Data from a national survey of 348 U.S. sports field managers were used to examine the effects of participation in Cooperative Extension events on the adoption of turfgrass weed management practices. Of the respondents, 94% attended at least one event in the previous three years. Of this 94%, 97% reported adopting at least one practice as a result of knowledge gained at an Extension turfgrass event. Half of the respondents adopted four or more practices; a third adopted five or more practices. Non-chemical, cultural practices were the most-adopted practices (65% of respondents). Multiple regression analysis was used to examine factors explaining practice adoption and Extension event attendance. Compared to attending one event, attending three events increased total adoption by an average of one practice. Attending four or more events increased total adoption by two practices. Attending four or more events (compared to one event) increased the odds of adopting six individual practices by 3- to 6-fold, depending on the practice. This suggests practice adoption could be enhanced by encouraging repeat attendance among past Extension event attendees. Manager experience was a statistically significant predictor of the number of Extension events attended, but a poor direct predictor of practice adoption. Experience does not appear to increase adoption directly, but indirectly, via its impact on Extension event attendance. In addition to questions about weed management generally, the survey asked questions about annual bluegrass management, specifically. Respondents were asked to rank seven sources of information for their helpfulness in managing annual bluegrass. There was no single dominant information source, but Extension was ranked as the most helpful more than any other source (by 22% of the respondents) and was ranked among the top three by 53%, closely behind field representative/local distributor sources at 54%.

Postemergence selective monocot control in grain sorghum is an issue due to the limited number of herbicides available. The herbicides currently labeled in grain sorghum have strict use restrictions, low efficacy on johnsongrass, or weed resistance issues. To introduce a new effective herbicide mode of action for monocot control, multiple companies and universities have been developing herbicide-resistant grain sorghum that would allow producers to utilize either acetolactate synthase (ALS) or acetyl coenzyme A carboxylase (ACCase) inhibitors for postemergence monocot control. An experiment was conducted in Fayetteville, AR, in 2020 and 2021 to determine the effectiveness of two ALS-inhibiting herbicides and nine ACCase-inhibiting herbicides on TamArkTM grain sorghum, conventional grain sorghum, and problematic monocot weed species. Grain sorghum and monocot weeds (johnsongrass, broadleaf signalgrass, barnyardgrass, and Texas panicum) were sprayed when TamArkTM grain sorghum reached the 2- to 3-leaf stage. TamArkTM grain sorghum was tolorant to all ACCase-inhibiting herbicides tested exhibiting ≤10% injury at all evaluation timings, except clethodim and sethoxydim, and had no resistance to the ALS-inhibiting herbicides evaluated. Additionally, all ACCase inhibitors except diclofop and pinoxaden controlled all monocots tested >91% by 28 days after application (DAA). Conversely, the two ALS inhibitors, imazamox and nicosulfuron had ≤81% control of broadleaf signalgrass 28 DAA but still controlled all other monocots >95%. TamArkTM grain sorghum 'has low sensitivity to multiple ACCase-inhibiting herbicides thus providing an effective POST option for monocot weed control and unwanted volunteer TamArkTM plants can be controlled with cledthodim, sethoxydim, nicosulfuron, or imazamox has low sensitivity to multiple ACCase-inhibiting herbicides. Imazamox and nicosulfuron, both ALS-inhibiting herbicides, while not useful on TamArkTM grain sorghum, are effective options for monocot control in IgrowthTM and InzenTM grain sorghum, respectively.

