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It is well established that dicamba can cause severe injury to soybean that is not resistant to dicamba. Dicamba-resistant (DR) cotton became available in 2015, followed by DR soybean in 2016; in late 2016 came the release of new dicamba formulations approved for topical use in cotton and soybeans. Until this approval, use of dicamba was limited to primarily corn, small grains, range and pasture, and eco-fallow acres. Hence, studies were conducted in 2015 and 2016 to examine off-target movement of two dicamba formulations using non-DR soybean as a bio-indicator. Diglycolamine (DGA) and N,N-Bis(3-aminopropyl)methylamine (BAPMA) dicamba were applied simultaneously at 560 g ae ha–1 in the center of two side-byside 8-ha fields to vegetative glufosinate-resistant soybean. On the same day, a rate response experiment was established encompassing nine different dicamba rates of each formulation. Results from the rate response experiment indicate that soybean is equally sensitive to DGA and BAPMA dicamba. In 2015, a rain event occurring 6 to 8 h after application of the large drift trial probably limited off-target movement by incorporating some of the herbicide into the soil. As a result, secondary drift was less in 2015 than in 2016. However, minimal secondary injury (<5%) occurred 12m farther into DGA dicamba plots in 2015. In 2016, secondary movement was decreased by 72m when BAPMA dicamba was used compared to DGA dicamba. Appreciable secondary movement of both DGA and BAPMA dicamba is possible following in-crop applications of either formulated product to soybean in early to mid-summer. Additionally, the risk for secondary movement of BAPMA dicamba is slightly less than for DGA dicamba. Nomenclature: Dicamba; glufosinate; cotton, Gossypium hirsutum L.; soybean, Glycine max (L.) Merr.

Although agrochemicals protect crops and reduce losses, these chemicals can migrate to non-target environments via run-off and leaching following irrigation or heavy rainfall, where non-target organisms can be exposed to a mixture of water-soluble compounds. This study investigated whether the water-soluble fractions of selected agricultural soils from South Africa contain quantifiable concentrations of four commonly used pesticides, 2,4-dichlorophenoxyacetic acid (2,4-D), atrazine, dicamba and imidacloprid, and whether the aqueous extracts induce effects in vitro. Effects investigated included cytotoxicity using the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] cell viability assay; xenobiotic metabolism using the H4IIE- luc rat hepatoma cell line; and (anti-)androgenic and (anti-)oestrogenic effects were screened for with the human breast carcinoma cell lines MDA-kb2 and T47D-KB luc , respectively. Oxidative stress responses were measured in H4IIE- luc and human duodenum adenocarcinoma (HuTu-80) cells. All extracts of soil induced oxidative stress, while several samples caused moderate to severe cytotoxicity and/or anti-androgenic effects . The herbicide atrazine had the greatest frequency of detection (89%), followed by dicamba (84%), 2,4-D (74%) and imidacloprid (32%). Concentrations of atrazine [2.0 × 10 –1 to 2.1 × 10 2  ng/g, dry mass (dm)] and the neonicotinoid insecticide, imidacloprid (2.0 × 10 1 to 9.7 × 10 1  ng/g, dm), exceeded international soil quality guidelines. Overall, there was no observable trend between the biological effects and pesticides quantified. Nonetheless, the findings of this study show that agricultural soils in South Africa can elicit effects in vitro and contain quantifiable concentrations of polar pesticides. These agrochemicals might pose risks to the health of humans and the environment, but more assessment is necessary to quantify such potential effects.

