Dicamba susceptibility of Erigeron spp. populations across Brazil: a six-year monitoring studyAbstract:
Background: Understanding the current scenario of Erigeron spp. susceptibility to dicamba, an auxin mimic, is of utmost importance since this mode of action has become prominent in the industry because the genetics crops. Thus, the monitoring and mapping of dicamba in Erigeron spp. populations is necessary to provide important information for their management.
Objective: To elaborate a dicamba baseline of Erigeron spp. as well as monitoring the populations dispersal across Brazil throughout six years.
Methods: Among 30 Erigeron spp. populations from the main grain areas in Brazil were evaluated to determine the dicamba baseline. Once the discriminating dose was identified, a monitoring screening of 1,413 Erigeron spp. populations susceptibility to dicamba was conducted over six years (2019, 2020, 2021, 2022, 2023, and 2024).
Results: Dicamba baseline considered ideal to control susceptible plants was 480 g ae ha−1. Among 1,413 Erigeron spp. populations evaluated in the six years of monitoring, 100% of populations were considered susceptible to dicamba.
Conclusions: These findings reinforce dicamba's continued relevance in Erigeron spp. management, provide a current benchmark for resistance monitoring efforts and broaden our understanding of the distribution of dicamba-susceptible Erigeron spp. across Brazil.
Keywords:
Conyza spp.; Baseline; Mapping; Auxin mimic
1. Introduction
The Erigeron genus (syn. Conyza) belongs to the Asteraceae family and encompasses 150 species worldwide (Wang et al., 2018). Notable among these species are hairy fleabane (Erigeron bonariensis L.), horseweed (E. canadensis L.), and sumatran fleabane (E. sumatrensis), which are recognized as weeds, primarily originating from the Americas (Marochio et al., 2017). Erigeron spp. spreads exclusively through seeds; each hairy fleabane plant has the potential to yield approximately 110,000 seeds, while horseweed can produce up to 200,000 seeds (Bhowmik, Bekech, 1993; Wu et al., 2007). The self-pollination ability of the species, combined with the large production of easily dispersible seeds, are factors that can contribute to the ecological adaptability, the survival of resistant biotypes of fleabane, and to high infestations in conservation tillage systems (Moreira et al., 2007).
In Brazil, Erigeron spp. represents one of the remarkable concerns in agricultural production, particularly due to the development of resistance to multiple herbicides. The first report of Erigeron spp. resistance was to glyphosate in 2005 (Heap, 2026). Thereafter, multiple resistance to glyphosate and chlorimuron; glyphosate, chlorimuron, and paraquat; and glyphosate, paraquat, 2,4-D, diuron, and saflufenacil was also reported (Heap, 2026). The impact of Erigeron spp. on crop yields primarily arises from its competition for essential resources such as water, nutrients, and light. At densities of 2.7 plants m−2, Erigeron spp. can reduce soybean yields by as much as 50% (Trezzi et al., 2015). Additionally, the presence of herbicide resistance poses challenges in managing fleabane and may lead to increased production costs (Baccin et al., 2022).
To Erigeron spp. control, several post-emergence herbicides are available. Two or more applications of herbicides are usually required to successfully control fleabane prior to soybean planting (Quinn et al., 2020; Cantu et al., 2021; Albrecht et al., 2022). Among them, dicamba is commonly used in the early post-emergence control or associated with other herbicides at burndown, either in single or in sequential applications. Dicamba (3,6-dichloro-2-methoxybenzoic acid) is a post-emergence herbicide that belongs to benzoic acid chemical group and synthetic auxin mode of action (group 4). When plants are treated with dicamba, the herbicide is absorbed by leaves and translocated via phloem to the organs, however, root absorption and translocation via xylem can occur (Cobb, Reade, 2010). Plants grow in abnormal and uncontrollable condition, which leads to plant death.
Dicamba has been an important component of weed management systems. In the United States, this herbicide was first approved by the Environmental Protection Agency (EPA) in 1967 and has been used by growers to control weeds for decades. Over the years, the use of dicamba raised selection for dicamba resistance in weeds. The first reported case was Kochia scoparia in 1999, approximately 30 years after registration in the country. In Brazil, the first registration of dicamba occurred in 2008. However, the formulated dicamba (commercial) was only registered in 2016. Since then, the herbicide has been used by farmers mainly for Erigeron spp. management and no cases of resistance have been reported. To date, there are 21 cases of weed resistance to dicamba worldwide, comprising 11 species reported in seven different countries (Heap, 2026).