Genetic similarities between johnsongrass and grain sorghum leave producers with limited herbicide options for postemergence johnsongrass control. TamArkTM grain sorghum with resistance to acetyl CoA carboxylase-inhibiting herbicides was developed through a collaboration between the University of Arkansas System Division of Agriculture and Texas A&M AgriLife Research. Two field experiments were conducted in 2021 in two locations each Keiser and Marianna, AR or Fayetteville and Marianna, AR. The objective of the first was to determine the optimal rate and application timing of fluazifop-butyl for control of natural johnsongrass populations in a non-crop setting, and of the second was to evaluate johnsongrass control and TamArkTM grain sorghum tolerance in response to fluazifop-butyl applied at different timings and rates based on crop growth stage. The highest levels of johnsongrass control occurred when sequential applications of fluazifop-butyl were utilized. All sequential treatments provided at least 80% johnsongrass control at any rate or application timing tested. A single application of fluazifop-butyl provided greater than 90% johnsongrass control when applied at 210 g ai ha-1 to johnsongrass with less than 6 leaves. Weed size played a role in achieving high levels of johnsongrass control. Greater than 90% control was achieved when johnsongrass had 6-leaves or less at the initial application for the sequential application treatments. A single application of fluazifop-butyl at 105 g ai ha-1 resulted in no more than 82% johnsongrass mortality at any application timing. TamArk TM grain sorghum injury did not exceed 6% at any application timing or rate. It was, therefore, considered to be safe even if the initial application was made before the 6-leaf crop stage. Since no unacceptable levels of injury were observed with TamArkTM grain sorghum for fluazifop-butyl, johnsongrass size at the time of application should be the most critical aspect for control with this herbicide.

The past 50 yr of advances in weed recognition technologies have poised site-specific weed control (SSWC) on the cusp of requisite performance for large-scale production systems. The technology offers improved management of diverse weed morphology over highly variable background environments. SSWC enables the use of nonselective weed control options, such as lasers and electrical weeding, as feasible in-crop selective alternatives to herbicides by targeting individual weeds. This review looks at the progress made over this half-century of research and its implications for future weed recognition and control efforts; summarizing advances in computer vision techniques and the most recent deep convolutional neural network (CNN) approaches to weed recognition. The first use of CNNs for plant identification in 2015 began an era of rapid improvement in algorithm performance on larger and more diverse datasets. These performance gains and subsequent research have shown that the variability of large-scale cropping systems is best managed by deep learning for in-crop weed recognition. The benefits of deep learning and improved accessibility to open-source software and hardware tools has been evident in the adoption of these tools by weed researchers and the increased popularity of CNN-based weed recognition research. The field of machine learning holds substantial promise for weed control, especially the implementation of truly integrated weed management strategies. Whereas previous approaches sought to reduce environmental variability or manage it with advanced algorithms, research in deep learning architectures suggests that large-scale, multi-modal approaches are the future for weed recognition.

Recent innovations in 3D imaging technology have created unprecedented potential for better understanding weed responses to management tactics. Although traditional 2D imaging methods for mapping weed populations can be limited in the field by factors such as shadows and tissue overlap, 3D imaging mitigates these challenges by using depth data to create accurate plant models. Three-dimensional imaging can be used to generate spatiotemporal maps of weed populations in the field and target weeds for site-specific weed management, including automated precision weed control. This technology will also help growers monitor cover crop performance for weed suppression and detect late-season weed escapes for timely control, thereby reducing seedbank persistence and slowing the evolution of herbicide resistance. In addition to its many applications in weed management, 3D imaging offers weed researchers new tools for understanding spatial and temporal heterogeneity in weed responses to integrated weed management tactics, including weed–crop competition and weed community dynamics. This technology will provide simple and low-cost tools for growers and researchers alike to better understand weed responses in diverse agronomic contexts, which will aid in reducing herbicide use, mitigating herbicide-resistance evolution, and improving environmental health.

In this research, the deep-learning optimizers Adagrad, AdaDelta, Adaptive Moment Estimation (Adam), and Stochastic Gradient Descent (SGD) were applied to the deep convolutional neural networks AlexNet, GoogLeNet, VGGNet, and ResNet that were trained to recognize weeds among alfalfa using photographic images taken at 200×200, 400×400, 600×600, and 800×800 pixels. An increase in the image sizes reduced the classification accuracy of all neural networks. The neural networks that were trained with images of 200×200 pixels resulted in better classification accuracy than the other image sizes investigated here. The optimizers AlexNet and GoogLeNet trained with AdaDelta and SGD outperformed the Adagrad and Adam optimizers; VGGNet trained with AdaDelta outperformed Adagrad, Adam, and SGD; and ResNet trained with AdaDelta and Adagrad outperformed the Adam and SGD optimizers. When the neural networks were trained with the best-performing input image size (200×200 pixels) and the best-performing deep learning optimizer, VGGNet was the most effective neural network, with high precision and recall values (≥0.99) when validation and testing datasets were used. Alternatively, ResNet was the least effective neural network in its ability to classify images containing weeds. However, there was no difference among the different neural networks in their ability to differentiate between broadleaf and grass weeds. The neural networks discussed herein may be used for scouting weed infestations in alfalfa and further integrated into the machine vision subsystem of smart sprayers for site-specific weed control.

