Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-15T03:23:24.120Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment of crop and weed management strategies prior to introduction of auxin-resistant crops in Brazil

Published online by Cambridge University Press:  28 August 2020

Maxwel C. Oliveira Open the ORCID record for Maxwel C. Oliveira [Opens in a new window] ,
Anelise Lencina ,
André R. Ulguim  and
Rodrigo Werle
Maxwel C. Oliveira*
Affiliation:
Research Associate, University of Wisconsin-Madison, Department of Agronomy, Madison, WI, USA Assistant Professor, Western Sao Paulo University, Department of Agronomy, Presidente Prudente, São Paulo, Brazil
Anelise Lencina
Affiliation:
Graduate Research Assistant, Department of Crop Protection, Universidade Federal de Santa Maria, Santa Maria, RS, Brazil
André R. Ulguim
Affiliation:
Assistant Professor, Department of Crop Protection, Universidade Federal de Santa Maria, Santa Maria, RS, Brazil
Rodrigo Werle
Affiliation:
Assistant Professor, Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin, USA
*
Author for correspondence: Maxwel C Oliveira, University of Wisconsin-Madison, Department of Agronomy, 1575 Linden Drive, Madison, WI53706. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

A stakeholder survey was conducted from April through June of 2018 to understand stakeholders’ perceptions and challenges about cropping systems and weed management in Brazil. The dominant crops managed by survey respondents were soybean (73%) and corn (66%). Approximately 75% of survey respondents have grown or managed annual cropping systems with two to three crops per year cultivated in succession. Eighteen percent of respondents manage only irrigated cropping systems, and over 60% of respondents adopt no-till as a standard practice. According to respondents, the top five troublesome weed species in Brazilian cropping systems are horseweed (asthmaweed, Canadian horseweed, and tall fleabane), sourgrass, morningglory, goosegrass, and dayflower (Asiatic dayflower and Benghal dayflower). Among the nine species documented to have evolved resistance to glyphosate in Brazil, horseweed and sourgrass were reported as the most concerning weeds. Other than glyphosate, 31% and 78% of respondents, respectively, manage weeds resistant to acetyl-CoA carboxylase (ACCase) inhibitors and/or acetolactate synthase (ALS) inhibitors. Besides herbicides, 45% of respondents use mechanical, and 75% use cultural (e.g., no-till, crop rotation/succession) weed control strategies. Sixty-one percent of survey respondents adopt cover crops to some extent to suppress weeds and improve soil chemical and physical properties. Nearly 60% of survey respondents intend to adopt the crops that are resistant to dicamba or 2,4-D when available. Results may help practitioners, academics, industry, and policy makers to better understand the bad and the good of current cropping systems and weed management practices adopted in Brazil, and to adjust research, education, technologies priorities, and needs moving forward.

Keywords

2, 4-DdicambaglyphosateAsiatic dayflower, Commelina communis L.asthmaweed, Conyza bonariensis (L.) CronquistBenghal dayflower, Commelina benghalensis L.Canadian horseweed, Conyza canadensis (L.) Cronquistdayflower, Commelina spp.goosegrass, Eleusine indica (L.) Gaertn.horseweed, Conyza spp.morningglory, Ipomoea spp.sourgrassDigitaria insularis (L.) Mez ex Ekmantall fleabane, Conyza sumatrensis Retz. E. Walkercorn, Zea mays L.soybean, Glycine max (L.) MerrilCover cropsherbicide weed resistanceno-tillsurveyweed control
Type
Education/Extension
