Bibliography Tag: dicamba

Malagoli et al., 2016

Malagoli, C., Costanzini, S., Heck, J. E., Malavolti, M., De Girolamo, G., Oleari, P., Palazzi, G., Teggi, S., & Vinceti, M.; “Passive exposure to agricultural pesticides and risk of childhood leukemia in an Italian community;” International Journal of Hygiene and Environmental Health, 2016, 219(8), 742-748; DOI: 10.1016/j.ijheh.2016.09.015.


BACKGROUND: Exposure to pesticides has been suggested as a risk factor for childhood leukemia, but definitive evidence on this relation and the specific pesticides involved is still not clear.

OBJECTIVE: We carried out a population-based case-control study in a Northern Italy community to assess the possible relation between passive exposure to agricultural pesticides and risk of acute childhood leukemia.

METHODS: We assessed passive pesticide exposure of 111 childhood leukemia cases and 444 matched controls by determining density and type of agricultural land use within a 100-m radius buffer around children’s homes. We focused on four common crop types, arable, orchard, vineyard and vegetable, characterized by the use of specific pesticides that are potentially involved in childhood induced leukemia. The use of these pesticides was validated within the present study. We computed the odds ratios (OR) of the disease and their 95% confidence intervals (CI) according to type and density of crops around the children’s homes, also taking into account traffic pollution and high-voltage power line magnetic field exposure.

RESULTS: Childhood leukemia risk did not increase in relation with any of the crop types with the exception of arable crops, characterized by the use of 2.4-D, MCPA, glyphosate, dicamba, triazine and cypermethrin. The very few children (n=11) residing close to arable crops had an OR for childhood leukemia of 2.04 (95% CI 0.50-8.35), and such excess risk was further enhanced among children aged <5 years.

CONCLUSIONS: Despite the null association with most crop types and the statistical imprecision of the estimates, the increased leukemia risk among children residing close to arable crops indicates the need to further investigate the involvement in disease etiology of passive exposure to herbicides and pyrethroids, though such exposure is unlikely to play a role in the vast majority of cases. FULL TEXT


Shealy et al., 1996

Shealy, Dana B., Bonin, Michael A., Wooten, Joe V., Ashley, David L., Needham, Larry L., & Bond, Andrew E.; “Application of an improved method for the analysis of pesticides and their metabolites in the urine of farmer applicators and their families;” Environment International, 1996, 22(6), 661-675; DOI: 10.1016/s0160-4120(96)00058-x.


As the annual use of pesticides in the United States has escalated, public health agencies have become increasingly concerned about chronic pesticide exposure. However, without reliable, accurate analytical methods for biological monitoring, low-level chronic exposures are often difficult to assess. A method for measuring simultaneously the urinary residues of as many as 20 pesticides has been significantly improved. The method uses a sample preparation which includes enzyme digestion, extraction, and chemical derivatization of the analytes. The derivatized analytes are measured by using gas chromatography coupled with isotope-dilution tandem mass spectrometry. The limits of detection of the modified method are in the high pg/L – low μg/L range, and the average coefficient of variation (CV) of the method was below 20% for most analytes, with approximately 100% accuracy in quantification. This method was used to measure the internal doses of pesticides among selected farmer applicators and their families. Definite exposure and elimination patterns (i.e., an increase in urinary analyte levels following application and then a gradual decrease to background levels) were observed among the farmer applicators and many of the family members whose crops were treated with carbaryl, dicamba, and 2,4-D esters and amines. Although the spouses of farm workers sometimes exhibited the same elimination pattern, the levels of the targeted pesticides or metabolites found in their urine were not outside the ranges found in the general U.S. population (reference range). The farmer applicators who applied the pesticides and some of their children appeared to have higher pesticide or metabolite levels in their urine than those found in the general U.S. population, but their levels were generally comparable to or lower than reported levels in other occupationally exposed individuals. These results, however, were obtained from a nonrandom sampling of farm residents specifically targeted to particular exposures who may have altered their practices because they were being observed; therefore, further study is required to determine if these results are representative of pesticide levels among residents on all farms where these pesticides are applied using the same application techniques. Using this method to measure exposure in a small nonrandom farm population allowed differentiation between overt and background exposure. In addition, the important role of reference-range information in distinguishing between various levels of environmental exposure was reaffirmed. FULL TEXT

Harris et al., 2010

Harris, S. A., Villeneuve, P. J., Crawley, C. D., Mays, J. E., Yeary, R. A., Hurto, K. A., & Meeker, J. D.; “National study of exposure to pesticides among professional applicators: an investigation based on urinary biomarkers;” Journal of Agricultural and Food Chemistry, 2010, 58(18), 10253-10261; DOI: 10.1021/jf101209g.


