Plant names carry a significant amount of information without providing a lengthy description. This is an efficient shorthand for scientists and stakeholders to communicate about a plant, but only when the name is based on a common understanding. It is standard to think of each plant having just two names, a common name and a scientific name, yet both names can be a source of confusion. There are often many common names that refer to the same plant, or a single common name that refers to multiple different species, and some plants have no common name at all. Scientific names are based upon international standards; however, when the taxonomy is not agreed upon, two scientific names may be used to describe the same species. Weed scientists and practitioners can easily memorize multiple plant names and know that they refer to the same species, but when we consider global communication and far-reaching databases, it becomes very relevant to consider two sides of this shift: (1) a need for greater standardization (due to database management and risk of lost data from dropped cross-referencing); and (2) the loss of local heritage, which provides useful meaning through various common names. In addition, weed scientists can be resistant to changing names that they learned or frequently use. The developments in online databases and reclassification of plant taxonomy by phylogenetic relationships have changed the accessibility and role of the list of standardized plant names compiled by the Weed Science Society of America (WSSA). As part of an attempt to reconcile WSSA and USDA common names for weedy plants, the WSSA Standardized Plant Names Committee recently concluded an extensive review of the Composite List of Weeds common names and had small changes approved to about 10% of the list of more than 2,800 distinct species.

Weed invasion has become increasingly recognized as a major threat to the practice of sustainable agriculture and the maintenance of natural ecosystems around the world. Without effective and ongoing management strategies, many weed species have the aggressive capacity to alter ecosystem functions and reduce the economic potential of the land into which they have been introduced. Although traditional weed management strategies can be useful in eliminating certain weeds, these approaches can be costly, economically damaging, and laborious and can result in variable long-term success. To further add to these challenges, several weed species have now developed resistance to a range of herbicide modes of action, which, to date, have been the major mechanism of weed control. As a result, it is anticipated that the use of emerging technology will help to provide a solution for the economical and environmentally sustainable management of various weeds. Of particular interest, emerging technology in the areas of weed detection and control (chemical, mechanical, electrical, laser, and thermal) has shown promising signs of improving long-term weed management strategies. These methods can also be assisted by, or integrated alongside, other technology, such as artificial intelligence or computer vision techniques for improved efficiency. To provide an overview of this topic, this review evaluates a range of emerging technology used for the detection and control of various weeds and explores the challenges and opportunities of their application within the field.

Knowledge of weed seeds present in the soil seedbank is important for understanding population dynamics and forecasting future weed infestations. Quantification of the weed seedbank has historically been laborious, and few studies have attempted to quantify seedbanks on the scale required to make management decisions. An accurate, efficient, and ideally automated method to identify weed seeds in field samples is needed. To achieve sufficient precision, we leveraged YOLOv8, a machine learning object detection to accurately identify and count weed seeds obtained from the soil seedbank and weed seed collection. The YOLOv8 model, trained and evaluated using high-quality images captured with a digital microscope, achieved an overall accuracy and precision exceeding 80% confidence in distinguishing various weed seed species in both images and real-time videos. Despite the challenges associated with species having similar seed morphology, the application of YOLOv8 will facilitate rapid and accurate identification of weed seeds for the assessment of future weed management strategies.

Due to increased food demand, the use of herbicides is both necessary and on the rise. Several herbicide classes target photosynthetic electron transport: Herbicide Resistance Action Committee (HRAC) Groups 5, 6, and 22. These herbicides are used in large amounts in many different cropping systems to control several species of broadleaf and grass weeds. This article provides a comprehensive review of what these photosynthesis inhibitors are, how they are used, and their modes of action. Presently, commercial herbicides only inhibit electron flow at two different sites: photosystem II (PSII) and photosystem I (PSI). Herbicides that inhibit electron flow at PSII block the movement of electrons down the electron transport chain, while those that inhibit electron flow at PSI accept electrons. Necrosis developing on the leaves of plants treated with PSII and PSI inhibitors is due to the accumulation of reactive oxygen species. Evolution of resistance, toxicity concerns, and other limitations of these herbicides call for the exploration of new chemistries that can be used to target this pathway.

