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

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

Opportunistic use of limited resources is often attributed to invasive species, and as a mature vine, old man’s beard (Clematis vitalba L.) is known to have devastating negative impacts on the trees it colonizes. No previous experimental studies have been published on how easily C. vitalba seedlings can colonize ground covered by other established vegetation. This species has had an increasing presence in forestry blocks and riparian zones in New Zealand, both of which usually maintain some grass cover. To determine the importance of vegetative ground cover for preventing ingress of new C. vitalba plants, this study looked at seedling emergence through the soil and establishment of C. vitalba within four different levels of grassy cover at three sites: (1) ground kept bare after vegetation removal; (2) ground bare at C. vitalba seed sowing, but thereafter allowed to recover; (3) vegetative cover trimmed to 4 cm high at C. vitalba sowing, and then allowed to recover; and (4) unmanaged vegetation. At the highest level of vegetation density (unmanaged vegetation), no C. vitalba seedlings were ever detected throughout a 1-yr monitoring period. At lower ground cover densities, poor seedling emergence was observed, with a maximum of 36% of seeds sown in bare plots producing a seedling. Also, seedlings did not survive past 1 yr, except in bare plots or in plots where vegetation grew sparsely. However, seedlings that did survive began producing multiple stems within 6 mo of emergence. These results indicate that obstacles to seedling emergence and poor development at the young seedling stage when vegetative cover is dense severely limit C. vitalba’s chances to invade new sites via seed. Yet some successful seedling recruitment does occur due to the magnitude of the propagule pressure on the landscape and the difficulty of maintaining high-density ground cover across large areas throughout the year.

Goosegrass [Eleusine indica (L.) Gaertn.] is one of the most problematic weeds in plasticulture strawberry [Fragaria × ananassa (Weston) Duchesne ex Rozier (pro sp.) [chiloenis × virginiana]] production systems in Florida. A 2-yr trial was implemented to evaluate the effects of different E. indica densities on strawberry growth and yield. Eleusine indica densities evaluated 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 strawberry transplant holes. Eleusine indica density did not affect E. indica height or biomass. However, E. indica seed production was positively correlated with E. indica density in Season 1 and negatively correlated with E. indica density in Season 2. A negative linear regression was observed between E. indica density and strawberry yield in both seasons. For each increase in E. indica plants per square meter, strawberry yield was reduced by 316 and 2,356 kg ha−1 for Seasons 1 and 2, respectively. Our results highlight the importance of achieving adequate E. indica management to minimize yield losses.

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

Automatic detection and removal of weeds is a challenging task that requires precise sensors. While crops and weeds possess similar features in terms of appearance, they can be discriminated based on spectral information. This can be done because any object has its own specific spectral signature based on its physical structure and chemical contents. This study examined the use of wavelet transform and deep learning for discrimination of weeds from crops. A total of 626 spectral reflectances in the range of 380 to 1,000 nm were obtained for three crops (cucumber [Cucumis sativus L.], tomato [Solanum lycopersicum L.], and bell pepper [Capsicum annuum L.]) and five different weeds (bindweed [Convolvulus spp.], purple nutsedge [Cyperus rotundus L.], narrowleaf plantain [Plantago lanceolata L.], common cinquefoil [Potentilla simplex Michx.], and garden sorrel [Rumex acetosa L.]). Morse wavelet was employed to decompose the spectra and extract the scalograms, which are the RGB representations of the spectral data. Two deep convolutional neural networks (i.e., GoogLeNet and SqueezNet) were employed for the recognition of crops and weeds. In addition, six common classifiers, including linear discriminant analysis, quadratic discriminant analysis, linear support vector machine, quadratic support vector machine, artificial neural networks, and k-nearest neighbors classifier (KNN), were used for the task of crop/weed discrimination to build the comparison with the proposed method. The error of prediction gradually decreased, and a 100% correct classification was achieved after 258 iterations. Analysis showed that SqueezNet provided classification of 100% accuracy, while GoogLeNet’s accuracy was 97.8% for the test set. Among the common classifiers, KNN provided the highest accuracy (i.e., 100%). This study showed that the proposed method can be successfully utilized for classification of crops and weeds.

