Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] is a dominant weed species occurring in rice fields across China. Metamifop, a common herbicide, is frequently applied to control E. crus-galli and other grassy weeds in rice fields. Herein, HS01, an E. crus-galli population suspected to be resistant (R) to metamifop, was collected from Hanshan County in Anhui Province. Whole-plant dose-response testing revealed that, compared with the susceptible (S) population FD03, HS01 had developed high-level resistance to metamifop with a resistance index (RI) of 11.76 and showed cross-resistance to cyhalofop-butyl (RI=9.33), fenoxaprop-P-ethyl (RI=5.80) and clethodim (RI=3.24). Gene sequencing revealed a Cys-2088-Arg mutation in ACCase 1,5 allele of all the R plants, while ACCase gene overexpression was not involved in the resistance. Molecular docking indicated that the less negative binding energies might be the main reason for the resistance of HS01 to ACCase-inhibiting herbicides. A derived cleaved amplified polymorphic sequence (dCAPS) method was developed for the rapid identification of the Cys-to-Arg mutation in the ACCase gene at codon position 2088 in E. crus-galli. Additionally, pretreatment with the cytochrome P450 inhibitor piperonyl butoxide or the glutathione S-transferase inhibitor 4-chloro-7-nitrobenzoxa-diazole had no significant effects (p> 0.05) on the resistance of HS01 to metamifop. To our knowledge, this is the first report of a Cys-2088-Arg mutation in E. crus-galli ACCase that confers cross-resistance to ACCase-inhibiting herbicides.

Herbicide-resistant weeds threaten modern agriculture production. In Michigan, horseweed (Erigeron canadensis L.; syn. Conyza canadensis (L.) Cronq.) is among the most troublesome weeds, and glyphosate was widely used to control E. canadensis. Due to extreme selection pressure imposed by heavy glyphosate usage, glyphosate-resistant E. canadensis is widespread. New technologies to control resistant E. canadensis are being introduced in the form of multiple herbicide-resistance traits into glyphosate-resistant soybean (e.g. dicamba or 2,4-D choline). These new soybean [Glycine max (L.) Merr.] varieties will likely increase the use of 2,4-D and dicamba thus increasing the resistance selection pressure in E. canadensis. Predicting agronomic factors that drive herbicide-resistance evolution can serve as an effective proactive tool to advise practitioners to modify management strategies. Therefore, the objectives of this study are: 1) conduct dose-response assays to assess current resistance spectrum of E. canadensis collected in Michigan and 2) predict and determine the main factors in row crop production that contribute to resistance evolution in these accessions. Dose-response assays were conducted to evaluate the herbicide sensitivity spectrum to glyphosate, dicamba, and 2,4-D in 20 E. canadensis accessions collected from eight Michigan counties. Out of the 20 accessions, 60% were resistant to glyphosate, 35% to 2,4-D, and 20% to dicamba. Pearson’s correlation coefficient of dose-response values were positive in all comparisons (2,4-D-dicamba, r = 0.35; dicamba-glyphosate, r = 0.15; 2,4-D-glyphosate, r = 0.21). Dose-response data were integrated in odds ratio analyses to access the influence that previous management history had on the occurrence of resistance. Out of the significant pairwise comparisons, 44% were related to crop rotation frequency, 33% to previous herbicide-resistance status, and 22% to location collected. Results highlight that growers have the ability to proactively manage herbicide-resistance evolution progression of E. canadensis in Michigan by adopting integrated weed management techniques to slow successive selection events that occur in low diversity management systems.

Established hedgerows of native plants on the borders of crop fields provide a variety of ecosystem service benefits in agricultural landscapes. However, their influence on weed communities is not well understood, and there are concerns that hedgerows could contribute to weed infestations on farms. To address this research gap, we examined the role of established hedgerows of native California plants on weed abundance (weed numbers and cover) and weed species richness in field borders and in adjacent crops, in large-scale, monocropping systems compared with conventionally managed field borders (i.e., no hedgerows). Across 20 farm sites in California’s Central Valley, hedgerows on orchard crop borders reduced weed numbers by 66%, weed species richness by 59%, and weed cover by 74%. On annual field crop borders, hedgerows reduced weed numbers by 71%, weed species richness by 60%, and weed cover by 70%. In orchards, hedgerows also reduced weed intrusion into the adjacent crop interior, with significantly lower weed cover to the first tree row (area directly underneath the trees), weed species richness to the 10 m tree row, and weed numbers to the 10 m avenue (area between the tree rows). Yearly management practices and associated costs for weed control in established hedgerows were significantly less than for conventionally managed field borders. This study highlights the effectiveness of native hedgerows as a sustainable nature-based solution for reducing weed pressure and management inputs on farms.