Information
Weed Technology , Volume 35 , Issue 1 , February 2021 , pp. 155 - 165
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the Weed Science Society of America

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Associate Editor: Aaron Hager, University of Illinois

References

Altieri, MA, Lana, MA, Bittencourt, HV, Kieling, AS, Comin, JJ, Lovato, PE (2011) Enhancing crop productivity via weed suppression in organic no-till cropping systems in Santa Catarina, Brazil. J Sustainable Agric 35:855–869 CrossRefGoogle Scholar
Alvares, CA, Stape, JL, Sentelhas, PC, de Moraes Gonçalves, JL, Sparovek, G (2013 ) Köppen’s climate classification map for Brazil. Meteorol Z 22:771–728CrossRefGoogle Scholar
Appleby, AP (2005) A history of weed control in the United States and Canada—a sequel. Weed Sci 53:762–768 CrossRefGoogle Scholar
Araújo, MLS, Sano, EE, Bolfe, ÉL, Santos, JRN, dos Santos, JS, Silva, FB (2019) Spatiotemporal dynamics of soybean crop in the Matopiba region, Brazil (1990–2015). Land Use Policy 80:57–67 CrossRefGoogle Scholar
Benbrook, CM (2016) Trends in glyphosate herbicide use in the United States and globally. Environ Sci Eur 28:3 CrossRefGoogle ScholarPubMed
Bish, MD, Bradley, KW (2017) Survey of Missouri pesticide applicator practices, knowledge, and perceptions. Weed Technol 31:165–177 CrossRefGoogle Scholar
Bonny, S (2011) Herbicide-tolerant transgenic soybean over 15 years of cultivation: pesticide use, weed resistance, and some economic issues. The case of the USA. Sustainability 3:1302–1322 CrossRefGoogle Scholar
Brunharo, CA, Patterson, EL, Carrijo, DR, Melo MS de, Nicolai, M, Gaines, TA, Nissen, SJ, Christoffoleti, PJ (2016) Confirmation and mechanism of glyphosate resistance in tall windmill grass (Chloris elata) from Brazil. Pest Manag Sci 72:1758–1764 CrossRefGoogle ScholarPubMed
Cerdeira, AL, Gazziero, DLP, Duke, SO, Matallo, MB (2011) Agricultural impacts of glyphosate-resistant soybean cultivation in South America. J Agric Food Chem 59:5799–5807 CrossRefGoogle ScholarPubMed
Christoffoleti, PJ, de Carvalho, SJP, López-Ovejero, RF, Nicolai, M, Hidalgo, E, da Silva, JE (2007) Conservation of natural resources in Brazilian agriculture: implications on weed biology and management. Crop Prot 26:383–389 CrossRefGoogle Scholar
Dauer, JT, Mortensen, DA, Vangessel, MJ (2007) Temporal and spatial dynamics of long-distance Conyza canadensis seed dispersal. J Appl Ecol 44:105–114 CrossRefGoogle Scholar
Dias, LCP, Pimenta, FM, Santos, AB, Costa, MH, Ladle, RJ (2016) Patterns of land use, extensification, and intensification of Brazilian agriculture. Global Change Biol 22:2887–2903 CrossRefGoogle ScholarPubMed
Duke, SO (2012) Why have no new herbicide modes of action appeared in recent years? Pest Manag Sci 68:505–512 Google ScholarPubMed
Duke, SO, Dayan, FE (2018) Herbicides. Page 9 in Encyclopedia of Life Sciences–eLS. Chichester, UK: John Wiley & Sons Google Scholar
Duke, SO, Powles, SB (2008) Glyphosate: a once-in-a-century herbicide. Pest Manag Sci 64:319–325 CrossRefGoogle ScholarPubMed
Fearnside, PM (2001) Soybean cultivation as a threat to the environment in Brazil. Environ Conserv 28:23–38 CrossRefGoogle Scholar
Frene, RL, Simpson, DM, Buchanan, MB, Vega, ET, Ravotti, ME, Valverde, PP (2018) Enlist E3TM Soybean sensitivity and EnlistTM herbicide-based program control of sumatran fleabane (Conyza sumatrensis). Weed Technol 32:416–423 CrossRefGoogle Scholar
Gianessi, LP, Reigner, NP (2007) The value of herbicides in U.S. crop production. Weed Technol 21:559–566 CrossRefGoogle Scholar
Goedert, WJ (1983) Management of the cerrado soils of Brazil: a review. J Soil Sci 34:405–428 CrossRefGoogle Scholar