Mixing ammonium sulfate (AMS) can increase dicamba volatility. Therefore, AMS cannot be used with dicamba products in dicamba-resistant soybean. However, most dicamba products applied in corn are labeled to mix with AMS. The objectives of this study were to evaluate broadleaf weed control with dicamba (DiFlexx®) and dicamba/tembotrione (DiFlexx® DUO) applied alone or with AMS or AMS substitute and their effect on broadleaf weed density and biomass. Field experiments were conducted in Illinois, Missouri, and Nebraska in 2018 and 2019. In Illinois and Nebraska, mixing AMS + crop oil concentrate (COC) with dicamba applied at 1,120 g ae ha–1 increased the control of Palmer amaranth and waterhemp (Amaranthus species) from 78% to 92% and velvetleaf from 73% to 96% compared with dicamba applied alone 14 d after application (DAA); however, Missouri data showed no difference. Mixing AMS + COC with dicamba/tembotrione at 597 and 746 g ai ha–1 did not improve broadleaf weed control 14 DAA at any site compared with dicamba/tembotrione applied alone. Control of Amaranthus species was increased from 82% with dicamba applied at 840 g ae ha–1 to 96% when mixed with AMS + COC 28 DAA in Illinois; however, control was similar to dicamba applied at 1,120 g ae ha–1. Broadleaf weed control did not differ among dicamba or dicamba/tembotrione 28 and 56 DAA in Missouri and Nebraska. Broadleaf weed density decreased from 64 plants m–2 to 24 plants m–2 with dicamba at 1,120 g ae ha–1 with AMS + COC 14 DAA in Nebraska; however, no differences were observed in broadleaf weed density or biomass 56 DAA in any state. The results suggest that dicamba or dicamba/ tembotrione can be applied without AMS or AMS substitute, especially at higher rates, without losing broadleaf weed control efficacy. Nomenclature: Dicamba; dicamba/tembotrione; Palmer amaranth; Amaranthus palmeri S. Watson (AMAPA); velvetleaf; Abutilon theophrasti Medik. (ABUTH); waterhemp; Amaranthus tuberculatus (Moq.) J.D. Sauer (AMATU); corn; Zea mays L.; soybean; Glycine max (L.) Merr.

Pesticide drift has been a concern since the introduction of pesticides. Historical incidences with off-target movement of 2,4-D and dichlorodiphenyltrichloroethane (DDT) have increased our understanding of pesticide fate in the atmosphere following aerial application. More recent incidences with dicamba have brought to light gaps in our current understanding of aerial pesticide movement following ground application. In this paper, we review the current understanding of inversions and other weather and environmental factors that contribute to secondary pesticide movement and raise questions that need to be addressed. Factors that influence volatility and terminology associated with the atmosphere, such as cool air drainage, temperature inversions, and radiation cooling will be discussed. We also present literature that highlights the need to consider the role(s) of wind in secondary drift in addition to the role in physical drift. With increased awareness of pesticide movement and more herbicide-resistant traits available than ever before, it has become even more essential that we understand secondary movement of pesticides, recognize our gaps in understanding, and advance from what is currently unknown. Nomenclature: dicamba; 2, 4-D; dichlorodiphenyltrichloroethane

Dicamba is a moderately volatile herbicide used for post-emergent control of broadleaf weeds in corn, soybean, and a number of other crops. With increased use of dicamba due to the release of dicamba-resistant cotton and soybean varieties, growing controversy over the effects of spray drift and volatilization on non-target crops has increased the need for quantifying dicamba collected from water and air sampling. Therefore, this study was designed to evaluate stable isotope-based direct quantification of dicamba from air and water samples using single-quadrupole liquid chromatography–mass spectrometry (LC–MS). The sample preparation protocols developed in this study utilize a simple solid-phase extraction (SPE) protocol for water samples and a single-step concentration protocol for air samples. The LC–MS detection method achieves sensitive detection of dicamba based on selected ion monitoring (SIM) of precursor and fragment ions and relies on the use of an isotopically labeled internal standard (IS) (D3-dicamba), which allows for calculating recoveries and quantification using a relative response factor (RRF). Analyte recoveries of 106–128% from water and 88–124% from air were attained, with limits of detection (LODs) of 0.1 ng mL−1 and 1 ng mL−1, respectively. The LC–MS detection method does not require sample pretreatment such as ion-pairing or derivatization to achieve sensitivity. Moreover, this study reveals matrix effects associated with sorbent resin used in air sample collection and demonstrates how the use of an isotopically labeled IS with RRF-based analysis can account for ion suppression. The LC–MS method is easily transferrable and offers a robust alternative to methods relying on more expensive tandem LC–MS/MS-based options.