A 3-yr field study was conducted in Keiser, AR, to investigate the response of the naturally occurring weed flora, dominated by Palmer amaranth, under various combinations of 4-hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting herbicide-based programs and crop rotation sequences. In the first year, corn plots were established with three corn HPPD-based herbicide programs designed to represent a range of efficacies and selection pressures for resistance. In the following two years, corn as monoculture or with soybean and/or cotton crops was included in the rotation sequence for selected herbicide programs. Weed emergence, weed biomass, and soil seedbank were assessed through the entire experimental period. The results show that crop rotation, especially a rotation sequence with corn followed by (fb) soybean fb cotton, and the lowest-risk herbicide program involving seven sites of action over the course of the entire crop rotation was effective in reducing the emergence of naturally occurring weeds, including Palmer amaranth, prickly sida, morningglory species, and grass weeds (broadleaf signalgrass, large crabgrass, barnyardgrass, and johnsongrass) by 88.3%, 57.5%, 28.7%, and 76.3%, respectively. Treatments without crop rotation (corn as monoculture for 3 consecutive years) and poor herbicide programs, with one site of action, increased weed emergence, notably of Palmer amaranth and prickly sida, by 73.5% and 74.1%, respectively. The soil seedbank showed a similar trend to weed emergence. This study highlights the fact that reducing the weed seedbank cannot rely on one management practice but requires a multitactic approach with various control methods. HPPD-inhibiting herbicide programs seem to be effective on Palmer amaranth when coupled with crop rotation and should be used with other best management practices.

Italian ryegrass is a major weed in winter cereals in the south-central United States. Harvest weed seed control (HWSC) tactics that aim to remove weed seed from crop fields are a potential avenue to reduce Italian ryegrass seedbank inputs. To this effect, a 4-yr, large-plot field study was conducted in College Station, Texas, and Newport, Arkansas, from 2016 to 2019. The treatments were arranged in a split-plot design. The main-plot treatments were (1) no narrow-windrow burning (a HWSC strategy) + disk tillage immediately after harvest, (2) HWSC + disk tillage immediately after harvest, and (3) HWSC + disk tillage 1 mo after harvest. The subplot treatments were (1) pendimethalin (1,065 g ai ha−1; Prowl H2O®) as a delayed preemergence application (herbicide program #1), and (2) a premix of flufenacet (305 g ai ha−1) + metribuzin (76 g ai ha−1; Axiom®) mixed with pyroxasulfone (89 g ai ha−1; Zidua® WG) as an early postemergence application followed by pinoxaden (59 g ai ha−1; Axial® XL) in spring (herbicide program #2). After 4 yr, HWSC alone was significantly better than no HWSC. Herbicide program #2 was superior to herbicide program #1. Herbicide program #2 combined with HWSC was the most effective treatment. The combination of herbicide program #1 and standard harvest practice (no HWSC; check) led to an increase in fall Italian ryegrass densities from 4 plants m−2 in 2017 to 58 plants m−2 in 2019 at College Station. At wheat harvest, Italian ryegrass densities were 58 and 59 shoots m−2 in check plots at College Station and Newport, respectively, whereas the densities were near zero in plots with herbicide program #2 and HWSC at both locations. These results will be useful for developing an improved Italian ryegrass management strategy in this region.

