on sunflower (Helianthus annuus) yield. Weed Sci 62:158165 Google Scholar
Lim, CA, Jha, P, Kumar, V, Leland, S, Jha, A (2016) Survival and fecundity of glyphosate-resistant kochia with variable EPSPS gene copies in response to glyphosate selection. Page 20 in Proceedings of the Western Society of Weed Science. Albuquerque, NM: Western Society of Weed Science Google Scholar
Mallory-Smith, CA, Thill, DC, Stallings, GP (1993) Survey and gene flow in acetolactate synthase resistant kochia and Russian thistle. Pages 555558 in Brighton Crop Protection Conference–Weeds. Farnham, UK: British Crop Protection Council Google Scholar
Martin, SL, Benedict, L, Sauder, CA, Wei, W, Da Costa, LO, Hall, LM, Beckie, HJ (2017) Glyphosate resistance reduces kochia fitness: comparison of segregating resistant and susceptible F2 populations. Plant Sci 261:6979 Google Scholar
Meades, SJ, Hay, SG, Brouillet, L (2000) Annotated Checklist of the Vascular Plants of Newfoundland and Labrador. Digital Flora of Newfoundland and Labrador Vascular Plants. http://www.digitalnaturalhistory.com/flora.htm. Accessed: June 24, 2018 Google Scholar
Mengistu, LW, Christoffers, MJ, Lym, RG (2005) A psbA mutation in Kochia scoparia (L) Schrad. from railroad right-of-ways with resistance to diuron, tebuthiuron, and metribuzin. Pest Manag Sci 61:10351042 Google Scholar
Mengistu, LW, Messersmith, CG (2002) Genetic diversity of kochia. Weed Sci 50:498503 Google Scholar
Mesbah, A, Miller, S, Fornstrom, KJ, Legg, DE (1994) Kochia (Kochia scoparia) and green foxtail (Setaria viridis) interference in sugarbeets (Beta vulgaris). Weed Technol 8:754759 Google Scholar
Mithila, J, Hall, JC, Johnson, WG, Kelley, KB, Riechers, DE (2011) Evolution of resistance to auxinic herbicides: historical perspectives, mechanisms of resistance, and implications for broadleaf weed management in agronomic crops. Weed Sci 59:445457 Google Scholar
Morishita, DW (2018) Impact of glyphosate-resistant sugar beet. Pest Manag Sci 74:10501053 Google Scholar
Morrison, IN, Devine, MD (1994) Herbicide resistance in the Canadian prairie provinces: five years after the fact. Phytoprotection 75(Suppl):516 Google Scholar
Mulugeta, D, Maxwell, BD, Fay, PK, Dyer, WE (1994) Kochia (Kochia scoparia) pollen dispersion, viability and germination. Weed Sci 42:548552 Google Scholar
Nandula, VK, Manthey, FA (2002) Response of kochia (Kochia scoparia) inbreds to 2,4-D and dicamba. Weed Technol 16:5054 Google Scholar
Nugent, P, Shaw, JA, Jha, P, Scherrer, B, Donelick, A, Kumar, V (2018) Discrimination of herbicide-resistant kochia with hyperspectral imaging. J Appl Remote Sens 12:016037 Google Scholar
Nyamusamba, RP (2014) Crop Canopy Effect on Kochia Establishment in Crop Fields. Ph.D dissertation. Brookings, SD: South Dakota State University. 92 pGoogle Scholar
Osipitan, OA, Dille, JA (2017) Fitness outcomes related to glyphosate resistance in kochia (Kochia scoparia): What life history stage to examine? Front Plant Sci 8:1090 Google Scholar
Peterson, GA, Westfall, DG (2004) Managing precipitation use in sustainable dryland agroecosystems. Ann Appl Biol 144:127138 Google Scholar
Petrosino, JS (2010) Response of Weeds to the Intensification of Kansas No-Till Crop Rotations with Cover Cropping. MS thesis. Manhattan, KS: Kansas State University. 155 pGoogle Scholar
