Seed impact mills, like the Redekop Seed Control Unit (SCU) and the integrated Harrington Seed Destructor (iHSD), have the potential to fit within the U.S. wheat (Triticum aestivum L.) production system, but they may be affected by changes in crop yield and harvest residues moisture as they can have an impact on chaff flow rate and chaff moisture, respectively. This research aimed to determine the seed kill of problematic weed species and how varying chaff flow rates and chaff moisture affect seed kill and horsepower draw of the SCU and the iHSD. Four different chaff flow rates were tested at 0.75, 1.5, 2.25, and 3.0 kg sec-1, which spans 0.5x to 2x of a combines standard throughput. Additionally, four chaff moisture contents were tested at 10.7%, 16.4%, 22.1%, and 27.8%, which span and exceed typical harvest conditions. Results indicated that >91% of all weed seeds of the tested species were killed by either mill. Seed kill decreased by 7.9% and 0.08% for every 1 kg increase in chaff flow rate for Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] and hairy vetch (Vicia villosa Roth), respectively, for the iHSD. Seed kill also decreased by 3.4% for every 1 kg increase in chaff flow rate for weedy L. perenne ssp. multiflorum for the SCU. Increasing chaff moisture resulted in seed kill decreasing by 0.43% and 0.015% for every 1% increase in chaff moisture for weedy L. perenne ssp. multiflorum and Brassica napus L., respectively, with the SCU. Both chaff flow rate and chaff moisture had a significant effect on horsepower draw for both mills compared to an empty mill. Despite the increase in horsepower draw and the decrease in seed kill, these data indicate the potential for seed impact mills to operate in less-than-ideal conditions while still providing seed kill rates >74%.

Residual herbicides are primarily degraded in the soil through microbial breakdown. Any practices that result in increased soil biological activity, such as cover cropping (between cash crop seasons), could lead to a reduced persistence of herbicides in the soil. Furthermore, cover crops can also interfere with herbicide fate by interception. Field trials were conducted between 2020 and 2023, in a corn-soybean rotation, to investigate the influence of cover crop [cereal rye (Secale cereale L.) and crimson clover (Trifolium incarnatum L.) use on soil enzyme activities [β-glucosidase (BG) and dehydrogenase (DHA)], its effect on the concentration of residual herbicides (sulfentrazone, s-metolachlor, cloransulam-methyl, atrazine, and mesotrione) in the soil, and the interception of herbicides by cover crop residue. The use of cover crops occasionally resulted in increased BG and DHA activities relative to the fallow treatment. However, even when there was an increase in the activity of these two enzymes, increased degradation of the residual herbicides was not observed. The initial concentrations of all residual herbicides in the soil were significantly reduced due to interception by cereal rye biomass. Nevertheless, significant reductions in early season weed biomass were observed when residual herbicides were included in the tank mixture applied at cover crop termination relative to the application of glyphosate plus glufosinate. Results from this research suggests that the use of cereal rye or crimson clover as cover crops (between cash crop seasons) do not impact the persistence of residual herbicides in the soil nor reduce their efficacy in controlling weeds early in the growing season.

The changing climate, land use, and agronomic practices are driving shifts in weed biology and management across Australia’s grain production systems. A stakeholder survey was conducted to identify key weed species, adaptations, and factors influencing future research priorities in three major cropping regions. The most problematic and adaptive species included rigid ryegrass (Lolium rigidum Gaud.), hairy fleabane (Erigeron bonariensis L.), Bromus spp. (includes both Bromus diandrus Roth and Bromus rigidus Roth), annual sowthistle (Sonchus oleraceus L.), wild radish (Raphanus raphanistrum L.), and feather fingergrass (Chloris virgata Sw.). These weeds also ranked high for future research focus. Observed adaptive traits included changes in dormancy, emergence patterns, shifts in phenology, and a shift towards year-round growth driven by warmer winters and increased summer rainfall. Regional responses varied slightly, with soil and crop management practices ranked as the primary driver of changing weed biology (88%), followed by climatic factors (56%), while soil factors (13%) were not considered as significant. Participants in the Northern region highlighted climate change (67%) as a major driver, while those in the Western region emphasized management practices (95%) and soil-related factors (32%). Sixty percent of participants noted that climatic changes were introducing new weeds, and 69% believed that changing weed biology was reducing control efficacy. National research priorities included understanding weed emergence dynamics (73%), effects of climate on herbicide efficacy (71%), and better understanding of weed ecology (68%). These findings highlight the trends and need for future research on changing weed biology and adaptive management strategies. Surveys of agronomists, farm advisors, researchers, and farmers provide a cost-effective method to monitor new weed adaptations. Refining survey methodologies and enhancing field data collection could improve the ability to track and manage weed adaptations to shifts in climate and management practices.