Epidemiologic studies of pesticides have been subject to important biases arising from exposure misclassification. Although turf applicators are exposed to a variety of pesticides, these exposures have not been well characterized. This paper describes a repeated measures study of 135 TruGreen applicators over three spraying seasons via the collection of 1028 urine samples. These applicators were employed in six cities across the United States. Twenty-four-hour estimates (mug) were calculated for the parent compounds 2,4-D, MCPA, mecoprop, dicamba, and imidacloprid and for the insecticide metabolites MPA and 6-CNA. Descriptive statistics were used to characterize the urinary levels of these pesticides, whereas mixed models were applied to describe the variance apportionment with respect to city, season, individual, and day of sampling. The contributions to the overall variance explained by each of these factors varied considerably by the type of pesticide. The implications for characterizing exposures in these workers within the context of a cohort study are discussed. FULL TEXT

Bohnenblust et al., 2016

Bohnenblust, E. W., Vaudo, A. D., Egan, J. F., Mortensen, D. A., & Tooker, J. F.; “Effects of the herbicide dicamba on nontarget plants and pollinator visitation;” Environmental Toxicology and Chemistry, 2016, 35(1), 144-151; DOI: 10.1002/etc.3169.


Nearly 80% of all pesticides applied to row crops are herbicides, and these applications pose potentially significant ecotoxicological risks to nontarget plants and associated pollinators. In response to the widespread occurrence of weed species resistant to glyphosate, biotechnology companies have developed crops resistant to the synthetic-auxin herbicides dicamba and 2,4-dichlorophenoxyacetic acid (2,4-D); and once commercialized, adoption of these crops is likely to change herbicide-use patterns. Despite current limited use, dicamba and 2,4-D are often responsible for injury to nontarget plants; but effects of these herbicides on insect communities are poorly understood. To understand the influence of dicamba on pollinators, the authors applied several sublethal, drift-level rates of dicamba to alfalfa (Medicago sativa L.) and Eupatorium perfoliatum L. and evaluated plant flowering and floral visitation by pollinators. The authors found that dicamba doses simulating particle drift (≈1% of the field application rate) delayed onset of flowering and reduced the number of flowers of each plant species; however, plants that did flower produced similar-quality pollen in terms of protein concentrations. Further, plants affected by particle drift rates were visited less often by pollinators. Because plants exposed to sublethal levels of dicamba may produce fewer floral resources and be less frequently visited by pollinators, use of dicamba or other synthetic-auxin herbicides with widespread planting of herbicide-resistant crops will need to be carefully stewarded to prevent potential disturbances of plant and beneficial insect communities in agricultural landscapes. FULL TEXT

Oseland et al., 2020

Oseland, E., Bish, M., Steckel, L., & Bradley, K.; “Identification of environmental factors that influence the likelihood of off-target movement of dicamba;” Pest Management Science, 2020, 76(9), 3282-3291; DOI: 10.1002/ps.5887.


BACKGROUND: Commercialization of dicamba-resistant soybean and cotton and subsequent post-emergence applications of dicamba contributed to at least 1.4 and 0.5 million hectares of dicamba-injured soybean in the United States in 2017 and 2018, respectively. This research was initiated to identify environmental factors that contribute to off-target dicamba movement. A survey was conducted following the 2017 growing season to collect information from dicamba applications that remained on the target field and those where dicamba moved. Weather and environmental data surrounding applications were collected and used to identify factors that reduce the likelihood of off-target movement. Soil pH was one factor identified in the model, and field experiments were conducted in 2018 and 2019 to validate the model. Three commercially-available dicamba formulations and one formulation currently in development were applied to soil at five distinct pH values. Sensitive soybean was used as a bioassay plant to detect dicamba volatilization.

RESULTS: Wind speeds the day of and following application, nearest water source to the field, soybean production acreage in the county, and soil pH were identified as factors that influence the likelihood for off-target movement. In the field study, when dicamba was applied to pH-adjusted soil and placed under low tunnels for 72 h, dicamba volatility increased when soil pH decreased as the model predicted. Dicamba choline, which is not commercially available, had reduced volatility compared to other formulations tested.

CONCLUSION: Results of this study identified specific factors that contribute to successful and unsuccessful dicamba applications and should be considered prior to applications.