Herbicide resistance, documented in many economically damaging weed species, is a major threat to global crop production. The injudicious use of herbicides, often in the absence of diverse weed control strategies, poses an immense selection pressure on weed communities for resistance evolution and weed adaptive traits such as high seed dormancy. This study evaluates the interaction among developing herbicide resistance, seed size, and seed dormancy of ripgut brome (Bromus diandrus Roth), wild oat (Avena fatua L.), and hare barley [Hordeum leporinum Link; syn. Hordeum murinum L. ssp. leporinum (Link) Arcang.] collected from within intensively managed fields (in-crop) in comparison with populations in surrounding ruderal (non-crop disturbed) areas with no history of exposure to herbicides within the Western Australian grainbelt. Seed size of the three species varied by farming system (continuous cereal-intensive annual crops, diverse annual crops, pasture based) and habitat (in-crop, ruderal). Field populations of H. leporinum and B. diandrus tended to have greater seed size compared with ruderal populations. Larger seeds had significantly more dormancy in all three weed species. Field-collected populations that were exposed to herbicide applications for at least the past 5 yr exhibited significantly greater seed dormancy compared with their counterparts present in ruderal areas within the same geographic area. The association between increased seed dormancy and developing multiple herbicide resistance further complicates effective weed management.

Seed retention, and ultimately seed shatter, are extremely important for the efficacy of harvest weed seed control (HWSC) and are likely influenced by various agroecological and environmental factors. Field studies investigated seed-shattering phenology of 22 weed species across three soybean [Glycine max (L.) Merr.]-producing regions in the United States. We further evaluated the potential drivers of seed shatter in terms of weather conditions, growing degree days, and plant biomass. Based on the results, weather conditions had no consistent impact on weed seed shatter. However, there was a positive correlation between individual weed plant biomass and delayed weed seed–shattering rates during harvest. This work demonstrates that HWSC can potentially reduce weed seedbank inputs of plants that have escaped early-season management practices and retained seed through harvest. However, smaller individuals of plants within the same population that shatter seed before harvest pose a risk of escaping early-season management and HWSC.

Wood vinegar, a product of pyrolysis, can induce phytotoxicity on plants when applied at an adequate rate and concentration. The objective of this research was to investigate wood vinegar obtained from the pyrolysis of apple tree branches for weed control in dormant zoysiagrass. In environment-controlled growth chambers, white clover visual injury and shoot mass reduction were evaluated and compared to the nontreated control after wood vinegar application at 1,000, 2,000, or 4,000 L ha−1 under 10 C or 30 C temperature conditions. Averaged across rates, wood vinegar rapidly desiccated white clover and caused 83% and 71% visual injury at 10 C and 30 C, respectively, at 1 d after treatment (DAT). Averaged across temperatures, wood vinegar at 1,000, 2,000, and 4,000 L ha−1 reduced white clover shoot mass by 56%, 81%, and 98% from the nontreated control at 10 DAT, respectively. In field experiments, weed control increased as wood vinegar rates increased from 1,000 to 5,000 L ha−1 in dormant zoysiagrass. The effective application dose of wood vinegar required to provide 90% control (ED90) of annual fleabane, Persian speedwell, and white clover was determined to be 2,450, 2,300, and 4,020 L ha−1, respectively, at 2 wk after treatment. Turf quality did not differ among the wood vinegar treatments and the nontreated control when zoysiagrass completely recovered from dormancy. Overall, results illustrate that wood vinegar resulting from the pyrolysis of apple tree branches can be used as a nonselective herbicide in dormant turfgrass, offering a new nonsynthetic herbicide option for weed control in managed turf.

The objective of this paper was to review the reproductive biology, herbicide-resistant (HR) biotypes, pollen-mediated gene flow (PMGF), and potential for transfer of alleles from HR to herbicide-susceptible grass weeds including barnyardgrass, creeping bentgrass, Italian ryegrass, johnsongrass, rigid (annual) ryegrass, and wild oats. The widespread occurrence of HR grass weeds is at least partly due to PMGF, particularly in obligate outcrossing species such as rigid ryegrass. Creeping bentgrass, a wind-pollinated turfgrass species, can efficiently disseminate herbicide resistance alleles via PMGF and movement of seeds and stolons. The genus Agrostis contains about 200 species, many of which are sexually compatible and produce naturally occurring hybrids and hybrids with species in the genus Polypogon. The self-incompatibility, extremely high outcrossing rate, and wind pollination in Italian ryegrass clearly point to PMGF as a major mechanism by which herbicide resistance alleles can spread across agricultural landscapes, resulting in abundant genetic variation within populations and low genetic differentiation among populations. Italian ryegrass can readily hybridize with perennial ryegrass and rigid ryegrass due to their similarity in chromosome numbers (2n = 14), resulting in interspecific gene exchange. Johnsongrass, barnyardgrass, and wild oats are self-pollinated species, so the potential for PMGF is relatively low and limited to short distances; however, seeds can easily shatter upon maturity before crop harvest, leading to wider dispersal. The occurrence of PMGF in reviewed grass weed species, even at a low rate, is greater than that of spontaneous mutations conferring herbicide resistance in weeds and thus can contribute to the spread of herbicide resistance alleles. This review indicates that the transfer of herbicide resistance alleles occurs under field conditions at varying levels depending on the grass weed species.