Mounting cases of herbicide-resistant waterhemp [Amaranthus tuberculatus (Moq.) Sauer] in the U.S. Midwest have renewed the interest in nonchemical weed management strategies. Field experiments were conducted in 2021 and 2022 to quantify the effectiveness of a commercial combine equipped with a seed impact mill in preventing A. tuberculatus seed return to the soil seedbank in soybean [Glycine max (L.) Merr.]. Amaranthus tuberculatus seed shattering before crop harvest was quantified. Amaranthus tuberculatus started shattering seeds during the last week of August in both years. Overall, 51% of A. tuberculatus seeds were retained on the plant at harvest on October 23, 2021, compared with 61% at harvest on October 7, 2022. Viability of shattered A. tuberculatus seeds ranged from 84% to 94%. Additional seed shattering occurred when plants were disturbed by the combine header during soybean harvest, which caused 15% and 9% shattering in 2021 and 2022, respectively. Amaranthus tuberculatus seeds passed through the impact mill were grouped in three categories: no damage, moderate damage, and severe damage. In 2021, A. tuberculatus seeds with moderate damage had 26% lower germination and viability than seeds with no visible damage. In 2022, seed germination and viability of no-damage seeds did not differ from seeds with a moderate level of damage. No severely damaged seed germinated or tested viable in either year. Altogether, impact mill treatment reduced the number of germinable seeds by 87% compared with the no–impact mill treatment. These results indicate that seed impact mills can be a useful tool in Iowa soybean production to help manage multiple herbicide–resistant A. tuberculatus populations. However, A. tuberculatus seed shattering before crop harvest reduces the overall effectiveness of seed impact mills in preventing seedbank replenishments.

Weedy rice (Oryza sativa f. spontanea Auct. ex Backer) is a troublesome annual weed from the Gramineae family and infests rice (Oryza sativa L.) fields globally, with a notable presence in China. However, limited information is available regarding the effects of diverse environmental factors on its germination and emergence. A better understanding of the seed biology and ecology of weedy rice is crucial for developing effective weed management strategies. Experiments were conducted to evaluate the effects of temperature, light, soil burial depth, wheat (Triticum aestivum L.) crop residue amount, salt stress, osmotic stress, and radiant heat on the germination and seedling emergence of weedy rice. Weedy rice exhibited robust germination (>98%) when exposed to varying day/night temperatures (20/15 to 35/30 C) and remained unaffected by light conditions. Seedling emergence was not influenced within the top 5-cm soil layer, where 100% of the seedlings emerged. However, emergence decreased as the soil burial depth increased, eventually resulting in no emergence from a burial depth of 11 cm. The soil burial depth required for 50% of the maximum emergence was 8.3 cm. Seedling emergence ranged from 97% to 100% across different amounts of the wheat straw residue cover (0 to 10,000 kg ha−1). The sodium chloride concentration and osmotic potential required for 50% were 230.8 mM and −0.5 MPa, respectively. No germination was observed when weedy rice seeds were exposed to >110 C pretreatment (radiant heat for 5 min), indicating that residue burning could reduce infestation of weedy rice. The insights gained from this study contribute valuable knowledge to enhance the integrated management of weedy rice in China.