Qi et al., 2020

Qi, M., Huo, J., Li, Z., He, C., Li, D., Wang, Y., Vasylieva, N., Zhang, J., & Hammock, B. D.; “On-spot quantitative analysis of dicamba in field waters using a lateral flow immunochromatographic strip with smartphone imaging;” Analytical and Bioanalytical Chemistry, 2020, 412(25), 6995-7006; DOI: 10.1007/s00216-020-02833-z.


Dicamba herbicide is increasingly used in the world, in particular’ with the widespread cultivation of genetically modified dicamba-resistant crops. However, the drift problem in the field has caused phytotoxicity against naive, sensitive crops, raising legal concerns. Thus, it is particularly timely to develop a method that can be used for on-the-spot rapid detection of dicamba in the field. In this paper, a lateral flow immunochromatographic strip (LFIC) was developed. The quantitative detection can be conducted by an app on a smartphone, named “Color Snap.” The tool reported here provides results in 10 min and can detect dicamba in water with a LOD (detection limit) value of 0.1 mg/L. The developed LFIC shows excellent stability and sensitivity appropriate for field analysis. Our sensor is portable and excellent tool for on-site detection with smartphone imaging for better accuracy and precision of the results.

Riter et al., 2020

Riter, L. S., Sall, E. D., Pai, N., Beachum, C. E., & Orr, T. B.; “Quantifying Dicamba Volatility under Field Conditions: Part I, Methodology;” Journal of Agricultural and Food Chemistry, 2020, 68(8), 2277-2285; DOI: 10.1021/acs.jafc.9b06451.


Quantitative assessment of the volatility of field applied herbicides requires orchestrated sampling logistics, robust analytical methods, and sophisticated modeling techniques. This manuscript describes a comprehensive system developed to measure dicamba volatility in an agricultural setting. Details about study design, sample collection, analytical chemistry, and flux modeling are described. A key component of the system is the interlaboratory validation of an analytical method for trace level detection (limit of quantitation of 1.0 ng/PUF) of dicamba in polyurethane foam (PUF) air samplers. Validation of field sampling and flux methodologies was conducted in a field trial that demonstrated agreement between predicted and directly measured dicamba air concentrations at a series of off-target locations. This validated system was applied to a field case study on two plots to demonstrate the utility of these methods under typical agricultural conditions. This case study resulted in a time-varying volatile flux profile, which showed that less than 0.2 +/- 0.05% of the applied dicamba was volatilized over the 3-day sampling period. FULL TEXT

Zhang et al., 2019b

Zhang, J., Huang, Y., Reddy, K. N., & Wang, B.; “Assessing crop damage from dicamba on non-dicamba-tolerant soybean by hyperspectral imaging through machine learning;” Pest Management Science, 2019, 75(12), 3260-3272; DOI: 10.1002/ps.5448.


BACKGROUND: Dicamba effectively controls several broadleaf weeds. The off-target drift of dicamba spray or vapor drift can cause severe injury to susceptible crops, including non-dicamba-tolerant crops. In a field experiment, advanced hyperspectral imaging (HSI) was used to study the spectral response of soybean plants to different dicamba rates, and appropriate spectral features and models for assessing the crop damage from dicamba were developed.

RESULTS: In an experiment with six different dicamba rates, an ordinal spectral variation pattern was observed at both 1 week after treatment (WAT) and 3 WAT. The soybean receiving a dicamba rate >/=0.2X exhibited unrecoverable damage. Two recoverability spectral indices (HDRI and HDNI) were developed based on three optimal wavebands. Based on the Jeffries-Matusita distance metric, Spearman correlation analysis and independent t-test for sensitivity to dicamba spray rates, a number of wavebands and classic spectral features were extracted. The models for quantifying dicamba spray levels were established using the machine learning algorithms of naive Bayes, random forest and support vector machine.

CONCLUSIONS: The spectral response of soybean injury caused by dicamba sprays can be clearly captured by HSI. The recoverability spectral indices developed were able to accurately differentiate the recoverable and unrecoverable damage, with an overall accuracy (OA) higher than 90%. The optimal spectral feature sets were identified for characterizing dicamba spray rates under recoverable and unrecoverable situations. The spectral features plus plant height can yield relatively high accuracy under the recoverable situation (OA = 94%). These results can be of practical importance in weed management. (c) 2019 Society of Chemical Industry.