Typically, weed density is used to predict weed-induced yield loss, as it is easy and quick to quantify, even though it does not account for weed size and time of emergence relative to the crop. Weed-crop leaf area relations, while more difficult to measure, inherently account for differences in plant size, representing weed-crop interference more accurately than weed density alone. Unmanned aerial systems (UAS) may allow for efficient quantification of weed and crop leaf cover over a large scale. It was hypothesized that UAS imagery could be used to predict maize yield loss based on weed-crop leaf cover ratios. A yield loss model for maize (Zea mays L.) was evaluated for accuracy using 15- and 30-m altitude aerial RGB and four-band multispectral imagery collected at four North Carolina locations. The model consistently over and underpredicted yield loss when observed yield loss was less than and greater than 3000 kg ha-1, respectively. Altitude and sensor type did not influence the accuracy of the prediction. A correction for the differences between predicted and observed yield loss was incorporated into the linear model to improve overall precision. The correction resulted in r2 increasing from 0.17 to 0.97 and a reduction in RMSE from 705 kg ha-1 to 219 kg ha-1. The results indicated that UAS images can be used to develop predictive models for weed-induced yield loss prior to canopy closure, making it possible for growers to plan production and financial decisions before the end of the growing season.

Sorghum halepense (L.) Pers. (Johnsongrass), an invasive tallgrass, actively inhabits grassland ecosystems of North America. The grasslands ecoregions of the southern Great Plains are particularly susceptible to S. halepense invasion and dominance because of its preferential growth in continental climate zones coupled with its ability to readily colonize recent disturbances associated with declining livestock grazing and anthropogenic energy and housing development. Controlling S. halepense via chemical or mechanical inputs can reduce plant species’ abundance temporarily, but are typically followed by S. halepense re-establishment. S. halepense does, however, provide high quality forage and appears to withstand the frequent drought and flooding events associated with climate change in southern Great Plains ecosystems. In this review, the benefits and drawbacks of S. halepense in southern Great Plains grassland ecosystems are discussed and areas where research on this species could be expanded are identified.

Weed infestations have been identified as a major cause of yield reductions in rapeseed (Brassica napus L.), a vital oil crop that has gained significant prominence in Iran, especially within Fars Province. Weed management using machine learning algorithms has become a crucial approach within the framework of precision agriculture for enhancing the efficacy and efficiency of weed control strategies. The evolution of habitat suitability models for weeds represents a significant advancement in agricultural technology, offering the capability to predict weed occurrence and proliferation accurately and reliably. This study focuses on the issue of dominant weed infestation in rapeseed cultivation, particularly emphasizing the prevalence and impact of wild oat (Avena fatua L.) as the dominant weed species in rapeseed farming in 2023. We collected data on 12 environmental variables related to topography, climate, and soil properties to develop habitat suitability models. Three “machine learning techniques”, including “random forest (RF)”, “support vector machine (SVM)”, and “boosted regression tree (BRT)”, were estimated based on the “receiver operating characteristic (ROC) and area under the curve (AUC)” to model the distribution of A. fatua. Model performance was quantified using the “ROC curve and AUC” metrics to identify the best predictive algorithm. The findings indicated that “Random Forest (RF), boosted regression tree (BRT), and support vector machine (SVM)” models exhibited accuracies of 99%, 97%, and 96% for the habitat suitability of A. fatua, respectively. The Boruta feature selection method identified the slope variable as significantly influential in wild oat habitat suitability modeling, followed by plan curvature, clay, temperature, and silt. This study serves as a case study that highlights the utility of machine learning for habitat suitability predictions when information on multiple environmental variables is available. This approach supports effective weed management strategies, potentially enhancing rapeseed productivity and mitigating the ecological impacts associated with weed infestation.