Since auxinic herbicides are essential tools for the management of Erigeron spp., the evolution and spread of populations resistant to 2,4-D has become a growing concern in Brazilian soybean production systems. In this context, dicamba represents an important alternative auxinic herbicide that may contribute to the management of 2,4-D-resistant populations. The introduction and expansion of dicamba-resistant soybean technologies further increase the relevance of this issue, as these biotechnologies enable dicamba application in post-emergence soybean, potentially increasing selection pressure on Erigeron spp. populations. Similar to the increased glyphosate use observed after the widespread adoption of glyphosate-resistant crops (Beckie et al., 2020). Therefore, this work has been developed to elaborate a baseline of Erigeron spp. susceptibility to dicamba and monitor the geographic distribution of populations over time across Brazil to support sustainable dicamba stewardship.
2. Materials and Methods
2.1 Baseline of susceptibility of Erigeron spp. to dicamba
Dicamba dose-response experiments were carried out with five replicates and were conducted twice using a completely randomized design, with five treatments. The herbicide (Xtendicam®, 480 g ae ha−1, Bayer®, São Paulo) doses used on the populations were 0, 240, 360, 480, and 720 g ae ha−1. A drift reducer, (XtendProtect®, 0.1% v v−1, Bayer®, São Paulo), was added to the dicamba mix. We selected 30 populations for dose-response studies from different States in Brazil: Rio Grande do Sul, Santa Catarina, Paraná, Minas Gerais, São Paulo, Bahia, Goiás, and Mato Grosso (Table 1). Experiments were conducted in Santa Cruz das Palmeiras – São Paulo.
Samples of Erigeron spp. populations per season, state, and geographic coordinates of collection adopted for dicamba dose-response studies
For all experiments, species identification was performed only at the genus level. Seeds from each Erigeron spp. populations were broadcast into a tray containing Carolina® (CSC, Brazil) potting mix. The trays were watered daily and maintained in a greenhouse under natural lighting and temperature conditions. Once emerged, the seedlings were transplanted into 0.2 L pots, with one seedling per pot. The plants were allowed to grow and reach the 5- to 6-leaf stage prior to herbicide application.
A pressurized backpack sprayer was used, equipped with three nozzles (TTI110015, TeeJet® Technologies), which delivered 150 L ha−1. The applications took place in the morning (8:00-10:00), prioritizing the most favorable weather conditions, i.e., relative humidity above 60%, air temperature below 30ºC, and no wind gusts.
At 35 days after application (DAA), plant injury was visually evaluated using a scale from 0% to 100%, in which 0% means no injury and 100% means plant death (Sociedade Brasileira da Ciência das Plantas Daninhas, 1995). Data analysis was performed by applying the F test in the variance analysis. Dose-response curves from the 30 Erigeron spp. populations were fitted to a logistic non-linear regression model. The control variable was adjusted to the model proposed by Streibig (1988):
In which: y = percentage of control; x = herbicide dose; and a, b and c = parameters of the curve, so that a is the difference between the maximum and minimum points of the curve; b is the dose that provides 50% response of the variable and c is the slope of the curve. To describe the susceptibility baseline, the dicamba rates required to achieve 80% visual control (ED80) were estimated by inverse equation, aiming to separate resistant and susceptible individuals by means of these parameters (Carvalho et al. 2005). Its confidence interval was given by the formula:
In which mˆ = estimated average of the repetitions; to = value present in the t-test table; s = standard deviation and r = number of replications.
2.2 Monitoring dispersal of Erigeron spp.
Erigeron spp. samples were collected during a survey of 1,413 sites covering 13 States and the Federal District (Rio Grande do Sul, Santa Catarina, Paraná, São Paulo, Minas Gerais, Mato Grosso do Sul, Mato Grosso, Goiás, Bahia, Piauí, Maranhão, Tocantins, and Pará) in Brazil over six years (2019, 2020, 2021, 2022, 2023, and 2024). The collected plants were identified as Erigeron spp.; species-level identification was not performed. Survey sites were not the same over the years.