Soltani et al., 2020

Soltani, Nader, Oliveira, Maxwel C., Alves, Guilherme S., Werle, Rodrigo, Norsworthy, Jason K., Sprague, Christy L., Young, Bryan G., Reynolds, Daniel B., Brown, Ashli, & Sikkema, Peter H.; “Off-target movement assessment of dicamba in North America;” Weed Technology, 2020, 34(3), 318-330; DOI: 10.1017/wet.2020.17.


Six experiments were conducted in 2018 on field sites located in Arkansas, Indiana, Michigan, Nebraska, Ontario, and Wisconsin to evaluate the off-target movement (OTM) of dicamba under field-scale conditions. The highest estimated dicamba injury in non-dicamba-resistant (DR) soybean was 50, 44, 39, 67, 15, and 44% injury for non-covered areas and 59, 5, 13, 42, 0, and 41% injury for covered areas during dicamba application in Arkansas, Indiana, Michigan, Nebraska, Ontario, and Wisconsin, respectively. The level of injury generally decreased exponentially as the downwind distance increased under covered and non-covered areas at all sites. There was an estimated 10% injury in non-DR soybean at 113, 8, 11, 8, and 8 m; and estimated 1% injury at 293, 28, 71, 15, and 19 m from the edge of treated field downwind when plants were not covered during dicamba application in Arkansas, Indiana, Michigan, Ontario and Wisconsin, respectively. Filter paper collectors placed from 4 up to 137 m downwind from the edge of the sprayed area suggested that the dicamba deposition reduced exponentially with distance. The greatest injury to non-DR soybean from dicamba OTM occurred at Nebraska and Arkansas (as far as 250 m). Non-DR soybean injury was greatest adjacent to the dicamba sprayed area but, injury decreased with no injury beyond 20 m downwind or any other direction from the dicamba sprayed area in Indiana, Michigan, Ontario, and Wisconsin. The presence of soybean injury under covered and non-covered areas during the spray period for primary drift suggests that secondary movement of dicamba was evident at five sites. Further research is needed to determine the exact forms of secondary movement of dicamba under different environmental conditions. FULL TEXT

Christensen et al., 2016

Christensen, C. H., Barry, K. H., Andreotti, G., Alavanja, M. C., Cook, M. B., Kelly, S. P., Burdett, L. A., Yeager, M., Beane Freeman, L. E., Berndt, S. I., & Koutros, S.; “Sex Steroid Hormone Single-Nucleotide Polymorphisms, Pesticide Use, and the Risk of Prostate Cancer: A Nested Case-Control Study within the Agricultural Health Study;” Frontiers in Oncology, 2016, 6, 237; DOI: 10.3389/fonc.2016.00237.


Experimental and epidemiologic investigations suggest that certain pesticides may alter sex steroid hormone synthesis, metabolism or regulation, and the risk of hormone-related cancers. Here, we evaluated whether single-nucleotide polymorphisms (SNPs) involved in hormone homeostasis alter the effect of pesticide exposure on prostate cancer risk. We evaluated pesticide-SNP interactions between 39 pesticides and SNPs with respect to prostate cancer among 776 cases and 1,444 controls nested in the Agricultural Health Study cohort. In these interactions, we included candidate SNPs involved in hormone synthesis, metabolism or regulation (N = 1,100), as well as SNPs associated with circulating sex steroid concentrations, as identified by genome-wide association studies (N = 17). Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Multiplicative SNP-pesticide interactions were calculated using a likelihood ratio test. We translated p-values for interaction into q-values, which reflected the false discovery rate, to account for multiple comparisons. We observed a significant interaction, which was robust to multiple comparison testing, between the herbicide dicamba and rs8192166 in the testosterone metabolizing gene SRD5A1 (p-interaction = 4.0 x 10(-5); q-value = 0.03), such that men with two copies of the wild-type genotype CC had a reduced risk of prostate cancer associated with low use of dicamba (OR = 0.62 95% CI: 0.41, 0.93) and high use of dicamba (OR = 0.44, 95% CI: 0.29, 0.68), compared to those who reported no use of dicamba; in contrast, there was no significant association between dicamba and prostate cancer among those carrying one or two copies of the variant T allele at rs8192166. In addition, interactions between two organophosphate insecticides and SNPs related to estradiol metabolism were observed to result in an increased risk of prostate cancer. While replication is needed, these data suggest both agonistic and antagonistic effects on circulating hormones, due to the combination of exposure to pesticides and genetic susceptibility, may impact prostate cancer risk. FULL TEXT