Petrosino, JS, Dille, JA, Holman, JD, Roozeboom, KL (2015) Kochia suppression with cover crops in southwestern Kansas. Crop Forage Turfgrass Manag 1:2014–0078Google Scholar
Pettinga, DJ, Ou, J, Patterson, EL, Jugulam, M, Westra, P, Gaines, TA (2017) Increased chalcone synthase (CHS) expression is associated with dicamba resistance in Kochia scoparia . Pest Manag Sci 74 23062315 Google Scholar
Preston, C, Belles, DS, Westra, PH, Nissen, SJ, Ward, SM (2009) Inheritance of resistance to the auxinic herbicide dicamba in kochia (Kochia scoparia). Weed Sci 57:4347 Google Scholar
Primiani, MM, Cotterman, JC, Saari, LL (1990) Resistance of kochia (Kochia scoparia) to sulfonylurea and imidazolinone herbicides. Weed Technol 4:169172 Google Scholar
Rana, N, Jhala, AJ (2016) Confirmation of glyphosate- and acetolactate synthase (ALS)-inhibiting-resistant kochia (Kochia scoparia) in Nebraska. J Agric Sci 8:10 Google Scholar
Reddy, KN, Huang, Y, Lee, MA, Nandula, VK, Fletcher, RS, Thomson, SJ, Zhao, F (2014) Glyphosate-resistant and glyphosate-susceptible Palmer amaranth (Amaranthus palmeri S. Wats.): hyperspectral reflectance properties of plants and potential for classification. Pest Manag Sci 70:19101917 Google Scholar
Riar, DS, Ball, DA, Yenish, JP, Burke, IC (2011) Light-activated, sensor-controlled sprayer provides effective postemergence control of broadleaf weeds in fallow. Weed Technol 25:447453 Google Scholar
Saari, LL, Cotterman, JC, Primiani, MM (1990) Mechanism of sulfonylurea herbicide resistance in the broadleaf weed, Kochia scoparia . Plant Physiol 93:5561 Google Scholar
Schweizer, EE (1973) Predicting sugarbeet root losses based on kochia densities. Weed Sci 21:565567 Google Scholar
Schwinghamer, TD, Van Acker, RC (2008) Emergence timing and persistence of kochia (Kochia scoparia). Weed Sci 56:3741 Google Scholar
Sivakumaran, K, Mulugeta, D, Fay, PK, Dyer, WE (1993) Differential herbicide response among sulfonylurea-resistant Kochia scoparia L. accessions. Weed Sci 41:159165 Google Scholar
Spaunhorst, DJ, Siefert-Higgins, S, Bradley, KW (2014) Glyphosate-resistant giant ragweed (Ambrosia trifida) and waterhemp (Amaranthus rudis) management in dicamba-resistant soybean (Glycine max). Weed Technol 28:131141 Google Scholar
Stallings, GP, Thill, DC, Mallory-Smith, CA, Shafii, B (1995) Pollen-mediated gene flow of sulfonylurea-resistant kochia (Kochia scoparia). Weed Sci 43:95102 Google Scholar
Tan, X, Calderon-Villalobos, LIA, Sharon, M, Zheng, C, Robinson, CV, Estelle, M, Zheng, N (2007) Mechanism of auxin perception by the TIR1 ubiquitin ligase. Nature 446:640645.Google Scholar
Teasdale, JR, Pillai, P, Collins, RT (2005) Synergism between cover crop residue and herbicide activity on emergence and early growth of weeds. Weed Sci 53:521527 Google Scholar
Thill, DC, Mallory-Smith, CA, Saari, LL, Cotterman, JC, Primiani, MM, Saladini, JL (1991) Sulfonylurea herbicide resistant weeds: discovery, distribution, biology, mechanism, and management. Pages 115128 in Caseley JC, Cussans GW, Atkin RK, eds. Herbicide Resistance in Weeds and Crops. Oxford, UK: Butterworth-Heinemann Google Scholar
Thompson, CR, Peterson, DE, Fick, WH, Currie, RS, Kumar, V, Slocombe, (2018) 2018 Chemical Weed Control for Field Crops, Pastures, Rangeland, and Noncropland. Manhattan, KS: Kansas State University Agricultural Experiment Station and Cooperative Extension Service Report of Progress 1139 Google Scholar