The genus Echinochloa constitutes some of the most prominent weed species found in rice (Oryza sativa L.) production worldwide. The taxonomy of Echinochloa is complex due to its morphological variations. The morphophysiological diversity and taxonomic characteristics of Echinochloa ecotypes infesting rice fields in Texas are unknown. A total of 54 Echinochloa ecotypes collected during late-season field surveys in 2015 and 2016 were characterized in a common garden in 2017. Plants were characterized for 14 morphophysiological traits, including stem angle; stem color; plant height; leaf color; leaf texture; flag leaf length, width, and angle; days to flowering; panicle length; plant biomass; seed shattering; seed yield; and seed dormancy. Principal component analysis indicated that 4 (plant height, flag leaf length, seed shattering, and seed germination) of the 14 phenological traits characterized here had significantly contributed to the overall morphological diversity of Echinochloa spp. Results showed wide interpopulation diversity for the measured traits among the E. colona ecotypes, as well as diverse intrapopulation variability in all three Echinochloa species studied, including barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.], junglerice [Echinochloa colona (L.) Link], and rough barnyardgrass [Echinochloa muricata (P. Beauv.) Fernald]. Taxonomical classification revealed that the collection consisted of three Echinochloa species, with E. colona being the most dominant (96%), followed by E. crus-galli (2%), and E. muricata (2%). Correlation analysis of morphophysiological traits and resistance status to commonly used preemergence (clomazone, quinclorac) and postemergence herbicides (propanil, quinclorac, imazethapyr, and fenoxaprop-ethyl) failed to show any significant association. Findings from this study provided novel insights into the morphophysiological characteristics of Echinochloa ecotypes in rice production in Texas. The morphological diversity currently present in Echinochloa ecotypes could contribute to their adaptation to selection pressure imposed by different management tools, emphasizing the need for a diversified management approach to effectively control this weed species.

The presence of a soil seedbank facilitates the persistence of annual weed species in arable fields. Soil weed seedbank is replenished by many sources, but the largest one is the seeds produced by uncontrolled late-season weed escapes. The estimation of weed seed production potential from late-season escapes may allow farmers to make appropriate management decisions to minimize seedbank replenishment. The objective of this research was to evaluate the feasibility of using unmanned aerial vehicle–based RGB and multispectral imagery for estimating seed rain potential in late-season weed escapes in crop fields. Three case studies were used to capture images of weed escapes before crop harvest: common waterhemp [Amaranthus tuberculatus (Moq.) Sauer] in soybean [Glycine max (L.) Merr.], Palmer amaranth [Amaranthus palmeri (S.) Watson] in cotton (Gossypium hirsutum L.), and johnsongrass [Sorghum halepense (L.) Pers.] in soybean. Randomly selected quadrats with different density gradients of weed escapes were sampled at the time of crop maturity. High-resolution RGB and multispectral images of the experimental area were collected using drones immediately before ground sample collection. Normalized difference vegetation index (NDVI), excess green index (ExG), and canopy volume estimates derived from canopy height models were used to obtain weed biological measurements (biomass and seed production). Among the indices investigated, NDVI and ExG had very strong correlations (0.71 to 0.97) with weed biomass. No specific remote sensing variable was ideal across the three cases examined here, suggesting that a generalized remote sensing approach may not offer robust estimations and case-specific applications are imperative. Nonetheless, drone imagery is a powerful tool for estimating seed production from uncontrolled weed escapes and assisting with management decision making.