Recently, farmers in Brazil have observed a decline in efficacy of glyphosate, chlorimuron, and imazethapyr control of smooth pigweed (Amaranthus hybridus L.). The objectives of this study were to quantify the resistance of Amaranthus in Brazil to glyphosate and acetolactate synthase (ALS)-inhibiting herbicides, elucidate the mechanism of resistance, and assess the frequency of shifts in sensitivity to glyphosate and chlorimuron in Brazil. Dose–response assays were conducted in a greenhouse with glyphosate, chlorimuron, and imazethapyr. This was followed by sequencing of the EPSPS and ALS genes. Additionally, 740 Amaranthus populations across several Brazilian states were monitored over 4 yr, subjected to a single discriminatory dose of glyphosate and chlorimuron. The populations BR18Asp051 and BR21Asp205 were resistant to glyphosate, chlorimuron, and imazethapyr. The elevated resistance level to glyphosate in these populations is attributed to multiple amino acid substitutions (TAP-IVS) in the EPSPS gene; and cross-resistance to sulfonylureas and imidazolinones is conferred by the Trp-574-Leu substitution in the ALS gene in both populations. Overall, resistance distribution indicated that 88% of the sampled populations were considered sensitive to glyphosate, while 66% were sensitive to chlorimuron. Furthermore, 10% of the samples demonstrated multiple resistance to both active ingredients. A shift in glyphosate sensitivity was observed in four states in Brazil; however, sensitivity shifts to chlorimuron were more widely dispersed in Brazilian agricultural regions.

Recently, there has been emphasis on the need to shift away from the use of synthetic chemical herbicides to low-risk alternatives derived from natural sources. This is aimed at lowering or averting the negative impact synthetic herbicides have on the environment and dealing with the emergence of weed species resistant to these chemicals. As a result, more stringent measures or outright bans on the use of most synthetic herbicides have been put in place by regulatory bodies. As seaweeds are abundant resources in the marine environment that have the capacity to produce diverse bioactive compounds, they could serve as sustainably viable, natural, and low-risk alternatives/sources to explore for potential phytotoxic capabilities. This could in turn help to enhance or boost the availability of effective solutions in the global bioherbicide market. This review highlights the prospects of using seaweeds as novel biopesticides for the control and management of various plant pests, including weed species, and for the development of sustainable agriculture/forestry practices. More specifically, it focuses on their use as a rich natural source for novel bioherbicide development, a potential that has remained underexplored for many years. However, to unlock the full potential of seaweed-derived bioherbicides and to create a potential path toward their development, increased research and development efforts are urgently needed to tackle and overcome possible constraints posed in this novel area, such as variability in seaweed chemical composition, formulation technologies, stability and efficacy of seaweed bioactive compounds, cost and scalability, and environmental considerations.

During the past 30 yr an impasse has developed in the discovery and commercialization of synthetic herbicides with new molecular targets and novel chemistries. Similarly, there has been little success with bioherbicides, both microbial and chemical. These bioherbicides are needed to combat fast-growing herbicide resistance and to fulfill the need for more environmentally and toxicologically safe herbicides. In response to this substantial and growing opportunity, numerous start-up companies are utilizing novel approaches to provide new tools for weed management. These diverse new tools broaden the scope of discovery, encompassing advanced computational, bioinformatic, and imaging platforms; plant genome–editing and targeted protein degradation technologies; and machine learning and artificial intelligence (AI)-based strategies. This review contains summaries of the presentations of 10 such companies that took part in a symposium held at the WSSA annual meeting in 2024. Four of the companies are developing microbial bioherbicides or natural product–based herbicides, and the other six are using advanced technologies, such as AI, to accelerate the discovery of herbicides with novel molecular target sites or to develop non-GMO, herbicide-resistant crops.