Green, JM (2018) The rise and future of glyphosate and glyphosate-resistant crops. Pest Manag Sci 74:1035–1039 CrossRefGoogle ScholarPubMed
Hart, SE, Wax, LM (1996) Dicamba antagonizes grass weed control with imazethapyr by reducing foliar absorption. Weed Technol 10:828–834 CrossRefGoogle Scholar
Heap, I (2020) International Survey of Herbicide Resistant Weeds (list of herbicide resistant weeds by country). http://www.weedscience.org/Summary/Country.aspx. Accessed: January 29, 2020Google Scholar
Holstun, JT, Wooten, J, McWhorter, CG, Crowe, GB (1960) Weed control practices, labor requirements and costs in cotton production. Weeds 8:232–243 CrossRefGoogle Scholar
HRAC-BR [Brazilian Association for Herbicide Resistance Action Committee] (2019) Possible glyphosate resistance of Amaranthus hybridus reported in Brazil. http://news.agropages.com/News/Detail-29964.htm. Accessed: April 24, 2019Google Scholar
IBGE [Brazilian Institute of Geography and Statistics] (2020) Série histórica da estimativa anual da área plantada, área colhida, produção e rendimento médio dos produtos das lavouras [Historical series of estimated annual planted area, harvested area, production and average crop yields] https://sidra.ibge.gov.br/tabela/6588. Accessed: January 27, 2020Google Scholar
Jones, GT, Norsworthy, JK, Barber, T, Gbur, E, Kruger, GR (2019) Off-target movement of DGA and BAPMA dicamba to sensitive soybean. Weed Technol 33:51–65 CrossRefGoogle Scholar
Kalsing, A, Rossi, CVS, Lucio, FR, Zobioli, LHS, Cunha, LCV, Minozzi, GB (2018) Effect of formulations and spray nozzles on 2,4-D spray drift under field conditions. Weed Technol 32:379–384 CrossRefGoogle Scholar
Klink, CA, Machado, RB (2005) Conservation of the Brazilian cerrado. Conserv Biol 19:707–713 CrossRefGoogle Scholar
Knezevic, SZ, Osipitan, OA, Scott, JE (2018) Sensitivity of grape and tomato to micro-rates of dicamba-based herbicides. J Hort 05:1 Google Scholar
Kniss, AR (2018) Soybean response to dicamba: a meta-analysis. Weed Technol 32:507–512 CrossRefGoogle Scholar
Küpper, A, Borgato, EA, Patterson, EL, Netto, AG, Nicolai, M, Carvalho SJP de, Nissen, SJ, Gaines, TA, Christoffoleti, PJ (2017) Multiple resistance to glyphosate and acetolactate synthase inhibitors in Palmer amaranth (Amaranthus palmeri) Identified in Brazil. Weed Sci 65:317–326 CrossRefGoogle Scholar
LeBaron, H, McFarland, J, Burnside, O, eds (2008) The Triazine Herbicides. San Diego: Elsevier Science. 604 p Google Scholar
Li, J, Han, H, Bai, L, Yu, Q (2020) 2,4-D antagonizes glyphosate in glyphosate-resistant barnyard grass Echinochloa colona . J Pestic Sci 45:109–113 CrossRefGoogle ScholarPubMed
Lucio, FR, Kalsing, A, Adegas, FS, Rossi, CVS, Correia, NM, Gazziero, DLP, Silva AF da (2019) Dispersal and frequency of glyphosate-resistant and glyphosate-tolerant weeds in soybean-producing edaphoclimatic microregions in Brazil. Weed Technol 33:217–231 CrossRefGoogle Scholar
Marth, PC, Mitchell, JW (1944) 2,4-dichlorophenoxyacetic acid as a differential herbicide. Botanical Gazette 106:224–232 CrossRefGoogle Scholar
Mohseni-Moghadam, M, Wolfe, S, Dami, I, Doohan, D (2016) Response of wine grape cultivars to simulated drift rates of 2,4-D, dicamba, and glyphosate, and 2,4-D or dicamba plus glyphosate. Weed Technol 30:807–814 CrossRefGoogle Scholar
Moraes, A, Carvalho PC de F, Anghinoni, I, Lustosa, SBC, Costa SEVG de A, Kunrath, TR (2014) Integrated crop–livestock systems in the Brazilian subtropics. Eur J Agron 57:4–9 CrossRefGoogle Scholar