Ryegrass (Lolium spp.) is a troublesome weed in major wheat (Triticum aestivum L.) production regions in the United States. High diversity and adaptive potential are known to contribute to its success as a weed species and also create difficulties in correct species identification in fields. The objective of this research was to characterize diversity for 16 different morphological traits among 56 Lolium populations collected from wheat production fields across the Texas Blackland Prairies region and identify Lolium species based on taxonomic characteristics. Populations were highly diverse (both at inter- and intrapopulation levels) for the traits studied, and a taxonomic comparison with USDA-GRIN reference samples revealed that all the populations were variants of Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] with a few offtypes of perennial ryegrass (Lolium perenne L.) or probable hybrids between the two species. Hierarchical clustering grouped the populations into six clusters based on their similarities for the morphological traits investigated. Principal component analysis showed that the variability for yield traits greatly contributed to the total diversity. Pre-flowering plant height (stage 10 on Feekes scale) was positively correlated with tiller count, shoot biomass, and spike count, but not with total seed count per plant, whereas plant height at maturity (stage 11.3 to 11.4 on Feekes scale) was highly correlated with total seeds per plant. Further, basal node color was positively correlated with plant growth habit, regrowth rate, and leaf color. Leaf blade width was positively correlated with survival to pinoxaden and multiple herbicides, whereas, spike count was negatively correlated with survival to mesosulfuron. The high levels of intra- as well as interpopulation variability documented in this study indicate the potential of this species to rapidly adapt to herbicides and emphasize the need for implementing diverse management tactics, including the integration of harvest weed seed control.

Potential effectiveness of harvest weed seed control (HWSC) systems depends upon seed shatter of the target weed species at crop maturity, enabling its collection and processing at crop harvest. However, seed retention likely is influenced by agroecological and environmental factors. In 2016 and 2017, we assessed seed-shatter phenology in 13 economically important broadleaf weed species in soybean [Glycine max (L.) Merr.] from crop physiological maturity to 4 wk after physiological maturity at multiple sites spread across 14 states in the southern, northern, and mid-Atlantic United States. Greater proportions of seeds were retained by weeds in southern latitudes and shatter rate increased at northern latitudes. Amaranthus spp. seed shatter was low (0% to 2%), whereas shatter varied widely in common ragweed (Ambrosia artemisiifolia L.) (2% to 90%) over the weeks following soybean physiological maturity. Overall, the broadleaf species studied shattered less than 10% of their seeds by soybean harvest. Our results suggest that some of the broadleaf species with greater seed retention rates in the weeks following soybean physiological maturity may be good candidates for HWSC.

Seed shatter is an important weediness trait on which the efficacy of harvest weed seed control (HWSC) depends. The level of seed shatter in a species is likely influenced by agroecological and environmental factors. In 2016 and 2017, we assessed seed shatter of eight economically important grass weed species in soybean [Glycine max (L.) Merr.] from crop physiological maturity to 4 wk after maturity at multiple sites spread across 11 states in the southern, northern, and mid-Atlantic United States. From soybean maturity to 4 wk after maturity, cumulative percent seed shatter was lowest in the southern U.S. regions and increased moving north through the states. At soybean maturity, the percent of seed shatter ranged from 1% to 70%. That range had shifted to 5% to 100% (mean: 42%) by 25 d after soybean maturity. There were considerable differences in seed-shatter onset and rate of progression between sites and years in some species that could impact their susceptibility to HWSC. Our results suggest that many summer annual grass species are likely not ideal candidates for HWSC, although HWSC could substantially reduce their seed output during certain years.