Herbicides are the primary tool for controlling weeds in peanut (Arachis hypogaea L.) and are crucial to sustainable peanut production in the United States. The literature on chemical weed management in peanut in the past 53 yr (1970 to 2022) in the United States was systematically reviewed to highlight the strengths and weaknesses of different herbicides and identify current research gaps in chemical weed management. Residual weed control in peanut is achieved mainly with dimethenamid-P, ethalfluralin, pendimethalin, and S-metolachlor. More recently, the use of the protoporphyrinogen oxidase inhibitor flumioxazin and acetolactate synthase inhibitors, such as diclosulam, for residual weed control in peanut has increased considerably. Postemergence broadleaf weed control in peanut is achieved mainly with acifluorfen, bentazon, diclosulam, imazapic, lactofen, paraquat, and 2,4-DB, while the graminicides clethodim and sethoxydim are the major postemergence grass weed control herbicides in peanut. Although several herbicides are available for weed control in peanut, no single herbicide can provide season-long weed control due to limited application timing, lack of extended residual activity, variability in weed control spectrum, and rotational restrictions. Therefore, effective weed management in peanut often requires herbicide mixtures and/or sequential application of preplant-incorporated, preemergence, and/or postemergence herbicides. However, the available literature showed a substantive range in herbicide efficacy due to variations in environmental conditions and flushes of weed germination across years and locations. Despite the relatively high efficacy of herbicides, the selection of herbicide-resistant weeds is another area of increasing concern. Future research should focus on developing new strategies for preventing or delaying the development of resistance and improving herbicide efficacy within the context of climate change and emerging constraints such as water shortages, rising temperatures, and increasing CO2 concentration.

Herbicide resistance is often viewed as a complex problem in need of innovative management solutions. Because of the transboundary mobility of many weeds, resistance to herbicides is also viewed as a community-scale issue. Consequently, the idea of greater coordination among resource users—especially growers—is often promoted as a management approach. Recently, scholars have framed herbicide resistance as a commons problem in need of collective action. Specifically, social scientists have explored the utility of adopting bottom-up, community-based approaches to help solve the growing problem of herbicide resistance through a framework for interpreting the commons known as common pool resource theory. This article analyzes how herbicide resistance fits—and fails to fit—within common pool resource theory and offers an updated conceptual framework from which to build future work. We argue that the application of common pool resource theory to herbicide-resistance management is underdeveloped, and approaches based on this theory have shown little success. The relevance of common pool resource theory for informing herbicide-resistance management is less settled than existing scholarship has suggested, and other frameworks for approaching transboundary resource problems—such as co-production of knowledge and participatory action research—warrant consideration.

Understanding the timing of weed emergence is crucial to effective management. Management practices implemented too early may fail to completely control late-emerging seedlings, whereas management practices implemented too late will suffer from low efficacy. Weed emergence times reflect biological factors, such as seed dormancy and germination requirements, as well as environmental conditions. We conducted a systematic review of studies that developed models to predict weed emergence temporal patterns. We screened 1,854 studies, 98 of which were included in the final dataset. Most of the studies included were conducted in North America (51%) or Europe (30%). A wide variety of weed species (102) and families (21) were included, and many studies modeled several weeds. Grass weeds (Poaceae) were modeled most frequently (83 instances). Most weeds (40%) had base temperature ${T_{\rm{b}}}$ values between 0 and 5 C, and 38% had base water potential ${{\rm{\psi }}_{\rm{b}}}$ ranging from −1.0 to −0.5 MPa. Most studies used empirical parametric models, such as Weibull (40%) or Gompertz (30%) models. Nonparametric and mechanistic models were also represented. Models varied in their biological and environmental data requirements. In general, empirical parametric models based on hydrothermal time (i.e., time above base temperature and water potential thresholds) represented a good balance between ease of use and prediction accuracy. Soft computing approaches such as artificial neural networks demonstrated substantial potential in situations with complex emergence patterns and limited data availability, although they (soft computing approaches) can be susceptible to overfitting. Our study also demonstrated variability in model performance and limited generalizability across species and regions. This finding underscores the need for context-specific and well-validated weed emergence models to inform management, especially in the context of climate change.