Mueller, TC, Steckel, LE (2019a) Dicamba volatility in humidomes as affected by temperature and herbicide treatment. Weed Technol 33:541–546 CrossRefGoogle Scholar
Mueller, TC, Steckel, LE (2019b) Spray mixture pH as affected by dicamba, glyphosate, and spray additives. Weed Technol 33:547–554 CrossRefGoogle Scholar
Oseland, E, Bish, M, Steckel, L, Bradley, K (2020) Identification of environmental factors that influence the likelihood of off-target movement of dicamba. Pest Manag Sci 76:3282–3291 CrossRefGoogle ScholarPubMed
Osipitan, OA, Scott, JE, Knezevic, SZ (2019) Glyphosate-resistant soybean response to micro-rates of three dicamba-based herbicides. Agrosystems 2:1–8 CrossRefGoogle Scholar
Ovejero, RFL, Takano, HK, Nicolai, M, Ferreira, A, Melo, MSC, Cavenaghi, AL, Christoffoleti, PJ, Oliveira, RS (2017) Frequency and dispersal of glyphosate-resistant sourgrass (Digitaria insularis) populations across Brazilian agricultural production areas. Weed Sci 65:285–294 Google Scholar
Owen, MD (2008) Weed species shifts in glyphosate-resistant crops. Pest Manag Sci 64:377–387 CrossRefGoogle ScholarPubMed
Owen, MDK (2000) Current use of transgenic herbicide-resistant soybean and corn in the USA. Crop Prot 19:765–771 CrossRefGoogle Scholar
Padgette, SR, Kolacz, KH, Delannay, X, Re, DB, LaVallee, BJ, Tinius, CN, Rhodes, WK, Otero, YI, Barry, GF, Eichholtz, DA, Peschke, VM, Nida, DL, Taylor, NB, Kishore, GM (1995) Development, identification, and characterization of a glyphosate-tolerant soybean line. Crop Sci 35:1451–1461 CrossRefGoogle Scholar
Pivetta, M, Dornelles, S, Sanchonete, D, Goergen, A, Soares, J, Brun, A, Pedrollo, N (2018) Capim arroz resistente ao glifosato em área de produção de soja no Rio Grande do Sul [Glyphosate-resistant jungle rice in a soybean production area at Rio Grande do Sul]. Page 560 in Resumos do XXXI Congresso Brasileiro da Ciência das Plantas Daninhas [Proceedings of the XXXI Brazilian Congress of Plant Science]. Rio de Janeiro, RJGoogle Scholar
Preston, C, Wakelin, AM, Dolman, FC, Bostamam, Y, Boutsalis, P (2009) A decade of glyphosate-resistant Lolium around the world: mechanisms, genes, fitness, and agronomic management. Weed Sci 57:435–441 CrossRefGoogle Scholar
R Core Team (2020) R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. https://www.R-project.org/. Accessed: October 4, 2020Google Scholar
Reis, MR, Aquino, LÂ, Melo, CAD, Silva, DV, Dias, RC, Reis, MR, Aquino, LÂ, Melo, CAD, Silva, DV, Dias, RC (2018) Carryover of tembotrione and atrazine affects yield and quality of potato tubers. Acta Scientiarum Agronomy 40:e35355 CrossRefGoogle Scholar
Sanders, JH, Bein, FL (1976) Agricultural development on the Brazilian frontier: southern Mato Grosso. Econ Dev Cult Change 24:593–610 CrossRefGoogle Scholar
Schryver, M, Soltani, N, Hooker, DC, Robinson, DE, Tranel, P, Sikkema, PH (2017) Control of glyphosate-resistant common waterhemp (Amaranthus tuberculatus var rudis) with dicamba and dimethenamid-P in Ontario. Can J Plant Sci 98:362–369 Google Scholar
Schwartz-Lazaro, LM, Norsworthy, JK, Steckel, LE, Stephenson, DO, Bish, MD, Bradley, KW, Bond, JA (2018) A midsouthern consultant’s survey on weed management practices in soybean. Weed Technol 32:116–125 CrossRefGoogle Scholar
Scursoni, JA, Vera, ACD, Oreja, FH, Kruk, BC, Fuente EB de la (2019) Weed management practices in Argentina crops. Weed Technol 33:459–463 CrossRefGoogle Scholar
Shields, EJ, Dauer, JT, VanGessel, MJ, Neumann, G (2006) Horseweed (Conyza canadensis) seed collected in the planetary boundary layer. Weed Sci 54:1063–1067 CrossRefGoogle Scholar
SIDRA-IBGE (2020) Sistema IBGE de recuperação automática–SIDRA [IBGE Automatic Recovery System]. https://sidra.ibge.gov.br/home/. Accessed: March 16, 2020Google Scholar