Briefly, the locations for seed collection were identified by visually observing the presence of Erigeron spp. from fields where a soybean pre-plant burndown application had failed. When present at the site, approximately 10 mature Erigeron spp. plants were collected and composited, resulting in a sample representing one population. Each population was placed in paper bags and identified by global positioning system coordinates (GPS), the name of the producer and/or property, and the collection date. Samples were sent to the State University of Maringá (UEM) located in Maringá – Paraná, University Center of Várzea Grande (Univag) located in Várzea Grande - Mato Grosso, and Agro do Mato located in Santa Bábara d’Oeste – São Paulo where experiments were carried out following the same protocol.
Erigeron spp. seeds were sown in 15-cell flats filled with Carolina Soil® (CSC, Brazil) potting mix. Once emerged, seedlings were transplanted into experimental units consisting of 0.2 L pots (7 × 7 × 8 cm) filled with soil when cotyledon leaves were fully expanded. The trays and pots were kept with daily irrigation (6–8 mm). A run was performed in a randomized design to arrange four replications for each population. A post label rate application of dicamba 480 g ae ha−1 (Xtendicam®, 480 g ae ha−1, Bayer®, São Paulo) + drift reducer (XtendProtect®, 0.1% v v−1, Bayer®, São Paulo) was administered at the 6-leaves stage. A pressurized backpack sprayer was used, equipped with three nozzles (TTI110015, TeeJet® Technologies), which delivered 150 L ha−1. The applications took place in the morning (8:00–10:00).
At 35 DAA, plant injury was visually evaluated using a scale of 0% to 100%, where 0% indicated no injury and 100% indicated plant death (SBCPD, 1995). Based on visual assessment, Erigeron spp. populations were classified as susceptible or resistant according to Lopez Ovejero et al. (2017) (Table 2).
After classifying each population based on the methodology proposed by Lopez Ovejero et al. (2017), the frequency of susceptible populations was calculated (number of samples in each class / total number of samples) by year. Map showing the distribution color code classification of Erigeron spp. populations was used to identify each sampling year using QGis software (version 2.14, Vienna, Austria).
3. Results and Discussion
3.1 Baseline of susceptibility of Erigeron spp. to dicamba
The data gathered following the application of dicamba on Erigeron spp. susceptible populations indicated ED80 of 573.14 g ae ha−1 (± 149.49) (Table 3). Data were adequately described by the log-logistic model, with the coefficient of determination above 99% (Figure 1). Values of ED80 were calculated once they are the minimum level of efficacy required by current legislation (Carvalho et al., 2006). Corroborating our data, ten horseweed populations from Nebraska – USA were screened with nine dicamba doses. Based on R:S ratios and recommended dicamba field use doses, none of the horseweed populations in this baseline study were considered resistant to dicamba (Crespo et al., 2013).
Parameters of the logistic model, coefficient of determination (R2) and control (C) for the susceptibility of 30 Erigeron spp. populations means to dicamba. Santa Cruz das Palmeiras – SP, 2024
Means of percent control for 30 dicamba-susceptible populations of Erigeron spp., submitted to increasing rates of dicamba and evaluated at 35 days after application (DAA). Santa Cruz das Palmeiras – SP, 2024
The methodology of single discriminating dose used to characterize the level of resistance is widely described in the literature (Schultz et al., 2015; Gonçalves Netto et al., 2022). The discriminating dose is defined as the minimum rate that provides the maximum difference between dose-response curves for resistant and susceptible biotypes, resulting in a minimum 80% control of the susceptible biotype (Beckie et al., 1990).
A review of product labels for dicamba formulations registered in Brazil found three products recommended to control Erigeron spp. at doses ranging from 480 g ae ha−1 to 720 g ae ha−1, with an average recommended dose of 600 g ae ha−1. Therefore, if baseline (Figure 1) and the lowest registered label rate (Rodrigues, Almeida, 2018) are concomitantly considered, it is evident that 480 g ae ha−1 of dicamba is the operational discriminatory dose to control susceptible Erigeron populations for the present experimental conditions.
3.2 Monitoring dispersal of Erigeron spp.
Throughout the six-year monitoring period, out of a total of 1,413 populations sampled, 76 were collected from eight States in 2019, 315 samples from 11 States in 2020, 235 samples from eight States in 2021, 292 samples from 10 States in 2022, 196 samples from 10 States in 2023, and 299 samples from 13 States in 2024. Consistently, the States of São Paulo, Minas Gerais, Mato Grosso, Mato Grosso do Sul, Goiás, Bahia, Paraná, and Rio Grande do Sul were sampled during the monitoring period. In contrast, Santa Catarina joined the sampling efforts in 2020, 2022, 2023, and 2024. Piauí (2024), Maranhão (2023 and 2024), Tocantins (2024), Pará (2020 and 2024), and Brasília (2020, 2022, and 2024) were the States with the lowest number of samples (one to three samples) per monitoring year.