The Amaranthus genus contains numerous agronomic weedy species that are widely distributed across the United States. The seeds of many Amaranthus species are morphologically indistinguishable. The Minnesota Department of Agriculture declared Palmer amaranth (Amaranthus palmeri S. Watson) a prohibited noxious weed seed in 2016. Any Amaranthus spp. seeds that are identified as contaminants during routine seed testing require genetic testing to determine whether A. palmeri is present. This research aimed to validate and optimize the molecular detection of A. palmeri in seed. We refined the DNA extraction from pools of Amaranthus spp. seeds ranging in size from 1 to 100 seeds to improve sample testing throughput. Real-time polymerase chain reaction (qPCR) using primers developed by Murphy and colleagues correctly identified the presence of A. palmeri genetics in 84 samples containing 0, 1, 2, 25, or 50 A. palmeri seeds in samples containing up to 100 seeds. The method specificity was examined using 17 Amaranthus species and 4 hybrids of unknown genetics. The Murphy regular qPCR cycle amplified Watson’s amaranth (Amaranthus watsonii Standl.), spleen amaranth (Amaranthus dubius Mart. ex Thell.), and spiny amaranth (Amaranthus spinosus L.), which would result in false-positive calls; however, the fast cycle only identified A. watsonii as a potential false positive. Examination of the Murphy primer binding site revealed an identical sequence for A. palmeri and A. watsonii. Additional markers were evaluated and optimized for use in qPCR to eliminate the risk of a false positive. The additional markers did eliminate the amplification of A. dubius and A. spinosus but did not eliminate the amplification for A. watsonii. Currently, A. watsonii is not known to be distributed outside of its limited native range and is not expected to be encountered in samples.

Pollinators risk exposure to insecticide residue when visiting weedy flowers in urban landscapes. Previous research shows that pollinators are routinely exposed to a variety of pesticides, but herbicides have exhibited minimal toxicity and did not contribute to the modeled risk quotients. Herbicides from different modes of action may deter pollinators from visiting turfgrass weeds, but their temporal influence on floral quality and pollinator foraging is unaddressed. Research experiments were conducted at Blacksburg, VA, in 2023 to assess the effect of four herbicides on floral morphology and ultraviolet (UV) reflectance of three different UV floral classes of weeds and associated pollinator foraging visits. Among 1,080 assessments per weed species, honeybees (Apis mellifera), bumble bees (Bombus spp.), solitary bees (Chelostoma florisomne), and flies (Diptera spp.) accounted for 94%, 2%, 3%, and 1%, respectively, of the total pollinator visitations on white clover (Trifolium repens L.) inflorescences; 71%, 2%, 0%, and 27%, respectively, on dandelion (Taraxacum officinale F.H. Wigg.) flowers; and 0%, 0%, 78%, and 22%, respectively, on bulbous buttercup (Ranunculus bulbosus L.) flowers. Pollinator visitation and floral quality were temporarily affected by herbicide application, with some herbicides eliminating food resources, while others transiently impacted floral quality and density. The combination of 2,4-D + dicamba + MCPP and topramezone eliminated pollinator foraging visits, but on differing temporal scales of 3 d for auxins and 14 d for topramezone. Halosulfuron and sulfentrazone transiently suppressed floral quality and density, with varying degrees of deterrence on pollinators depending on the weed species. All evaluated herbicides reduced radiometric UV reflectance of T. officinale petal apices, but only synthetic auxin and topramezone reduced digitally assessed floral UV-reflecting area. Petal UV reflectance appears to contribute but not solely influence pollinator foraging behavior. UV-absorbing and UV-reflecting flowers differed in UV-reflectance response to herbicides, but pollinators were similarly deterred. Results suggest that herbicides may offer a variety of management solutions to pollinator deterrence in areas slated for insecticide treatment, including long-term or transient deterrence with potential food-resource preservation.