Combine modifications for harvest weed seed control, like the Redekop Seed Control Unit (SCU) and the integrated Harrington Seed Destructor (iHSD), have been successfully used to kill problematic weed seeds in small grain production in Australia. These seed impact mills could have a fit in US soybean [Glycine max (L.) Merr.] production. Testing the seed kill rate of problematic weed species in soybean is important for confirming the efficacy of the mills. Additionally, the mills may be affected by changes in crop yield and harvest residue moisture as they can have an impact on chaff flow rate and chaff moisture, respectively. This research aimed to determine the seed kill percent for problematic weeds and how varying chaff flow rates and chaff moisture content in soybean chaff affect the seed kill rate and horsepower draw of two different impact mills, the Redekop SCU and the iHSD. All testing was conducted using stationary test stands. Chaff flow rate and chaff moisture levels tested ranged from 0.5x to 2x standard combine throughput and 11.7%-28.6% moisture, respectively. All tested species were killed at >98% by both mills. Increasing chaff flow rate resulted in a decrease in seed kill for all tested species with the iHSD and only common ragweed (Ambrosia artemisiifolia L.) with the Redekop SCU. Increasing chaff moisture only resulted in a decrease in seed kill for Palmer amaranth (Amaranthus palmeri S. Watson) with the iHSD. Data evaluating the horsepower needed to power the mills also indicated that chaff flow rate and chaff moisture resulted in a significant increase in horsepower draw. With generally high kill rates (>98%) and the ability to kill weed seeds at >98% in less-than-ideal harvest conditions (i.e. high moisture chaff), seed impact mills could be used in soybean production to reduce weed seed inputs into the soil seedbank during harvest.

The widespread distribution of wolf poison (Stellera chamaejasme L.), spanning from southern Russia to southwestern China and the western Himalayas, contributes to its prevalence as an invasive species in grassland ecosystems. Its extensive range, coupled with its ability to thrive in harsh environments, enables it to rapidly colonize grasslands. Once established, it rapidly spreads and dominates large areas. This process inevitably leads to grassland degradation over time, thereby exerting significant impacts on both ecology and economy. In China, grasslands (26.45 million hectares, 27.5% of land area) face severe degradation, with over 90% impacted by overgrazing and climate change. S. chamaejasme infestations exceed 1.4 million hectares in Qinghai, 546,700 in Gansu, and 133,000 in Inner Mongolia, causing annual forage losses of 137.5 million kg and economic damages of 15–20 million yuan in Gansu alone. These impacts threaten ecosystem stability and pastoral livelihoods. Therefore, research on the spread mechanisms of invasive plants is crucial. In this comprehensive description, we investigated the effects of S. chamaejasme on plant communities and herbivore interactions. Our research showed how this species successfully invades grasslands and establishes itself as a dominant species. S. chamaejasme enhances Its expansion alters soil physicochemical properties, reduces nutrient cycling, and increases pathogenic fungi abundance while enhancing microbial diversity, creating self-favoring soil conditions. With high genetic diversity, robust reproductive capacity, and potent allelopathic effects, it suppresses neighboring vegetation and escapes herbivory due to toxicity, accelerating invasion. These interrelated traits facilitate the rapid invasion and spread of S. chamaejasme on grasslands, ultimately leading to its dominance. This trend poses a significant threat to the health and stability of the grassland ecosystem. Future research should delve into the ecological adaptability and allelopathic mechanisms of S. chamaejasme, aiming to develop effective management strategies for controlling its spread and promoting grassland recovery and biodiversity conservation.

A three-way transgenic sugarbeet cultivar, engineered for resistance to glyphosate, glufosinate, and dicamba (referred to as ‘triple-stacked,’ henceforth), is anticipated to be commercialized by mid-2020s. While offering potential benefits for growers facing glyphosate resistance, two of three herbicides (dicamba and glyphosate) to be utilized with triple-stacked sugarbeet (Beta vulgaris L.) have previously been used on major weeds in western United States cropping systems, raising concerns about pre-existing resistance to these active ingredients. We conducted a field survey in sugarbeet-growing counties of South-East Montana and North-West Wyoming in fall 2021, prior to the sugarbeet harvest. We collected kochia [Bassia scoparia (L.) A. J. Scott], redroot pigweed (Amaranthus retroflexus L.), and common lambsquarters (Chenopodium album L.) populations and screened them for glyphosate, glufosinate, and dicamba resistance in greenhouse conditions. Our results showed two-way resistance (glyphosate and dicamba) in 32% of B. scoparia populations and 78% populations of C. album with reduced susceptibility to glyphosate. Additionally, we conducted a greenhouse experiment to assess the emergence patterns of collected populations. Phylogenetically closely related B. scoparia and C. album showed higher resemblance in emergence pattern than distant relative A. retroflexus. While the majority of B. scoparia and C. album populations emerged in <20 day(s) (d) [time required to reach 90% emergence (E90) < 20 d], A. retroflexus populations required >30 d to reach E90. Widespread glyphosate and dicamba resistance in B. scoparia populations raises concerns about the long-term feasibility of a triple-stacked sugarbeet cultivar. Furthermore, the delayed emergence of A. retroflexus may enable it to evade early-season weed management.