Palmer amaranth (Amaranthus palmeri S. Watson) was first reported in Iowa in 2013 and has continued to spread across the state over the last decade. Amaranthus palmeri is widely recognized as one of the more economically important weeds in production agriculture. The presence of A. palmeri in Iowa is concerning as the species has evolved resistance to ten herbicide sites of action, however, no formal characterization has been conducted on Iowa populations. Therefore, herbicide assays were conducted on an A. palmeri population collected in Harrison County, IA, in 2023 (Southwest Palmer Amaranth [SWPA]) and a known herbicide-susceptible population collected from Nebraska in 2001 (Palmer Amaranth Susceptible [PAS]). The two populations were treated with preemergence and postemergence herbicides commonly used in Iowa. The treatments included preemergence applications of atrazine, metribuzin, and mesotrione and postemergence applications of atrazine, imazethapyr, glyphosate, lactofen, mesotrione, glufosinate, 2,4-D, and dicamba at 1× and 4× the labeled rates. Survival frequency of SWPA was >90% when treated postemergence with 1× rates of imazethapyr, atrazine, glyphosate, and mesotrione compared with ≤6% for PAS. Both SWPA and PAS had 0% survival when treated with lactofen, glufosinate, 2,4-D, and dicamba at the 1× or 4× rates. Plant population density reduction for SWPA was 53% and 40% in response to 1× rates of preemergence-applied mesotrione and atrazine, respectively. Metribuzin applied preemergence reduced SWPA plant population density by >90% at both rates. Dose–response experiments revealed the 50% effective doses (ED50) of mesotrione, glyphosate, imazethapyr, and atrazine for SWPA were 9.5-,8.5-, 71-, and 40-fold greater than for PAS, respectively. The results confirm that SWPA is four-way multiple-herbicide resistant. Amaranthus palmeri infestations are likely to continue to spread within Iowa; therefore, diversified weed management programs that include early detection, rapid response, and effective multi-tactic management strategies will be required for control.

Herbicides have been placed in global Herbicide Resistance Action Committee (HRAC) herbicide groups based on their sites of action (e.g., acetolactate synthase–inhibiting herbicides are grouped in HRAC Group 2). A major driving force for this classification system is that growers have been encouraged to rotate or mix herbicides from different HRAC groups to delay the evolution of herbicide-resistant weeds, because in theory, all active ingredients within a herbicide group physiologically affect weeds similarly. Although herbicide resistance in weeds has been studied for decades, recent research on the biochemical and molecular basis for resistance has demonstrated that patterns of cross-resistance are usually quite complicated and much more complex than merely stating, for example, a certain weed population is Group 2-resistant. The objective of this review article is to highlight and describe the intricacies associated with the magnitude of herbicide resistance and cross-resistance patterns that have resulted from myriad target-site and non–target site resistance mechanisms in weeds, as well as environmental and application timing influences. Our hope is this review will provide opportunities for students, growers, agronomists, ag retailers, regulatory personnel, and research scientists to better understand and realize that herbicide resistance in weeds is far more complicated than previously considered when based solely on HRAC groups. Furthermore, a comprehensive understanding of cross-resistance patterns among weed species and populations may assist in managing herbicide-resistant biotypes in the short term by providing growers with previously unconsidered effective control options. This knowledge may also inform agrochemical company efforts aimed at developing new resistance-breaking chemistries and herbicide mixtures. However, in the long term, nonchemical management strategies, including cultural, mechanical, and biological weed management tactics, must also be implemented to prevent or delay increasingly problematic issues with weed resistance to current and future herbicides.

Waterhemp [Amaranthus tuberculatus (Moq.) Sauer] is one of the most troublesome weeds in the United States. An A. tuberculatus population (CHR) was identified in Illinois, USA, as resistant to herbicides from six different site-of-action groups. Recently, the same population was also recognized as dicamba resistant. This study aimed to identify key resistance genes and the putative dicamba resistance mechanism in A. tuberculatus via transcriptomics analysis. Multiple differentially expressed (DE) genes and co-expression gene modules were identified as associated with dicamba resistance. Specifically, genes encoding glutathione S-transferases (GSTs), ATP-binding cassette transporters, peroxidases, and uridine diphosphate (UDP)-glycosyltransferases (UGTs) were identified. Results indicated enhanced oxidative stress tolerance as the primary mechanism for reducing dicamba toxicity. Results also point to potential glycosylation via UGTs and conjugation via GSTs of dicamba and its by-products. This is the first transcriptomics characterization of dicamba resistance in A. tuberculatus. Multiple non-target-site resistance genes were identified, indicating a cross-resistance pattern in the CHR population leading to a putative-enhanced oxidative stress response. Regions of multiple DE genes (i.e., genomic hot spots) across the A. tuberculatus genome corroborate previous results and potentially add to the complexity of non-target-site resistance traits.