Among the sampled States during the six-years monitoring, Rio Grande do Sul presented the highest number of samples, representing 34% of the total populations sampled, followed by Paraná (17%) and Mato Grosso (13%). The large number of samples were collected in these parts of Brazil because the oldest soybean growing areas are in the Southern part of the country and due to the history of resistance in the country. Out of nine cases of fleabane reported with resistance to herbicides and with multiple resistance, eight were found in Southern Brazil, mainly in Paraná state (Heap, 2026).
Based on the baseline dose-response analysis and the registered label rates for Erigeron spp. control in Brazil, 480 g ae ha−1 of dicamba was considered the operational discriminatory dose for susceptible populations throughout six years of evaluations. According to the mapping, 100% were classified as susceptible (white) to dicamba under the screening criterion, which means a noteworthy result considering the geographic extent of the survey and the six-years monitoring period (Figure 2). The absence of populations classified as putatively resistant at 480 g ae ha−1 indicates that no dicamba resistance was detected among the Erigeron spp. populations sampled during the survey period. However, this result should not be interpreted as evidence that dicamba resistance is absent from Brazil or that all individuals within a sampled population are uniformly susceptible. Single-dose screening assays are designed to identify populations with atypical responses under defined experimental conditions and may not detect resistant individuals occurring at low frequencies. The lack of evidence for dicamba resistance among the sampled Erigeron spp. populations may be associated with the relatively recent adoption of dicamba in Brazilian agricultural systems, beginning around 2016, which may not yet have imposed sufficient and sustained selection pressure to select resistant biotypes at detectable frequencies. In addition, dicamba is commonly recommended in association with glyphosate. Soares et al. (2012) reported that the dicamba + glyphosate mixture was not antagonistic for Erigeron control and may result in an additive response, even in glyphosate-resistant populations. Therefore, the use of this mixture may reduce the survival of individuals with reduced dicamba susceptibility, potentially delaying the enrichment of such individuals in the population.
Dispersion of dicamba-susceptible populations of Erigeron spp., in Brazil from the 2019 to 2024 seasons
The first report of Erigeron spp. resistance was to glyphosate in 2005; after that, some other reports were done and more recently (2017), there was a report of sumatran fleabane (Erigeron sumatrensis) with multiple resistance to five different herbicides (glyphosate, paraquat, diuron, saflufenacil, and 2,4-D). The evolution of herbicide resistance in weeds as fleabane is a role of several determinants, including initial frequency of the resistance gene, gene flow, selection pressure, mutation rate, and the mode of inheritance (Jasieniuk et al., 1996). We do not know with certainty which factor(s) are involved in process of Erigeron resistance to the 2,4-D herbicide, however, the burndown herbicide programs for soybeans usually include single or mixed sprays containing 2,4-D, which may have led to selection pressure (Lorenzetti et al., 2024).
The resistance to 2,4-D in Erigeron spp., recently characterized by a rapid necrosis phenotype, has prompted growers to adopt alternative synthetic auxins prior to soybean planting, mainly dicamba and triclopyr, in early burndown applications (Queiroz et al., 2020; Cantu et al., 2021). Dicamba and 2,4-D are herbicides from the same HRAC group (Group 4) that mimic the plant hormone auxin indole-3-acetic acid and comprise key tools for weed control in crops. However, dicamba (benzoic acid) belongs to a different chemical class than 2,4-D (phenoxyacetic).
Corroborating our data, previous research conducted by Kruger et al. (2009) reported that 350 g ha−1 dose of dicamba were enough to control fleabane (Erigeron canadensis). Similarly, the herbicide 2,4-D showed more limited control against some Erigeron bonariensis biotypes resistant to glyphosate, diclosulam, and chlorimuron in Uruguay, with control rates of 70.25%. In contrast, dicamba achieved control rates exceeding 97% for all tested biotypes (Kaspary et al., 2024). Also, McCauley and Young (2019) observed greater dicamba efficacy, compared to 2,4-D, in Erigeron canadensis plants up to 20 cm.