It is well established that soybean that does not contain the dicamba-resistant (DR) trait is highly sensitive to off-target exposure to dicamba. However, there is limited information on the effect of low doses of dicamba plus glyphosate mixtures on dicamba-sensitive soybean—a mixture likely to be used on a vast acreage of dicamba/glyphosate-resistant soybean. The objective of this research was to examine leaf and pod malformation, along with height and yield effects, when dicamba, glyphosate, or a mixture of the two was applied to soybean sensitive to both dicamba and glyphosate at sublethal doses. Field applications were made at three growth stages (R1, R3, and R5) at multiple locations. Two glyphosate rates (1/64 and 1/256 of the labeled rate of 870 g ae ha -1) and two dicamba rates (1/64 and 1/256 of the labeled rate of 560 g ae ha -1) were used. Adding glyphosate to dicamba increased leaf malformation by 6% more than dicamba alone when applied at the R1 soybean growth stage. After R3 applications, pod malformation was 10% greater in treatments containing dicamba and glyphosate than dicamba alone. Applications at R5 showed minimal leaf and pod malformation. Seed from field trials was planted in the greenhouse to evaluate the offspring. The number of offspring plants showing dicamba-like symptomology was not increased with the addition of glyphosate to dicamba. Overall, injury to offspring was similar in dicamba alone and dicamba plus glyphosate treatments; however, the number of plants injured increased when parent plants were exposed to sublethal doses of dicamba at R3 and R5 compared with R1 growth-stage exposure. Vigor was reduced in dicamba-containing treatments, but not glyphosate-alone treatments. Glyphosate addition to dicamba had no effect on vigor of soybean offspring. Although there is increased injury to parent plants when glyphosate is added to dicamba, this research demonstrates that glyphosate does not contribute to the negative effects of dicamba on soybean offspring. Nomenclature: Dicamba; glyphosate; soybean, Glycine max (L.) Merr

The fitness costs that are conferred by herbicide resistance alleles can affect the rate of herbicide resistance evolution within populations. We evaluated the direct fitness costs involved with multiple resistance to dicamba and atrazine (R1 and R2) in Chenopodium album by comparing the performance of multiple-resistant phenotypes to those phenotypes that were only resistant to atrazine (S1 and S2). The R1 and R2 phenotypes were consistently shorter and produced less dry matter than the S1 and S2 phenotypes. The R1 and R2 phenotypes were shown to have lower relative growth rates (RGR) and net assimilation rates (NAR) than the S1 and S2 phenotypes at an early stage of growth. However, there was no significant difference in RGR between the R1 and R2 and, S1 and S2 phenotypes at a later stage of growth, though the R1 and R2 phenotypes still had a lower NAR at this later stage. Further investigations using a neighbouring crop competition approach showed that the R1 and R2 phenotypes were weaker competitors, and exhibited significantly less capacity for vegetative growth compared to the S1 and S2 phenotypes during competition. Overall, the results of this study revealed multiple-resistance to atrazine and dicamba endowed a significant fitness penalty to C. album, and it is possible that the frequency of multiple-resistant individuals would gradually decline once selection pressure from herbicides was discontinued.