Trifludimoxazin is a PPO-inhibiting herbicide currently under development for preplant burndown and soil residual weed control in soybean [Glycine max (L.) Merr.] and other crops. Greenhouse dose response experiments with foliar applications of trifludimoxazin, fomesafen, and saflufenacil were conducted on susceptible and PPO-inhibitor resistant (PPO-R) waterhemp [Amaranthus tuberculatus (Moq.) Sauer] and Palmer amaranth (Amaranthus palmeri S. Watson) biotypes. These PPO-R biotypes contained the PPO2 target site (TS) mutations ΔG210 (A. tuberculatus and A. palmeri), R128G (A. tuberculatus), and V361A (A. palmeri). The R/S ratios for fomesafen and saflufenacil ranged from 2.0 to 9.2 across all PPO-R biotypes. In contrast, the response of known PPO inhibitor-susceptible and -resistant biotypes to trifludimoxazin did not differ within each Amaranthus species. In 2017 and 2018 experiments at the Meigs and Davis Purdue Agriculture Centers were conducted in fields with native A. tuberculatus populations comprised of 3% and 30% PPO-R plants (ΔG210 mutation), respectively. At Meigs in 2018, A. tuberculatus control following foliar applications of fomesafen, lactofen, saflufenacil, and trifludimoxazin was greater than 95%. When averaged across the other three site-years, applications of 25 g ai ha-1 trifludimoxazin resulted in 95% control of A. tuberculatus 28 DAA, while applications of fomesafen (343 g ai ha-1), lactofen (219 g ai ha-1), or saflufenacil (25.0 or 50 g ai ha-1), resulted in 80 to 88% control. Thus, at these relative application rates, the foliar efficacy of trifludimoxazin was comparable or greater on A. tuberculatus, when compared to other commercial PPO inhibitors, even in populations where low frequencies of PPO inhibitor-resistant plants exist. The lack of cross resistance for common PPO2 TS mutations to trifludimoxazin, and the level of foliar field efficacy observed on populations containing PPO-R individuals suggests that trifludimoxazin may be a valuable herbicide in an integrated approach for managing herbicide-resistant Amaranthus weeds.

Echinochloa crus-galli var. crus-galli (L.) P. Beauv. (EC), Echinochloa crus-galli var. mitis (Pursh) Petermann (ECM), and Echinochloa glabrescens Munro ex Hook. f. (EG) are all serious rice (Oryza sativa L.) weeds, which are usually treated as a single species in weed management practices. To determine interspecific and intraspecific differences in seed germination responding to different temperatures among the three Echinochloa weeds, we conducted field surveys and collected 66 EC, 141 ECM, and 120 EG populations from rice fields of East China in 2022; and tested their seed germination under 28/15C (day/night), 30/20C, and 35/25C regimes, simulating temperatures of rice planting periods for double-cropping early rice, single-cropping rice, and double-cropping late rice, respectively. In EC, ECM, and EG, seed percentage germination (cumulative percent of germinated seed) and germination index (sum of the ratio of germinated seeds to the corresponding days) increased with increasing temperatures. At 28/15C, the average percentage germination of EC populations (67.5%) was significantly (P < 0.05) higher than ECM (46.4%) and EG (43.7%); GD50 (duration for 50% total germination) for EC populations (5.2 d) was significantly shorter than ECM (5.9 d) and EG (5.8 d). At 35/25C, the percentage germination of EC (90.7%), ECM (80.5%), and EG (80.3%) were all significantly the highest among the three temperature treatments, respectively, and the GD50 values for EC (2.5 d), ECM (2.6 d), and EG (2.7 d) were all significantly the lowest. At 30/20C and 35/25C, average germination percentage of populations collected from transplanted rice fields were significantly higher than that of populations collected from direct-seeded rice fields. Moreover, among EG populations, the longitudes and latitudes of collection locations were significantly correlated with seed percentage germination and germination indices. According to the interspecific differences and intraspecific variations of Echinochloa species, weed management strategies should also be customized according to the species and population characteristics in seed germination.