Other studies in Brazil have also found greater efficacy of dicamba in controlling Erigeron spp. Osipe et al. (2017) reported excellent Erigeron spp. control by combining dicamba with glyphosate to control glyphosate resistant plants, mainly when these plants were more developed (10–12 leaves stage). According to Filus et al. (2024), to control of E. sumatrensis plants with heights of less than 10 cm (12 leaves) and more than 10 cm (30 leaves) dicamba and 2,4-D were equally effective. Albrecht et al. (2022) also demonstrated excellent control of Erigeron sumatrensis biotypes resistant to 2,4-D with dicamba. These literature reports are consistent with our results.
Since dicamba-resistant soybean was recently released in South America, it is important to monitor the susceptibility of Erigeron spp. populations to dicamba, as this herbicide is an excellent alternative for managing fleabane. Our survey has successfully monitored the frequency and dispersion of fleabane populations across different agricultural regions over six years. This comprehension enables the assessment of appropriate strategies for slowing down the emergence of resistant populations (Schultz et al., 2015; Beckie et al., 2020). Although all populations were classified as susceptible in this study, the absence of dicamba resistance should not be interpreted as an absence of future risk. Continuous monitoring, combined with herbicide rotation, effective tank mixtures, and integrated weed-management practices will be essential to preserve dicamba as a valuable component of weed-management programs. Consequently, this insight plays a crucial role in the decision-making process for developing region-specific practices to effectively manage the challenges posed by weeds (Schultz et al., 2015; Lopez Ovejero et al., 2017).
4. Conclusions
This study established a dicamba susceptibility baseline for Erigeron spp. and monitored the geographic distribution of populations across Brazil over six consecutive years. A dicamba rate of 480 g ae ha−1 was defined as a discriminatory dose for susceptible populations, and all evaluated populations were classified as susceptible. These results indicate that dicamba remains an effective option for Erigeron spp. management in Brazilian agricultural systems. Therefore, this baseline provides a reference for future resistance monitoring and supports the adoption of integrated weed-management practices to preserve dicamba efficacy.
Funding
Data Availability Statement
The data availability policy does not apply
Acknowledgements
The authors would like to thank Universidade Estadual de Maringá (UEM), Universidade de Várzea Grande (UNIVAG), Agro do Mato Soluções Agronômicas Ltda and Bayer Crop Science that have all contributed to the development of this study.
References
-
Albrecht LP, Heimerdinger N, Albrecht AJP, Silva AFM, Piccin ES, Silva LM et al. Chemical control of fleabane resistant to 2,4-D. Outlooks Pest Manage. 2022;33(6):239-43. Available from: https://doi.org/10.1564/v33_dec_07
» https://doi.org/10.1564/v33_dec_07 -
Baccin LC, Albrecht AJP, Albrecht LP, Silva AFM, Victoria Filho R. Mechanisms of multiple resistance to herbicides in Conyza sp. complex. J Plant Prot Res. 2022;62(2):113-21. Available from: https://doi.org/10.24425/jppr.2022.141358
» https://doi.org/10.24425/jppr.2022.141358 -
Beckie HJ, Friesen LF, Nawolsky KM, Morrison IN. A rapid bioassay to detect trifluralin-resistant green foxtail (Setaria viridis). Weed Technol. 1990;4(3):505-8. Available from: https://doi.org/10.1017/S0890037X00025860
» https://doi.org/10.1017/S0890037X00025860 -
Beckie HJ, Shirriff S, Leeson JY, Hall LM, Brenzil CA, Neil Harker K et al. Herbicide-resistant weeds in the Canadian prairies: 2012 to 2017. Weed Technol. 2020;34(3):461-74. Available from: https://doi.org/10.1017/wet.2019.128
» https://doi.org/10.1017/wet.2019.128 - Bhowmik PC, Bekech MM. Horseweed (Conyza canadensis) seed production, emergence, and distribution in no-tillage and conventional-tillage corn (Zea mays). Agronomy. 1993;1:67-71.