Interseeding alfalfa (Medicago sativa L.) into corn (Zea Mays L.) is a novel approach that increases the production of high-quality forage and reduces the risk of nutrient and soil loss from cropland. Annual grass weeds like yellow foxtail [Setaria pumila (Poir.) Roem. & Schult.] can reduce the success of alfalfa establishment and are difficult to manage in the interseeding system. This study evaluated ground cover, fall biomass, and fall plant density of interseeded alfalfa in response to varying populations of S. pumila. Our goal was to identify a threshold for initiating control of annual grasses to ensure good establishment of alfalfa in this intercropping system. Groundcover of interseeded alfalfa growing under corn declined as S. pumila density increased from 0 to 125 plants m-2 in July, August and October with the sharpest decline in August (up to a 70% reduction in alfalfa cover). This reduction in groundcover was associated with a decline in post-establishment shoot and root mass and a reduction in alfalfa plant density from 246 to 146 plants m-2 in October. Results suggest that June S. pumila populations should be kept < 50 plants m-2 to obtain recommended fall alfalfa densities of 200 plants m-2 that are needed to maximize alfalfa yield the following year. This research provides crucial information to practitioners on when annual grass management is needed to ensure successful alfalfa establishment in this interseeded system.

Yellow nutsedge (Cyperus esculentus L.) is one of the most problematic weeds in turfgrass due to its fast growth rate and high tuber production. Effective long-term control relies on translocation of systemic herbicides to underground tubers. Two identical trials were conducted simultaneously in separate greenhouses to evaluate the effect of several acetolactate synthase (ALS)- and protoporphyrinogen oxidase (PPO)-inhibiting postemergence herbicides on C. esculentus tuber production and viability. Seven tubers were planted into 1-L pots, and plants were allowed to mature for 6 wk before trial initiation. Treatments included pyrimisulfan at 73 g ai ha−1 once or 49 g ai ha−1 twice, imazosulfuron at 736 g ai ha−1 once or 420 g ai ha−1 twice, carfentrazone-ethyl + sulfentrazone at 22 + 198 g ai ha−1 once or 14 + 127 g ai ha−1 twice, halosulfuron at 70 g ai ha−1 once or 35 g ai ha−1 twice, and a nontreated control. Sequential applications were made 3 wk after initial treatment (WAIT) for both trials. Both single and sequential applications of carfentrazone-ethyl + sulfentrazone exhibited the quickest control (80% to 83% 4 WAIT). Two applications of imazosulfuron resulted in the greatest reduction in tuber number (81%) and tuber dry biomass (85%), while one application of carfentrazone-ethyl + sulfentrazone resulted in the greatest reduction in shoot biomass (71%). The viability of tubers that were recovered from each pot was reduced 48% to 70%, with the greatest reduction in response to carfentrazone-ethyl + sulfentrazone. Although two applications of pyrimisulfan only resulted in tuber number and shoot biomass reductions of 66% and 38%, respectively, tuber dry biomass reduction was 80%. Therefore, pyrimisulfan, imazosulfuron, halosulfuron, and carfentrazone-ethyl + sulfentrazone are all viable options for long-term C. esculentus control in turfgrass.

Kochia [Bassia scoparia (L.) A.J. Scott] is an invasive tumbleweed in the North American Great Plains that is difficult to manage in croplands and ruderal areas due to widespread resistance to up to four herbicide sites of action, including auxin mimics (Herbicide Resistance Action Committee [HRAC] Group 4) and inhibitors of acetolactate synthase (HRAC Group 2), photosystem II (HRAC Group 5), and 5-enolpyruvylshikimate-3-phosphate synthase (HRAC Group 9). Poor B. scoparia control with protoporphyrinogen oxidase (PPO)-inhibiting (HRAC Group 14) herbicides was noted in a brown mustard [Brassica juncea (L.) Czern.] field near Kindersley, SK, Canada, in 2021. Similar observations were made in a sunflower (Helianthus annuus L.) field near Mandan, ND, USA, and in research plots near Minot, ND, USA, in 2022. Whole-plant dose–response experiments were conducted to determine whether these B. scoparia accessions were resistant to the PPO-inhibiting herbicides saflufenacil and carfentrazone and the level of resistance observed. All three B. scoparia accessions were highly resistant to foliar-applied saflufenacil and carfentrazone compared with two locally relevant susceptible accessions. The Kindersley accession exhibited 57- to 87-fold resistance to saflufenacil and 97- to 121-fold resistance to carfentrazone based on biomass dry weight at 21 d after treatment (DAT). Similarly, the Mandan accession exhibited 204- to 321-fold resistance to saflufenacil and 111- to 330-fold resistance to carfentrazone, while the Minot accession exhibited 45- to 71-fold resistance to saflufenacil and 88- to 264-fold resistance to carfentrazone. Substantial differences in visible control at 7 and 21/28 DAT were also observed between the putative-resistant and susceptible accessions. This study represents the first confirmations of PPO inhibitor–resistant B. scoparia globally and the fifth herbicide site of action to which B. scoparia has evolved resistance. It also documents this issue present at three locations in the Northern Great Plains region that occur up to 790 km apart and on both sides of the Canada/U.S. border.

Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] is a dominant weed species occurring in rice (Oryza sativa L.) 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, China. 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 the 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 acetyl-CoA carboxylase (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-nitrobenzoxadiazole 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 integrated into glyphosate-resistant soybean [Glycine max (L.) Merr.] (e.g., dicamba or 2,4-D choline). These new soybean 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 the 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 was 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 where 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.

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 (UASs) 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 (Zea mays L.) yield loss based on weed–crop leaf cover ratios. A yield loss model for maize was evaluated for accuracy using 15- and 30-m-altitude aerial red–green–blue 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 3,000 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 root mean-square error 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 before canopy closure, making it possible for growers to plan production and financial decisions before the end of the growing season.

Johnsongrass [Sorghum halepense (L.) Pers.], 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 this plant species’ abundance temporarily, but are typically followed by S. halepense reestablishment. Sorghum 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.

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.

Weed infestations have been identified as a major cause of yield reductions in canola (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 canola cultivation, particularly emphasizing the prevalence and impact of wild oat (Avena fatua L.) as the dominant weed species in canola 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 RF, BRT, and 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 A. fatua 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 canola productivity and mitigating the ecological impacts associated with weed infestation.

Carolina geranium (Geranium carolinianum L.) growth in planting holes in commercial strawberry [Fragaria × ananassa (Weston) Duchesne ex Rozier (pro sp.) [chiloensis × virginiana]] fields is a serious problem in Florida. This study aimed to evaluate the effects of different G. carolinianum densities on strawberry growth and yield in plasticulture production systems. Geranium carolinianum densities were 0, 0.4, 0.8, 1.9, 2.7, and 3.8 plants m−2 equally distributed on the plastic-mulched bed top within the planting holes. Geranium carolinianum density did not affect plant height; however, seed production and season-end biomass were negatively correlated with density in Season I. There was a negative, linear correlation between weed density and berry yields. With each increase in G. carolinianum per square meter, the total annual yield was lowered by 554 and 935 kg ha−1, in Seasons I and II, respectively. Our data clearly indicate that G. carolinianum emerging in the transplant holes of strawberry and competing throughout the season has a significantly negative effect on total berry yield.

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 that 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 28/15 C (day/night), 30/20 C, and 35/25 C 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 percentage of germinated seed) and germination index (sum of the ratio of germinated seeds to the corresponding days) increased with increasing temperatures. At 28/15 C, the average percentage germination of EC populations (67.5%) was significantly (P < 0.05) higher compared with ECM (46.4%) and EG (43.7%); GD50 (duration for 50% total germination) for EC populations (5.2 d) was significantly shorter compared with ECM (5.9 d) and EG (5.8 d). At 35/25 C, the percentage germinations 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 30/20 C and 35/25 C, the average germination percentages of populations collected from transplanted rice fields were significantly higher than those 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.

Trifludimoxazin is a protoporphyrinogen oxidase (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 resistant/susceptible (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 PPO-R 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 composed 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 3 site-years, applications of 25 g ai ha−1 trifludimoxazin resulted in 95% control of A. tuberculatus at 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 with other commercial PPO inhibitors, even in populations where low frequencies of PPO-R 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 suggest that trifludimoxazin may be a valuable herbicide in an integrated approach for managing herbicide-resistant Amaranthus weeds.

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 before or following application. Additionally, climate models suggest more extreme weather will become the norm, further expanding the weather range to which glufosinate can be exposed. 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 postemergence application of glufosinate applied to waterhemp [Amaranthus tuberculatus (Moq.) Sauer], morningglory species (Ipomoea spp.), and/or giant foxtail (Setaria faberi Herrm.) <15 cm 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 5 d before glufosinate application was detrimental to the probability of successful control of A. tuberculatus and S. faberi. Lower relative humidity (≤70%) and solar radiation (≤23 MJ m−1 d−1) on 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 5 d after application was ≤25 C. As climate continues to change and become more variable, the risk of unacceptable control of several common species with glufosinate is likely to increase.