Weeds can cause significant yield losses and will continue to be a problem for agricultural production due to climate change. Dicamba is widely used to control weeds in monocot crops, especially genetically engineered dicamba-tolerant (DT) dicot crops, such as soybean and cotton, which has resulted in severe off-target dicamba exposure and substantial yield losses to non-tolerant crops. There is a strong demand for non-genetically engineered DT soybeans through conventional breeding selection. Public breeding programs have identified genetic resources that confer greater tolerance to off-target dicamba damage in soybeans. Efficient and high throughput phenotyping tools can facilitate the collection of a large number of accurate crop traits to improve the breeding efficiency. This study aimed to evaluate unmanned aerial vehicle (UAV) imagery and deep-learning-based data analytic methods to quantify off-target dicamba damage in genetically diverse soybean genotypes. In this research, a total of 463 soybean genotypes were planted in five different fields (different soil types) with prolonged exposure to off-target dicamba in 2020 and 2021. Crop damage due to off-target dicamba was assessed by breeders using a 1–5 scale with a 0.5 increment, which was further classified into three classes, i.e., susceptible (≥3.5), moderate (2.0 to 3.0), and tolerant (≤1.5). A UAV platform equipped with a red-green-blue (RGB) camera was used to collect images on the same days. Collected images were stitched to generate orthomosaic images for each field, and soybean plots were manually segmented from the orthomosaic images. Deep learning models, including dense convolutional neural network-121 (DenseNet121), residual neural network-50 (ResNet50), visual geometry group-16 (VGG16), and Depthwise Separable Convolutions (Xception), were developed to quantify crop damage levels. Results show that the DenseNet121 had the best performance in classifying damage with an accuracy of 82%. The 95% binomial proportion confidence interval showed a range of accuracy from 79% to 84% (p-value ≤ 0.01). In addition, no extreme misclassifications (i.e., misclassification between tolerant and susceptible soybeans) were observed. The results are promising since soybean breeding programs typically aim to identify those genotypes with ‘extreme’ phenotypes (e.g., the top 10% of highly tolerant genotypes). This study demonstrates that UAV imagery and deep learning have great potential to high-throughput quantify soybean damage due to off-target dicamba and improve the efficiency of crop breeding programs in selecting soybean genotypes with desired traits.

Sumatran fleabane (Conyza sumatrensis) is one of the main herbicide-resistant weeds in Brazil posing challenges for soybean management. As an alternative to reduce its interference, genetically modified soybean cultivars resistant to auxinic herbicides, such as 2,4-D and dicamba, have been proposed. This study evaluated the effect of competition between these herbicide-resistant soybeans cultivars and two Sumatran fleabane biotypes: one resistant and the other susceptible to 2,4-D, during two soybean growing seasons. The study was characterized as an incomplete partial additive experiment evaluating weed development (height, number of leaves, dry mass and seed production) and soybean yield. In soybeans resistant to 2,4-D, the application of the herbicide reduced the interference from Sumatran fleabane from 19 to 32% in relation with the number of pods and grain mass. When chemical control was combined with cultural control (soybean presence), weed suppression ranged from 80% to 98%. The application of 2,4-D and coexistence with soybeans reduced the seed production of Sumatran fleabane by 95% to 99% in the presence of herbicide or soybean alone. In the case of soybeans resistant to 2,4-D the resistant biotype caused less interference in grain production compared to the susceptible during both growing seasons. The application of dicamba did not result in any increase in resistant soybean yield. Coexisting with dicamba-resistant soybeans and herbicide application reduced the development of Sumatran fleabane by 88% to 98%. The results underscore the importance of integrated management strategies combining chemical and cultural control methods to suppress the growth and reproduction of Sumatran fleabane. RESUMO: A buva (Conyza sumatrensis) é uma das principais plantas daninhas resistentes a herbicidas no Brasil, representando um desafio para o manejo da soja. Como alternativa para reduzir sua interferência, têm sido propostas cultivares de soja geneticamente modificados com resistência a herbicidas auxínicos, como 2,4-D e dicamba. Este estudo avaliou o efeito da competição entre essas cultivares de soja resistente a herbicidas e dois biótipos de buva: um resistente e o outro suscetível ao 2,4-D, durante duas safras de soja. O estudo foi caracterizado como um experimento aditivo parcial incompleto, avaliando o desenvolvimento da planta daninha (altura, número de folhas, massa seca e produção de sementes) e o rendimento das sojas. Nas sojas resistentes ao 2,4-D, a aplicação do herbicida reduziu a interferência da buva em 19% a 32% em relação ao número de vagens e massa de grãos. Quando o controle químico foi combinado com o controle cultural, a supressão da planta daninha variou de 80% a 98%. A aplicação de 2,4-D e a convivência com a soja reduziram a produção de sementes da buva em 95% a 99% na presença do herbicida ou da soja sozinha. No caso das sojas resistentes ao 2,4-D, o biótipo resistente causou menor interferência na produção de grãos em comparação com o biótipo suscetível durante ambas as safras. A aplicação de dicamba não resultou em aumento do rendimento da soja resistente. A convivência com a soja resistente ao dicamba e a aplicação do herbicida reduziram o desenvolvimento da buva em 88% a 98%. Os resultados ressaltam a importância de estratégias de manejo integrado que combinem métodos de controle químico e cultural para suprimir o crescimento e a reprodução da buva.