-
Cantu RM, Albrecht LP, Albrecht AJP, Silva AFM, Danilussi MTY, Lorenzetti JB. Herbicide alternative for Conyza sumatrensis control in pre-planting in no-till soybeans. Adv Weed Sci. 2021;39:1-9. Available from: https://doi.org/10.51694/AdvWeedSci/2021;39:000012
» https://doi.org/10.51694/AdvWeedSci/2021;39:000012 -
Carvalho SJP, Buissa JAR, Nicolai M, Lopez Ovejero RF, Christoffoleti PJ. [Differential susceptibility of Amaranthus weeds to trifloxysulfuron-sodium and chlorimuron-ethyl herbicides]. Planta Daninha. 2006;24(3):541-8. Portuguese. Available from: https://doi.org/10.1590/S0100-83582006000300017
» https://doi.org/10.1590/S0100-83582006000300017 - Cobb AH, Reade JPH. Herbicides and plant physiology. 2nd ed. Chichester: John Wiley & Sons; 2010.
-
Crespo RJ, Bernards ML, Kruger G, Lee D, Wilson R. Response of Nebraska horseweed (Conyza canadensis) populations to dicamba. J Agric Sci. 2013;5(5):158-68. Available from: https://doi.org/10.5539/jas.v5n5p158
» https://doi.org/10.5539/jas.v5n5p158 -
Filus A, Barroso AAM, Albrecht AJP, Silva AFM, Albrecht LP, Roncatto E. Application technology and effectiveness of auxin herbicides in controlling Conyza sumatrensis and Commelina benghalensis Rev Agric Neotrop. 2024;11(1):1-11. Available from: https://doi.org/10.32404/rean.v11i1.8319
» https://doi.org/10.32404/rean.v11i1.8319 -
Gonçalves Netto A, Resende LS, Malardo MR, Presoto JC, Andrade JF, Nicolai M et al. Geographical distribution and resistance level to chlorimuron of Amaranthus spp. populations in the main soybeans producing regions of Brazil. Adv Weed Sci. 2022;40(spe 2):1-9. Available from: https://doi.org/10.51694/AdvWeedSci/2022;40:Amaranthus010
» https://doi.org/10.51694/AdvWeedSci/2022;40:Amaranthus010 -
Heap I. International survey of herbicide resistant weeds. WeedScience. 2026[access Jan 11, 2026]. Available from: http://weedscience.org/Home.aspx
» http://weedscience.org/Home.aspx -
Jasieniuk M, Brûlé-Babel AL, Morrison IN. The evolution and genetics of herbicide resistance in weeds. Weed Sci. 1996;44(1):176-93. Available from: https://doi.org/10.1017/S0043174500093747
» https://doi.org/10.1017/S0043174500093747 -
Kaspary TE, Waller Barcena ME, García MA, Cabrera M, Hill SM. Conyza bonariensis’ resistance to glyphosate, diclosulam, and chlorimuron: confirmation and alternative control for the first case of multiple and cross-resistance in Uruguay. Agronomy. 2024;14(1):1-14. Available from: https://doi.org/10.3390/agronomy14010079
» https://doi.org/10.3390/agronomy14010079 -
Kruger GR, Davis VM, Weller SC, Stachler JM, Loux MM, Johnson WG. Frequency, distribution, and characterization of horseweed (Conyza canadensis) biotypes with resistance to glyphosate and ALS-inhibiting herbicides. Weed Sci. 2009;57(6):652-9. Available from: https://doi.org/10.1614/WS-09-075.1
» https://doi.org/10.1614/WS-09-075.1 -
Lopez Ovejero RF, Takano HK, Nicolai M, Ferreira A, Melo MSC, Cavenaghi AL et al. Frequency and dispersal of glyphosate-resistant sourgrass (Digitaria insularis) populations across Brazilian agricultural production areas. Weed Sci. 2017;65(2):285-94. Available from: https://doi.org/10.1017/wsc.2016.31
» https://doi.org/10.1017/wsc.2016.31 -
Lorenzetti JB, Danilussi MTY, Albrecht AJP, Barroso AAM, Albrecht LP, Silva AFM et al. Identification, mapping, and chemical control of fleabane resistant to glyphosate, chlorimuron, paraquat, and 2,4-D. Weed Technol. 2024;38:1-12. Available from: https://doi.org/10.1017/wet.2024.10
» https://doi.org/10.1017/wet.2024.10 -