Purple nutsedge (Cyperus rotundus L.) is one of the world’s resilient upland weeds, primarily spreading through its tubers. Its emergence in rice (Oryza sativa L.) fields has been increasing, likely due to changing paddy-farming practices. This study aimed to investigate how C. rotundus, an upland weed, can withstand soil flooding and become a problematic weed in rice fields. The first comparative analysis focused on the survival and recovery characteristics of growing and mature tubers of C. rotundus exposed to soil-flooding conditions. Notably, mature tubers exhibited significant survival and recovery abilities in these environments. Based on this observation, further investigation was carried out to explore the morphological structure, nonstructural carbohydrates, and respiratory mechanisms of mature tubers in response to prolonged soil flooding. Over time, the mature tubers did not form aerenchyma but instead gradually accumulated lignified sclerenchymal fibers, with lignin content also increasing. After 90 d, the lignified sclerenchymal fibers and lignin contents were 4.0 and 1.1 times higher than those in the no soil-flooding treatment. Concurrently, soluble sugar content decreased while starch content increased, providing energy storage, and alcohol dehydrogenase activity rose to support anaerobic respiration via alcohol fermentation. These results indicated that mature tubers survived in soil-flooding conditions by adopting a low-oxygen quiescence strategy, which involves morphological adaptations through the development of lignified sclerenchymal fibers, increased starch reserves for energy storage, and enhanced anaerobic respiration. This mechanism likely underpins the flooding tolerance of mature C. rotundus tubers, allowing them to endure unfavorable conditions and subsequently germinate and grow once flooding subsides. This study provides a preliminary explanation of the mechanism by which mature tubers of C. rotundus from the upland areas confer flooding tolerance, shedding light on the reasons behind this weed’s increasing presence in rice fields.

Effective pesticide application is dependent on precise and sufficient delivery of active ingredients to targeted pests. Water-sensitive papers (WSPs) have been used to estimate the stain coverage, droplet density, droplet size, total spray volume, and other spray-quality metrics by analyzing deposit stains using image analysis software. However, because WSPs are expensive, they are typically distributed along unidimensional transects at intervals of 0.5 m or more, which comprises 0.5% or less of the total treated area. This might limit the ability to accurately represent the deposition of agricultural sprayers with irregular patterns, such as agricultural drone sprayers in the early developmental stage. This study introduces a novel approach utilizing white Kraft paper and a blue colorant proxy for assessing spray deposition. A custom Python-based image analysis tool, SprayDAT (Spray Droplet Analysis Tool), was developed and compared with traditional image analysis software, DepositScan. Both models showed increased accuracy in detecting larger objects, with SprayDAT generally performing better for smaller droplets. DepositScan underestimated the total deposited spray volume by up to 2.7 times less compared with the colorant extraction assessed via spectrophotometry and the predicted output based on flow rate, coverage, and speed. Accuracy of software-estimated spray volume declined with increasing total stain coverage, likely due to overlapping stain objects. Droplet density exhibited a Gaussian trend, with peak density at approximately 22% stain cover, offering evidence for overlapped stains for both DepositScan and SprayDAT as stain cover increased. Both models showed exponential growth in volumetric median diameter (VMD) with increasing stain cover. SprayDAT is freely accessible through an online repository. It features a user-friendly interface for batch processing large sets of scanned images and offers versatility for customization to meet individual needs, such as adjusting spread factor, updating the standard curve for spray volume estimation, or modifying the stain detection threshold.

Agricultural spray drone (ASD) use in managed turfgrass has been given limited attention in the scientific literature. Further, deposition patterns of ASD spray have been obscured in previous research by ambient wind, crop canopy interference, and limited sampling resolution. Using a continuous sampling method involving blue colorant and water sprayed over white Kraft paper that was assessed via digital image analysis of stain objects and referenced spectrophotometric analysis of extractant, deposition metrics were estimated across a 29.3-m transect perpendicular to an ASD or ground-sprayer spray swath. The ASD applies very fine droplets that are highly concentrated with herbicide, similar to ultra–low volume treatments, that improved smooth crabgrass [Digitaria ischaemum (Schreb.) Schreb. ex Muhl.] control compared with a ground sprayer when the ASD was operated 2 m above the turf. Unfortunately, these very fine droplets also drift, leading to four times greater droplet density at distance of almost 12 m away from the targeted spray swath following an operational height of 10 m compared with 2 m. As ASD operational height increases, drift and effective swath width at 30% coefficient of variation uniformity increases, while effective application rate, total deposition, and D. ischaemum control by quinclorac herbicide decreased. Total deposition decreased 6% for each meter increase in ASD operational height, likely due to evaporation. The potential losses due to evaporation are a serious consideration for ASD use that has received little attention in the scientific literature. Our data suggest that ASD operational height should be as low as possible, but modification of spray systems may be needed to improve homogeneity of spray pattern.