Foliar-applied postemergence applications of glufosinate are often applied to glufosinate-resistant crops to provide nonselective weed control without significant crop injury. Rainfall, air temperature, solar radiation, and relative humidity near the time of application have been reported to affect glufosinate efficacy. However, previous research may have not captured the full range of weather variability to which glufosinate may be exposed to prior to or following application. Additionally, climate models suggest more extreme weather will become the norm, further expanding this weather range glufosinate can be exposed to. The objective of this research was to quantify the probability of successful weed control (efficacy ≥85%) with glufosinate applied to some key weed species across a broad range of weather conditions. A database of >10,000 North American herbicide evaluation trials was used in this study. The database was filtered to include treatments with a single POST application of glufosinate applied to waterhemp (Amaranthus tuburculatus (Moq.) J. D. Sauer), morningglory species (Ipomoea spp.), and/or giant foxtail (Setaria faberi Herm.) <15cm in height. These species were chosen because they are well represented in the database and listed as common and troublesome weed species in both corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] (Van Wychen 2020, 2022). Individual random forest models were created. Low rainfall (≤20 mm) over the five days prior to glufosinate application was detrimental to the probability of successful control of A. tuburculatus and S. faberi. Lower relative humidity (≤70%) and solar radiation (≤23 MJ m-1 day-1) the day of application reduced the probability of successful weed control in most cases. Additionally, the probability of successful control decreased for all species when average air temperature over the first five days after application was ≤25C. As climate continues to change and become more variable, the risk of unacceptable control of several common species with glufosinate is likely to increase.

Integrating cover crops (CC) in dryland crop rotations could help in controlling herbicide-resistant weeds. Field experiments were conducted at Kansas State University Agricultural Research Center near Hays, KS from 2020-2023 to determine the effect of fall-planted CC on weed suppression in grain sorghum, crop yield, and net returns in no-till dryland winter wheat (Triticum aestivum L.)-grain sorghum [Sorghum bicolor (L.) Moench]-fallow (W-S-F) rotation. The field site had a natural seedbank of glyphosate-resistant (GR) kochia [Bassia scoparia (L.) A. J. Scott] and Palmer amaranth (Amaranthus palmeri S. Watson). A CC mixture (triticale/winter peas/radish/rapeseed) was planted after wheat harvest and terminated at triticale heading stage before sorghum planting. Treatments included nontreated control, chemical fallow, CC terminated with glyphosate (GLY), and CC terminated with GLY+ acetochlor/atrazine (ACR/ATZ). Across three years, CC terminated with GLY+ACR/ATZ reduced total weed density by 34-81% and total weed biomass by 45-73% compared to chemical fallow during the sorghum growing season. Average grain sorghum yield was 786 to 1432 kg ha-1 and did not differ between chemical fallow and CC terminated with GLY+ACR/ATZ. However, net returns were lower with both CC treatments (USD -$275 to $66) in all three years compared to chemical fallow (USD -$111 to $120). These results suggest that fallow replacement with fall-planted CC in the W-S-F rotation can help suppress GR B. scoparia and A. palmeri in the subsequent grain sorghum. However, the cost of integrating CC exceeded the benefits of improved weed control and lower net returns were recorded in all three years compared to chemical fallow.

Furrow-irrigated rice (Oryza sativa L.) hectares are increasing in the Midsouth. The lack of sustained flooding creates a favorable environment for weed emergence and persistence, which makes Palmer amaranth (Amaranthus palmeri S. Watson) difficult to control throughout the growing season. The negative yield impacts associated with season-long A. palmeri interference in corn, cotton, and soybean have been evaluated. However, there is limited knowledge of the weed’s ability to influence rice grain yield. Research was initiated in 2022 and 2023 to determine the effect of A. palmeri time of emergence relative to rice on weed seed production and grain yield. Cotyledon stage A. palmeri plants were marked every seven days, beginning one week before rice emergence through four weeks after rice emergence. Amaranthus palmeri seed production decreased exponentially as emergence timing was delayed relative to rice, and seed production increased by 447 seed plant-1 for every one-gram increase in weed biomass. Without rice competition and from the earliest emergence timing, A.palmeri produced 540,000 seeds plant-1. Amaranthus palmeri that emerged one week before the crop had the greatest spatial influence on rice, with grain yield loss of 5% and 50% at a distance of 1.4 m and 0.40 m from the weed, respectively. As A. palmeri emergence was delayed, the area of influence decreased. However, A. palmeri plants emerging 3.5 weeks after rice emergence still negatively affected grain yield and produce sufficient seed to replenish the soil seedbank, potentially impacting long-term crop management decisions. These results show that the time of A. palmeri emergence is a crucial factor influencing rice grain yield and weed seed production, which can be used to determine the consequences of escapes in rice.