Information regarding the prevalence and distribution of herbicide-resistant waterhemp [Amaranthus tuberculatus (Moq.) Sauer] in Minnesota is limited. Whole-plant bioassays were conducted in the greenhouse on 90 A. tuberculatus populations collected from 47 counties in Minnesota. Eight postemergence herbicides, 2,4-D, atrazine, dicamba, fomesafen, glufosinate, glyphosate, imazamox, and mesotrione, were applied at 1× and 3× the labeled doses. Based on their responses, populations were classified into highly resistant (≥40 % survival at 3× the labeled dose), moderately resistant (<40% survival at 3× the labeled dose but ≥40% survival at 1× the labeled dose), less sensitive (10% to 39% survival at 1× the labeled dose), and susceptible (<10% survival at 1× the labeled dose) categories. All 90 populations were resistant to imazamox, while 89% were resistant to glyphosate. Atrazine, fomesafen, and mesotrione resistance was observed in 47%, 31%, and 22% of all populations, respectively. Ten percent of the populations were resistant to 2,4-D, and 2 of 90 populations exhibited >40% survival following dicamba application at the labeled dose. No population was confirmed to be resistant to glufosinate. However, 22% of all populations were classified as less sensitive to glufosinate. Eighty-two populations were found to be multiple-herbicide resistant. Among these, 15 populations exhibited resistance to four different herbicide sites of action (SOAs); 7 and 4 populations were resistant to five and six SOAs, respectively. All six-way-resistant populations were from southwest Minnesota. Two populations, one from Lincoln County and the other from Lyon County, were resistant to 2,4-D, atrazine, dicamba, fomesafen, glyphosate, imazamox, and mesotrione, leaving only glufosinate as a postemergence control option for these populations in corn (Zea mays L.) and soybean [Glycine max (L.) Merr.]. Diversified management tactics, including nonchemical control measures along with herbicide applications from effective SOAs, should be implemented to slow down the evolution and spread of herbicide-resistant A. tuberculatus populations.

Quinclorac controls crabgrass (Digitaria spp.) in cool- and warm-season turfgrass species. Herbicide-resistant smooth crabgrass [Digitaria ischaemum (Schreb.) Schreb. ex Muhl.] biotypes have evolved due to recurrent usage of quinclorac. Two Mississippi populations (MSU1 and MSU2) of D. ischaemum were characterized using standard greenhouse dose–response screens to assess their resistance relative to known susceptible populations. Subsequent investigations explored mechanisms of resistance, including examining cyanide accumulation, glutathione S-transferase (GST) activity, and the potential involvement of cytochrome P450s in MSU1, MSU2, and a susceptible (SMT2). Resistant populations MSU1 and MSU2 required 80 and 5 times more quinclorac, respectively, to reach 50% biomass reduction than susceptible populations. The SMT2 biotype accumulated three times more cyanide than the resistant MSU1 and MSU2 populations. GST activity was elevated in resistant MSU1 and MSU2 populations. Furthermore, quinclorac concentrations in treated resistant populations were elevated when plants were pretreated with the P450 inhibitor malathion. These findings suggest a non–target site based mechanism of resistance involving the accumulation of cyanide. This may provide a scientific basis for understanding the occurrence of quinclorac-resistant D. ischaemum, although further research is needed to investigate potential target-site mechanisms of resistance.