Biocides, such as herbicides, are routinely tested for toxicity but not for sublethal effects on microbes. Many biocides are known to induce an adaptive multiple-antibiotic resistance phenotype. This can be due to either an increase in the expression of efflux pumps, a reduced synthesis of outer membrane porins, or both. Exposures of Escherichia coli and Salmonella enterica serovar Typhimurium to commercial formulations of three herbicides—dicamba (Kamba), 2,4-dichlorophenoxyacetic acid (2,4-D), and glyphosate (Roundup)—were found to induce a changed response to antibiotics. Killing curves in the presence and absence of sublethal herbicide concentrations showed that the directions and the magnitudes of responses varied by herbicide, antibiotic, and species. When induced, MICs of antibiotics of five different classes changed up to 6-fold. In some cases the MIC increased, and in others it decreased. Herbicide concentrations needed to invoke the maximal response were above current food maximum residue levels but within application levels for all herbicides. Compounds that could cause induction had additive effects in combination. The role of soxS , an inducer of the AcrAB efflux pump, was tested in β-galactosidase assays with soxS-lacZ fusion strains of E. coli. Dicamba was a moderate inducer of the sox regulon. Growth assays with Phe-Arg β-naphtylamide (PAβN), an efflux pump inhibitor, confirmed a significant role of efflux in the increased tolerance of E. coli to chloramphenicol in the presence of dicamba and to kanamycin in the presence of glyphosate. Pathways of exposure with relevance to the health of humans, domestic animals, and critical insects are discussed. IMPORTANCE Increasingly common chemicals used in agriculture, domestic gardens, and public places can induce a multiple-antibiotic resistance phenotype in potential pathogens. The effect occurs upon simultaneous exposure to antibiotics and is faster than the lethal effect of antibiotics. The magnitude of the induced response may undermine antibiotic therapy and substantially increase the probability of spontaneous mutation to higher levels of resistance. The combination of high use of both herbicides and antibiotics in proximity to farm animals and important insects, such as honeybees, might also compromise their therapeutic effects and drive greater use of antibiotics. To address the crisis of antibiotic resistance requires broadening our view of environmental contributors to the evolution of resistance. Increasingly common chemicals used in agriculture, domestic gardens, and public places can induce a multiple-antibiotic resistance phenotype in potential pathogens. The effect occurs upon simultaneous exposure to antibiotics and is faster than the lethal effect of antibiotics. The magnitude of the induced response may undermine antibiotic therapy and substantially increase the probability of spontaneous mutation to higher levels of resistance. The combination of high use of both herbicides and antibiotics in proximity to farm animals and important insects, such as honeybees, might also compromise their therapeutic effects and drive greater use of antibiotics. To address the crisis of antibiotic resistance requires broadening our view of environmental contributors to the evolution of resistance.