The resistance to fenoxaprop-P-ethyl, a herbicide that inhibits acetyl-CoA carboxylase (ACCase), has emerged in shortawn foxtail (Alopecurus aequalis Sobol.) since the 1990s, presenting a considerable challenge to wheat (Triticum aestivum L.) production in China. One of the primary mechanisms responsible for this high-level resistance is the presence of mutations at codons 1781, 2041, and 2078 in the ACCase gene. However, the conventional methods used to detect these mutations, such as polymerase chain reaction (PCR) and gene sequencing, are time-consuming and labor-intensive. To address this issue and enable the prompt and effective detection of these common ACCase mutations in A. aequalis, a loop-mediated isothermal amplification (LAMP) strategy was developed. The LAMP assay specifically targets the Ile-1781-Leu and Asp-2078-Gly mutations within the ACCase gene of A. aequalis. Through the optimization of primers, systems, and conditions, the LAMP assay enables rapid differentiation between wild-type individuals and mutants of A. aequalis carrying either of these two mutations. Including SYBR Green I dye in the final reaction mixtures enables detection of the target mutation through a noticeable color change that can be observed with the naked eye. It is noteworthy that the sensitivity of the LAMP assay was approximately 104-fold greater than that of conventional PCR methods. Additionally, a derived cleaved amplified polymorphic sequence (dCAPS) assay was established for each mutation to distinguish between homozygous and heterozygous mutants. Overall, the developed LAMP assay could efficiently detect the Ile-1781-Leu and Asp-2078-Gly mutations in the ACCase gene of A. aequalis, offering significant advantages for the monitoring and management of fenoxaprop-P-ethyl resistance.

Herbicide drift to sensitive crops can result in significant injury, yield loss, and even crop destruction. When pesticide drift is reported to the Georgia Department of Agriculture (GDA), tissue samples are collected and analyzed for residues. Seven field studies were conducted in 2020 and 2021 in cooperation with the GDA to evaluate the effect of (1) time interval between simulated drift event and sampling, (2) low-dose herbicide rates, and (3) the sample collection methods on detecting herbicide residues in cotton (Gossypium hirsutum L.) foliage. Simulated drift rates of 2,4-D, dicamba, and imazapyr were applied to non-tolerant cotton in the 8- to 9-leaf stage with plant samples collected at 7 or 21 d after treatment (DAT). During collection, plant sampling consisted of removing entire plants or removing new growth occurring after the 7-leaf stage. Visual cotton injury from 2,4-D reached 43% to 75% at 0.001 and 0.004 kg ae ha−1, respectively; for dicamba, it was 9% to 41% at 0.003 or 0.014 kg ae ha−1, respectively; and for imazapyr, it was 1% to 74% with 0.004 and 0.03 kg ae ha−1 rates, respectively. Yield loss was observed with both rates of 2,4-D (11% to 51%) and with the high rate of imazapyr (52%); dicamba did not influence yield. Herbicide residues were detected in 88%, 88%, and 69% of samples collected from plants treated with 2,4-D, dicamba, and imazapyr, respectively, at 7 DAT compared with 25%, 16%, and 22% when samples were collected at 21 DAT, highlighting the importance of sampling quickly after a drift event. Although the interval between drift event and sampling, drift rate, and sampling method can all influence residue detection for 2,4-D, dicamba, and imazapyr, the factor with the greatest influence is the amount of time between drift and sample collection.

Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] is increasingly infesting imidazolinone-tolerant (IMI-T) rice (Oryza sativa L.) fields in China, and E. crus-galli imazamox resistance has become the major concern for weed management in IMI-T rice fields. In this study, the susceptible population JLGY-3 (S) and the suspected resistant population JHXY-2 (R) collected from IMI-T rice fields were used as research subjects. When treated with imazamox, the JHXY-2 (R) population showed a high level of herbicide resistance with a resistance index of 31.2. JHXY-2 (R) was cross-resistant to all five acetolactate synthase (ALS) inhibitors from different chemical families, but sensitive to herbicides inhibiting acetyl-CoA carboxylase. To understand the reason why JHXY-2 (R) was resistant to imazamox, we performed experiments to characterize potential target-site resistance (TSR) and non–target site resistance (NTSR) mechanisms. A Trp-574-Leu amino acid mutation in ALS and low imazamox ALS sensitivity were the main mechanisms underlying imazamox resistance in this JHXY-2 (R) population. There was no significant difference in ALS gene expression and ALS protein abundance between R and S populations. High-performance liquid chromatography–tandem mass spectrometry analysis showed enhanced metabolism of imazamox in JHXY-2 (R), which was in contrast to the results of pretreatment with a metabolic enzyme inhibitor. Treatments with cytochrome P450 monooxygenase/glutathione S-transferase (P450/GST) inhibitors did not alter the resistance level of JHXY-2 (R) against imazamox. Transcriptome sequencing showed that there was almost no significant difference in the expression of P450 and GST metabolic enzyme genes between R and S populations, and only GSTU1 showed a significant upregulation in the R population, further clarifying the NTSR mechanism of JHXY-2 (R). In conclusion, amino acid mutation and higher enzyme activity of ALS are the main causes of imazamox resistance in JHXY-2 (R). However, given the differences in imazamox residues in the leaves of E. crus-galli, there may still be undetectable NTSR mechanisms that are causing imazamox resistance in the R population.

Palmer amaranth (Amaranthus palmeri S. Watson, AMAPA) is one of the most troublesome weeds in North America due to its rapid growth rate, substantial seed production, competitiveness and the evolution of herbicide-resistant populations. Though frequently encountered in the South, Midwest, and Mid-Atlantic regions of the United States, A. palmeri was recently identified in soybean [Glycine max (L.) Merr.] fields in Genesee, Orange, and Steuben counties, NY, where glyphosate was the primary herbicide for in-crop weed control. This research, conducted in 2023, aimed to (1) describe the dose response of three putative resistant NY A. palmeri populations to glyphosate, (2) determine their mechanisms of resistance, and (3) assess their sensitivity to other postemergence herbicides commonly used in NY crop production systems. Based on the effective dose necessary to reduce aboveground biomass by 50% (ED50), the NY populations were 42 to 67 times more resistant to glyphosate compared with a glyphosate-susceptible population. Additionally, the NY populations had elevated EPSPS gene copy numbers ranging from 25 to 135 located within extrachromosomal circular DNA (eccDNA). Label rate applications of Weed Science Society of America (WSSA) Group 2 herbicides killed up to 42% of the NY populations of A. palmeri. Some variability was observed among populations in response to WSSA Group 5 and 27 herbicides. All populations were effectively controlled by labeled rates of herbicides belonging to WSSA Groups 4, 10, 14, and 22. Additional research is warranted to confirm whether NY populations have evolved multiple resistance to herbicides within other WSSA groups and to develop effective A. palmeri management strategies suitable for NY crop production.

Following the application of MCPA/MCPB at 1.7 kg ae ha−1 at a field site near Dresden, ON, Canada, poor control (<50% visible control) of green pigweed (Amaranthus powellii S. Watson) was observed. Amaranthus powellii is a common weed in Ontario crop production, and its evolution of resistance to synthetic auxin herbicides (SAHs) could pose a risk to crop yields. The suspected resistant A. powellii population (R) was used in dose–response and field experiments to determine resistance to SAHs. The objective of these studies was to determine whether this population of A. powellii is resistant to MCPA and cross-resistant to other SAHs. The GR50 (herbicide dose that causes a 50% reduction in plant aboveground biomass) values were determined by fitting plant dry weight data, obtained following application with seven SAHs, to a four-parameter log-logistic equation and were compared between the suspected-resistant (R) population and a known susceptible (S) population of A. powellii. The field trial was conducted in 2017, 2018, 2019, and 2021 in corn (Zea mays L.) and consisted of 11 postemergence SAH treatments. The GR50 values differed between the R and S populations following application with MCPA, aminocyclopyrachlor, dichlorprop-p, and mecoprop, resulting in resistance factors of 4.4, 3.0, 2.5, and 2.4, respectively. In the field study, dicamba and MCPA ester controlled A. powellii 84% and 30%, respectively, at 8 wk after treatment application (WAA). The control of Amaranthus powellii with all SAHs applied POST in corn was poor (<90% visible control) at 8 WAA. Both studies confirmed resistance to SAHs in this population of A. powellii, which will create limitations for farmers aiming to control this weed.