Weed suppression benefits of cover crops (CCs) have long been recognized; however, the specific ability of CCs to suppress highly epidemic Amaranthus spp. (Palmer amaranth (Amaranthus palmeri S. Watson), redroot pigweed (Amaranthus retroflexus L.), smooth pigweed (Amaranthus hybridus L.), and waterhemp [Amaranthus tuberculatus (Moq.) Sauer]) has not been widely discussed. The objective of this meta-analysis was to evaluate the implications of CC management decisions (CC type, planting and termination methods, residue fate after termination, and in-season weed management plan) on Amaranthus spp. weed density (ASWD) and Amaranthus spp. weed biomass (ASWB) compared to no CC (NCC) in temperate regions including US and Canada. We found 41 studies conducted across US and Canada and extracted 595 paired observations. The results indicate that CCs reduced the ASWD by 58% in the early- [0–4 weeks after crop planting (WAP)], by 48% in the mid- (5–8 WAP) and by 44% in the late- (>8 WAP) season. Similarly, CCs reduced ASWB by 59%, 55%, and 37% in the early-, mid-, and late-season, respectively. Meta-regression analysis showed CCs terminated within 2.5 weeks of crop planting reduced ASWD by ≥50%. Cover crop biomass required to reduce ASWD and ASWB by 50% was 4,079 kg ha–1 for ASWD and 5,352 kg ha–1 for ASWB. Among CC types, grasses and mixtures reduced ASWD by 60% and 77% in early-, 53% and 59% in mid-, and 44% and 47% in late-season. Legume CCs were effective only during the early-season (47% ASWD reduction) while brassicas did not affect ASWD. Cover crop residues remaining on the soil surface were more effective for reducing ASWD than incorporation. Cover crops did not affect ASWD or ASWB compared to NCC when herbicides were used for in-season weed management. In general, CCs were found to reduce ASWD, and ASWB, therefore can be used as an effective tool for integrated management of Amaranthus spp.

Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] has become a major annual weed in wheat (Triticum aestivum L.) production systems in the inland Pacific Northwest. With large genetic variability and abundant seed production, L. perenne ssp. multiflorum has developed globally 74 documented cases of herbicide resistance covering eight different mechanisms of action. Harvest weed seed control (HWSC) systems were introduced in Australia in response to the widespread evolution of multiple herbicide resistance in rigid ryegrass (Lolium rigidum L.) and wild radish (Raphanus raphanistrum L.). The efficacy of these systems for any given weed species is directly related to the proportion of total seed retained by that species at harvest time. From 2017-2020, ten L. perenne ssp. multiflorum plants were collected from three different slope aspects at each location. Collections were initiated in each field when it was visually apparent that seed fill was nearly complete, and seed shatter had not yet occurred. Collection continued at near weekly intervals until the fields were harvested. The number of filled florets on a spikelet was used to assess the degree of seed shatter over time. Seed shatter at harvest was 67% of the total number of florets on each spikelet. Seed shatter was closely aligned with wheat kernel development in both spring and winter wheat. The high percentage of L. perenne ssp. multiflorum seeds that are shattered by harvest may make HWSC less effective than for L. rigidum in Australia; however, seeds with the greatest biomass tend to not shatter prior to harvest, which may increase the efficacy of HWSC for managing the soil seedbank. Strategies like planting earlier maturing wheat cultivars could help HWSC be more effective by having wheat harvest begin earlier when more L. perenne ssp. multiflorum seeds are still on the mother plant.