Marochio CA, Bevilaqua MRR, Takano HK, Mangolim CA, Oliveira Junior RS, Machado MFPS. Genetic admixture in species of Conyza (Asteraceae) as revealed by microsatellite markers. Acta Sci Agron. 2017;39(4):437-45. Available from: https://doi.org/10.4025/actasciagron.v39i4.32947
» https://doi.org/10.4025/actasciagron.v39i4.32947 -
McCauley CL, Young BG. Differential response of horseweed (Conyza canadensis) to halauxifen-methyl, 2,4-D, and dicamba. Weed Technol. 2019;33(5):673-9. Available from: https://doi.org/10.1017/wet.2019.56
» https://doi.org/10.1017/wet.2019.56 -
Moreira MS, Nicolai M, Carvalho SJP, Christoffoleti PJ. [Resistance of Conyza canadensis and C. bonariensis to glyphosate]. Planta Daninha. 2007;25(1):157-164. Portuguese. Available from: https://doi.org/10.1590/S0100-83582007000100017
» https://doi.org/10.1590/S0100-83582007000100017 -
Osipe JB, Oliveira Junior RS, Constantin J, Takano HK, Biffe DF. Spectrum of weed control with 2,4-D and dicamba herbicides associated to glyphosate or not. Planta Daninha. 2017;35:1-12. Available from: https://doi.org/10.1590/S0100-83582017350100053
» https://doi.org/10.1590/S0100-83582017350100053 -
Queiroz ARS, Delatorre CA, Lucio FR, Rossi CVS, Zobiole LHS, Merotto A. Rapid necrosis: a novel plant resistance mechanism to 2,4-D. Weed Sci. 2020;68(1):6-18. Available from: https://doi.org/10.1017/wsc.2019.65
» https://doi.org/10.1017/wsc.2019.65 -
Quinn J, Soltani N, Ashigh J, Hooker DC, Robinson DE, Sikkema PH. Halauxifen-methyl controls glyphosate-resistant horseweed (Conyza canadensis) but not giant ragweed (Ambrosia trifida) in winter wheat. Weed Technol. 2020;34(4):607-12. Available from: https://doi.org/10.1017/wet.2020.21
» https://doi.org/10.1017/wet.2020.21 - Rodrigues BN, Almeida FS. [Herbicide guide]. 7th ed. Londrina: Author's Edition; 2018. Portuguese.
-
Schultz JL, Chatham LA, Riggins CW, Tranel PJ, Bradley KW. Distribution of herbicide resistances and molecular mechanisms conferring resistance in Missouri waterhemp (Amaranthus rudis Sauer) populations. Weed Sci. 2015;63(1):336-345. Available from: https://doi.org/10.1614/WS-D-14-00102.1
» https://doi.org/10.1614/WS-D-14-00102.1 -
Soares DJ, Oliveira WS, López-Ovejero RF, Christoffoleti PJ. Control of glyphosate resistant hairy fleabane (Conyza bonariensis) with dicamba and 2,4-D. Planta Daninha. 2012;30(2):401-6. Available from: https://doi.org/10.1590/S0100-83582012000200020
» https://doi.org/10.1590/S0100-83582012000200020 - Sociedade Brasileira da Ciência das Plantas Daninhas - SBCPD. [Procedures for the installation, evaluation, and analysis of herbicide experiments]. Londrina: Sociedade Brasileira da Ciência das Plantas Daninhas; 1995. Portuguese.
-
Streibig JC. Herbicide bioassay. Weed Res. 1988;28(6):479-84. Available from: https://doi.org/10.1111/j.1365-3180.1988.tb00831.x
» https://doi.org/10.1111/j.1365-3180.1988.tb00831.x -
Trezzi MM, Vidal RA, Patel F, Miotto Júnior E, Debastiani F, Balbinot Júnior AA et al. Impact of Conyza bonariensis density and establishment period on soyabean grain yield, yield components and economic threshold. Weed Res. 2015;55(1):34-41. Available from: https://doi.org/10.1111/wre.12125
» https://doi.org/10.1111/wre.12125 -
Wang A, Wu H, Zhu X, Lin J. Species identification of Conyza bonariensis assisted by chloroplast genome sequencing. Front Genet. 2018;9:1-8. Available from: https://doi.org/10.3389/fgene.2018.00374
» https://doi.org/10.3389/fgene.2018.00374 -
Wu H, Walker S, Rollin MJ, Tan DKY, Robinson G, Werth J. Germination, persistence, and emergence of flaxleaf fleabane (Conyza bonariensis [L.] Cronquist). Weed Biol Manag. 2007;7(3):192-9. Available from: https://doi.org/10.1111/j.1445-6664.2007.00256.x
» https://doi.org/10.1111/j.1445-6664.2007.00256.x