Volunteer corn (Zea mays L.) is a competitive weed in corn-based cropping systems. Scientific literature does not exist about the water use of volunteer corn grown in different crops and irrigation systems. The objectives of this study were to characterize the growth and evapotranspiration (ETa) of volunteer corn in corn, soybean [Glycine max (L). Merr.], and sorghum [Sorghum bicolor (L.) Moench] under center-pivot irrigation (CPI) and subsurface drip irrigation (SDI) systems. Field experiments were conducted in south-central Nebraska in 2021 and 2022. Soil moisture sensors were installed at depths of 0 to 0.30, 0.30 to 0.60, and 0.60 to 0.90 m to track soil water balance and quantify seasonal total ETa. Corn was the most competitive, as volunteer corn had the lowest biomass, leaf area, and plant height compared with the fallow. Soybean was the least competitive with volunteer corn, as the plant height, biomass, and leaf area of volunteer corn in soybean were similar to fallow at 15, 30, 45, and 60 d after transplanting (DATr). Averaged across crop treatments, irrigation type did not affect volunteer corn growth at 15 to 45 DATr. Soil water depletion and ETa were similar across crop treatments with and without volunteer corn, as water was not a limiting factor in this study. The ETa of volunteer corn was the highest in soybean (623 mm), followed by sorghum (622 mm), and corn (617 mm) under CPI. The SDI had higher irrigation efficiency, because without affecting crop yield, it had 3%, 6%, and 8% lower ETa in soybean (605 mm), sorghum (585 mm), and corn (571 mm), respectively. Although soil water use did not differ with volunteer corn infestation, a soybean yield loss of 27% was observed, which suggests that volunteer corn may not compete for moisture under fully irrigated conditions; however, it can impact the crop yield potential due to competition for factors other than soil moisture.

New agronomic practices are emerging in the green cane system to utilize sugarcane (Saccharum officinarum L.) straw for energy cogeneration, which necessitates its removal from the soil surface. This study has three main objectives: (1) evaluate the population dynamics and composition of Jamaican crabgrass (Digitaria horizontalis Willd.) and large crabgrass [Digitaria sanguinalis (L.) Scop.] under different sugarcane straw amounts, with and without herbicide treatment; (2) assess the development of sugarcane under different straw amounts; and (3) determine the amount of sugarcane straw that should be kept on the soil surface after harvest to ensure that it does not compromise the chemical control for Digitaria spp. in ratoon cane in a green cane system. We conducted this research at two experimental sites, one at the beginning and the other during the middle of the harvest season, over a span of 2 yr. Our primary treatments consisted of different amounts of sugarcane straw after harvest on the soil surface (0, 5, 10, and 15 Mg ha−1), while secondary treatments included the herbicide application (sulfentrazone + tebuthiuron for the beginning of harvest season and isoxaflutole + tebuthiuron for the middle of harvest season). The Digitaria spp. exhibited higher density (four times more) and dry matter (two times more) in scenarios with a lower sugarcane straw amount (5 Mg ha−1) on the soil surface and no herbicide application. However, a higher straw amount (15 Mg ha−1) contributed to reduced Digitaria spp. infestation and to improved sugarcane yield. According to this research, it is essential to maintain at least 10 Mg ha−1 of sugarcane straw on the soil surface and remove only 5 Mg ha−1 for energy cogeneration.