Rapid increase in the hectarage and agricultural systems that use cover cropping for soil conservation and improvement, soil moisture retention, and weed management has highlighted the need to develop formal breeding programs for cover crop species. Cereal rye (Secale cereale L.) is preferred by many growers due to high biomass production and weed-suppression potential, which is believed to be partially due to allelopathy. Rye germplasm exhibits large variability in allelopathic activity, which could be used to breed rye with enhanced weed suppression. Here, we provide an overview of rye history and breeding and describe a strategy to develop rye lines with increased allelopathic activity. The discussion focuses on ways to deal with important challenges to achieving this goal, including obligate cross-pollination and its consequent high segregation levels and the need to quantify allelopathic activity under field conditions. This review seeks to encourage weed scientists to collaborate with plant breeders and promote the development of cover crop cultivars better suited to reduce weed populations.

Allohexaploid wheat (Triticum aestivum L.) is tolerant to halauxifen-methyl (HM) via rapid detoxification of the phytotoxic form of HM, halauxifen acid (HA), to non-phytotoxic metabolites. Previous research utilizing ‘Chinese Spring’ (CS) wheat, alien substitution (i.e., endogenous chromosome pair substituted with a homoeologous pair from diploid Sears’ goatgrass (Aegilops searsii M. Feldman & M. Kislev) (AS), or nullisomic-tetrasomic (NT) lines indicated plants lacking chromosome 5A are more sensitive than CS to HM. We hypothesized the increased HM sensitivity of these plants results from losing gene(s) on chromosome 5A associated with HA metabolism, which leads to a reduced HA detoxification rate relative to CS. To compare HA abundance among AS, CS, alien substitution, and NT lines during a time course, two excised-leaf studies using unlabeled HM and liquid chromatography–mass spectrometry analyses were performed. Aegilops searsii accumulated more HA than CS did, and each substitution line at 8, 12, and 24 h after treatment (HAT). Furthermore, only the wheat substitution line lacking chromosome 5A displayed greater abundance of HA relative to CS (2.4- to 3.8-fold, depending on the time point). In contrast, HA abundances in lines possessing chromosome 5A were not different than HA abundances in CS at all time points. When NT lines were compared with CS, the nullisomic 5D-tetrasomic 5A (N5D-T5A) line displayed similar HA abundance, whereas the nullisomic 5A-tetrasomic 5D (N5A-T5D) accumulated approximately 3-fold more HA at 12 and 24 HAT. These results biochemically support the hypothesis that genes encoding HA-detoxifying enzyme(s) are located on wheat chromosome 5A and corroborate findings from previous greenhouse phenotypic experiments. Future experimentation is needed to identify and characterize genes and enzymes on wheat chromosome 5A involved with HA detoxification, which may include cytochrome P450 monooxygenases, unknown oxidases, UDP-dependent glucosyltransferases, or, potentially, transcription factors that regulate expression of these genes associated with HA detoxification.

The success of the insect sterile technique (IST) in managing insect pests raised the hypothesis that a similar approach could be employed to control weed populations. Here, we investigated the feasibility of employing irradiated sterile pollen as a means to disrupt seed production in dioecious weeds, specifically focusing on Palmer amaranth (Amaranthus palmeri S. Watson). Our goal was to determine the optimal irradiation dose that strikes a balance between inducing sterility and preserving competitiveness, as excessive doses could result in pollen mortality, while low doses may retain fertility. Plants were grown in a greenhouse during the summer of 2020 and spring of 2021. Once they reached the flowering stage, male and female individuals were isolated. Mature pollen samples were collected and exposed to varying dosages (0, 100, 200, 300, 400, and 500 Gy) of gamma rays. These irradiated and non-irradiated pollen samples were used in pollen viability assessments and hand-pollination experiments. In the hand-pollination study conducted in 2020, we employed six pollination treatments using different irradiation doses. The results showed that 300 Gy was the most effective dose, resulting in a maximum reduction of 30% in seed set compared with open pollination when irradiated pollen had prior access to the stigma through artificial pollination before open pollination. In 2021, to simulate real field conditions, three additional treatments were introduced into the study, further confirming the effectiveness of the optimal 300 Gy dose. Our findings indicate that the sterile pollen technique (SPT) using irradiated pollen can be a valuable approach for reducing weed seed production. SPT also holds potential for broad-spectrum weed control by mixing sterile pollen from multiple weed species in a single application. Additionally, it could aid in managing herbicide-resistant weeds that have survived in-season control efforts. This research contributes to the development of novel and sustainable weed management strategies.