A paper-based survey was conducted from 2015 to 2017 among stakeholders of the Texas rice industry on current weed management challenges and factors influencing management decisions. A total of 108 survey questionnaires were completed by stakeholders at the rice Cooperative Extension meetings conducted in the rice-growing counties of Texas. In addition, late-season field surveys were conducted prior to harvest in 2015 and 2016 across the rice-growing counties to understand dominant weed escapes occurring in rice fields. Results from the questionnaire survey revealed that rice–fallow–rice was the most common rotation practiced in Texas rice production. Echinochloa spp., Leptochloa spp., and Cyperus spp. were the top three problematic weed issues faced by the respondents. Among the Leptochloa species, Nealley’s sprangletop, a relatively new species in rice fields, was indicated as an emerging concern. Clomazone was the most frequently used PRE herbicide, whereas quinclorac, propanil, imazethapyr, and cyhalofop were the popular POST herbicides. Most respondents (72%) made weed-control decisions on the basis of economic thresholds, whereas 63% made decisions on the basis of weed problems from previous years. Most respondents (88%) expressed moderate to high concern for herbicide-resistant weeds in their operations. Strategies to manage herbicide-resistant weeds and economical weed management practices were among the top suggested research needs. The field survey revealed that jungle rice, Nealley’s sprangletop, and hemp sesbania were the top three late-season weed escapes in rice production in Texas, with frequencies of occurrence of 28%, 19%, and 13%, respectively. Furthermore, average field area infested by a species was the greatest for jungle rice (13%), followed by hemp sesbania (11%) and weedy rice (11%). Findings from the stakeholder and field surveys help direct future research and outreach efforts for sustainable weed management in Texas rice.

Herbicide-resistant weeds pose a severe threat to sustainable vegetation management in various production systems worldwide. The majority of the herbicide resistance cases reported thus far originate from agronomic production systems where herbicide use is intensive, especially in industrialized countries. Another notable sector with heavy reliance on herbicides for weed control is managed turfgrass systems, particularly golf courses and athletic fields. Intensive use of herbicides, coupled with a lack of tillage and other mechanical tools that are options in agronomic systems, increases the risk of herbicide-resistant weeds evolving in managed turfgrass systems. Among the notable weed species at high risk for evolving resistance under managed turf systems in the United States are annual bluegrass, goosegrass, and crabgrasses. The evolution and spread of multiple herbicide resistance, an emerging threat facing the turfgrass industry, should be addressed with the use of diversified management tools. Target-site resistance has been reported commonly as a mechanism of resistance for many herbicide groups, though non–target site resistance is an emerging concern. Despite the anecdotal evidence of the mounting weed resistance issues in managed turf systems, the lack of systematic and periodic surveys at regional and national scales means that confirmed reports are very limited and sparse. Furthermore, currently available information is widely scattered in the literature. This review provides a concise summary of the current status of herbicide-resistant weeds in managed turfgrass systems in the United States and highlights key emerging threats.

Tillage regimes can influence weed population dynamics and, consequently, the choice of appropriate weed management practices. Studies were conducted in 2016 and 2017 in a long-term (36-yr) grain sorghum [Sorghum bicolor (L.) Moench ssp. bicolor] experiment at Texas A&M University, College Station, to determine the impact of long-term no-till (NT) and conventional till (CT) systems on weed species dynamics. Higher densities of johnsongrass [Sorghum halepense (L.) Pers.], prostrate spurge [Chamaesyce humistrata (Engelm. ex A. Gray) Small], waterhemp [Amaranthus tuberculatus (Moq.) Sauer], and henbit (Lamium amplexicaule L.) were recorded in the NT system compared with the CT system. Further, the NT system showed greater weed diversity (Shannon-Wiener index, H = 0.8) and species richness (S = 6.2), compared with the CT system (H = 0.6, S = 4.2). Seedling emergence of some dominant weed species was also delayed in the NT system. In the CT system, 50% emergence of S. halepense (8.5 C base temperature) and waterhemp (10 C base temperature) occurred at 59 and 63 growing degree days (GDD), respectively, whereas 68 and 75 GDD, respectively, were required in the NT system. Further, a greater proportion (61%) of the viable seedbank was present at the top 5 cm of the soil in the NT system compared with the CT system (46%). Overall, findings from this 36-yr-long tillage experiment have revealed that the NT system had greater weed densities (especially of the perennial weed S. halepense) and a high proportion of weed seeds (particularly small-seeded annuals) on the topsoil layer, corroborating some earlier reports that were based on short-term investigations. Findings indicate that growers transitioning to NT systems should be mindful of potential shifts in weed species dominance and develop appropriate management tactics.