Thompson, CR, Thill, DC, Shafii, B (1994) Germination characteristics of sulfonylurea-resistant and -susceptible kochia (Kochia scoparia). Weed Sci 42:5056 Google Scholar
Tidemann, BD, Hall, LM, Harker, KN, Beckie, HJ (2017) Factors affecting weed seed devitalization with the Harrington seed destructor. Weed Sci 65:650658 Google Scholar
Tonks, DJ, Westra, P (1997) Control of sulfonylurea-resistant kochia (Kochia scoparia). Weed Technol 11:270276 Google Scholar
Trebst, A, Draber, W (1986) Inhibitors of photosystem II and the topology of the herbicide and QB binding polypeptide in the thylakoid membrane. Photosynth Res 10:381392 Google Scholar
[USDA-NRCS] United States Department of Agriculture–Natural Resources Conservation Service (2008) The PLANTS Database. Version 3.5. Baton Rouge, LA: National Plant Data Center. http://plants.usda.gov. Accessed: June 15, 2018 Google Scholar
Varanasi, VK, Godar, AS, Currie, RS, Dille, AJ, Thompson, CR, Stahlman, PW, Jugulam, M (2015) Field-evolved resistance to four modes of action of herbicides in a single kochia (Kochia scoparia L. Schrad.) population. Pest Manag Sci 71:12071212 Google Scholar
Vink, JP, Soltani, N, Robinson, DE, Tardif, FJ, Lawton, MB, Sikkema, PH (2012) Glyphosate-resistant giant ragweed (Ambrosia trifida) control in dicamba-tolerant soybean. Weed Technol 26:422428 Google Scholar
Waite, J, Thompson, CR, Peterson, DE, Currie, RS, Olson, BLS, Stahlman, PW, Khatib, KA (2013) Differential kochia (Kochia scoparia) populations response to glyphosate. Weed Sci 61:193200 Google Scholar
Walsh, MJ, Newman, P, Powles, SB (2013) Targeting weed seeds in-crop: a new weed control paradigm for global agriculture. Weed Technol 27:431436 Google Scholar
Walsh, MJ, Powles, SB (2014) High seed retention at maturity of annual weeds infesting crop fields highlights the potential for harvest weed seed control. Weed Technol 28:486493 Google Scholar
Warwick, SI, Xu, R, Sauder, C, Beckie, HJ (2008) Acetolactate synthase target-site mutations and single nucleotide polymorphism genotyping in ALS-resistant kochia (Kochia scoparia). Weed Sci 56:797806 Google Scholar
Weatherspoon, DM, Schweizer, EE (1971) Competition between sugarbeet and five densities of kochia. Weed Sci 19:125128 Google Scholar
Westra, EP (2016)Glyphosate-Resistant Kochia (Kochia scoparia) Management in the Central Great Plains and Western Canada. Ph.D dissertation. Fort Collins, CO: Colorado State University. 99 pGoogle Scholar
Wicks, GA, Martin, AR, Haack, AE, Mahnken, GW (1994) Control of triazine-resistant kochia (Kochia scoparia) in sorghum (Sorghum bicolor). Weed Technol 8:748753 Google Scholar
Wicks, GA, Martin, AR, Mahnken, GW (1993) Control of triazine-resistant kochia (Kochia scoparia) in conservation tillage corn (Zea mays). Weed Sci 41:225231 Google Scholar
Wiersma, AT, Gaines, TA, Preston, C, Hamilton, JP, Giacomini, D, Buell, CR, Leach, JE, Westra, P (2015) Gene amplification of 5-enol-pyruvylshikimate-3-phosphate synthase in glyphosate resistant Kochia scoparia . Planta 241:463474 Google Scholar
Yu, Q, Powles, SB (2014) Resistance to AHAS inhibitor herbicides: current understanding. Pest Manag Sci 70:13401350 Google Scholar
Zorner, PS, Zimdahl, RL, Schweizer, EE (1984) Effect of depth and duration of seed burial on kochia (Kochia scoparia). Weed Sci 32:602607 Google Scholar