The rapid and efficient removal of weeds is currently a research hotspot. With the integration of robotics and automation technology into agricultural production, intelligent field weeding robots have emerged. The development status of weeding robots is overviewed based on bibliometric and scientific mapping methods. Secondly, the two key technologies of weeding robots are summarized. Then, the research progress of precision spraying weeding robots, mechanical weeding robots, and thermal weeding robots with laser devices, categorized by their weeding methods, is reviewed. Finally, a summary and an outlook on the future development trends of intelligent field weeding robots are provided, aiming to offer a reference for further promoting the development of weeding robots.

Efficient chemical weed management considers precise application of herbicides, maximizing herbicide retention and absorption, reducing the impact of abiotic factors, and mitigating off-target movement in order to optimize herbicide efficacy. Hence, this study assessed the employability and cost-efficiency of an unmanned aerial vehicle (UAV) for pre-planting application and post-emergence selective grass weed control infesting legume cover crops (LCCs) in immature oil palm (Elaeis quineensis Jacq.) plantation. Field experiments were conducted in 2020 and 2021 at a research center and an oil palm replanting area in Jerantut, Pahang, Malaysia. Droplet deposition and distribution analyses revealed that the pressure at 0.25 MPa yielded better spraying coverage and increased droplet counts compared to 0.15 MPa. For pre-planting application, both UAV and mist blower resulted in total weed control. Meanwhile for selective grass control in the LCCs, conventional knapsack sprayer (CKS) application provided slightly better weed control than the UAV over the 12 weeks observation. However, cost-efficiency analysis revealed that UAV spraying yielded economically favorable for areas over 3,000 hectares, with potential savings ranging from 4% to 28%. Furthermore, UAV spraying demonstrated superior operational efficiency and reduced working hours by 37%, water consumption by 91%, and human labor expenses by 81% compared to both conventional methods. These findings underscore the potential of UAV-based spraying for large-scale weed control in oil palm plantations and highlight its efficiency, comparable effectiveness, and cost-saving benefits.

Accounting for 53% of United States peanuts (Arachis hypogaea L.), Georgia is the top peanut-producing state with approximately 1.42 billion kg produced in 2023. Peanut producers often use the ALS imidazolinone herbicide imazapic but reduced yellow nutsedge (Cyperus esculentus L.) control was reported in Georgia peanuts after four-years of continuous imazapic use. This study aimed to determine the level of resistance (LD50, I50, and GR50), potential cross-resistance for the suspected resistant population, and identify the associated genetic mutations conferring resistance. A susceptible biotype was treated with 0, 0.0088, 0.0175, 0.035, 0.07, 0.14, 0.28, and 0.56 kg ai ha-1, and a resistant biotype was sprayed with 0, 0.07, 0.14, 0.28, 0.56, 1.13, 2.26, and 4.5 kg ai ha-1 of imazapic. To determine if the suspected resistant biotype was cross-resistant to halosulfuron-methyl, an ALS herbicide used to control nutsedge spp., both biotypes were treated with 0, 0.0117, 0.0233, 0.0466, 0.0933, 0.187, 0.373, and 0.746 g ai ha-1 of halosulfuron-methyl. Plants were rated for injury 7, 14, and 28 days after treatment (DAT), and above-ground biomass harvested at 28 DAT. For imazapic, LD50 was 0.041 and 1.503 kg ai ha-1 and the GR50 was estimated to be 0.0128 and 1.853 kg ai ha-1 for Sus and Res biotypes, respectively, indicating 36 and 145-fold increase in resistance of the Res biotype for I50 and GR50, respectively. Both biotypes responded similarly to applications of halosulfuron-methyl, with biomass reductionat rates greater than 0.023 kg ai ha-1. Transcriptome profiles revealed a mutation in the target-site gene of the resistant biotype, causing an amino acid substitution from Alanine to Valine at position 205 (Ala205Val). Growers should continue to rotate chemistries and implement integrated weed management approaches for control of C. esculentus as the use of imazapic over consecutive years has led to resistance in C. esculentus.