Soltani, N, Oliveira, MC, Alves, GS, Werle, R, Norsworthy, JK, Sprague, CL, Young, BG, Reynolds, DB, Brown, A, Sikkema, PH (2020) Off-target movement assessment of dicamba in North America. Weed Technol 34:318–330 Google Scholar
Takano, HK, Mendes, RR, Scoz, LB, Ovejero, RFL, Constantin, J, Gaines, TA, Westra, P, Dayan, FE, Oliveira, RS (2019) Proline-106 EPSPS mutation imparting glyphosate resistance in goosegrass (Eleusine indica) emerges in South America. Weed Sci 67:48–56 CrossRefGoogle Scholar
Takano, HK, Ovejero, RFL, Belchior, GG, Maymone, GPL, Dayan, FE (2019) ACCase-inhibiting herbicides: mechanism of action, resistance evolution and stewardship. Scientia Agricola 78:e20190102 CrossRefGoogle Scholar
Takano, HK, Oliveira RS de, Constantin, J, Mangolim, CA, Machado M de FPS, Bevilaqua, MRR (2018) Spread of glyphosate-resistant sourgrass (Digitaria insularis): independent selections or merely propagule dissemination? Weed Biol and Manag 18:50–59 CrossRefGoogle Scholar
Troyer, JR (2001) In the beginning: the multiple discovery of the first hormone herbicides. Weed Sci 49:290–297 CrossRefGoogle Scholar
Ulguim, AR, Agostinetto, D, Vargas, L, Dias Gomes da Silva, J, Moncks da Silva, B, da Rosa Westendorff, N (2017) Agronomic factors involved in low-level wild poinsettia resistance to glyphosate. Revista Brasileira de Ciências Agrárias 12:51–59 CrossRefGoogle Scholar
Underwood, MG, Soltani, N, Hooker, DC, Robinson, DE, Vink, JP, Swanton, CJ, Sikkema, PH (2016) The addition of dicamba to POST applications of quizalofop-p-ethyl or clethodim antagonizes volunteer glyphosate-resistant corn control in dicamba-resistant soybean. Weed Technol 30:639–647 CrossRefGoogle Scholar
USDA-NASS (2020) National Agricultural Statistics Service–charts and maps–County Maps. https://www.nass.usda.gov/Charts_and_Maps/Crops_County/#cr. Accessed: January 10, 2020Google Scholar
Vila-Aiub, MM, Vidal, RA, Balbi, MC, Gundel, PE, Trucco, F, Ghersa, CM (2008) Glyphosate-resistant weeds of South American cropping systems: an overview. Pest Manag Sci 64:366–371 CrossRefGoogle ScholarPubMed
Walsh, MJ, Broster, JC, Schwartz-Lazaro, LM, Norsworthy, JK, Davis, AS, Tidemann, BD, Beckie, HJ, Lyon, DJ, Soni, N, Neve, P, Bagavathiannan, MV (2018) Opportunities and challenges for harvest weed seed control in global cropping systems. Pest Manag Sci 74:2235–2245 CrossRefGoogle ScholarPubMed
Warren, GF (1998) Spectacular increases in crop yields in the United States in the twentieth century. Weed Technol 12:752–760 CrossRefGoogle Scholar
Werle, R, Oliveira, MC, Jhala, AJ, Proctor, CA, Rees, J, Klein, R (2018) Survey of Nebraska farmers’ adoption of dicamba-resistant soybean technology and dicamba off-target movement. Weed Technol 32:754–761 CrossRefGoogle Scholar
Wickham, H (2017) Tidyverse: Easily install and load the ’tidyverse’. R package version 1.2. Vienna: R Foundation for Statistical Computing.Google Scholar
Wright, TR, Shan, G, Walsh, TA, Lira, JM, Cui, C, Song, P, Zhuang, M, Arnold, NL, Lin, G, Yau, K, Russell, SM, Cicchillo, RM, Peterson, MA, Simpson, DM, Zhou, N, Ponsamuel, J, Zhang, Z (2010) Robust crop resistance to broadleaf and grass herbicides provided by aryloxyalkanoate dioxygenase transgenes. Proc Natl Acad Sci USA 107:20240–20245 CrossRefGoogle ScholarPubMed
Yamada, T (2005) The cerrado of Brazil: a Success story of production on acid soils. J Soil Sci Plant Nutr 51:617–620 CrossRefGoogle Scholar
Zalles, V, Hansen, MC, Potapov, PV, Stehman, SV, Tyukavina, A, Pickens, A, Song, X-P, Adusei, B, Okpa, C, Aguilar, R, John, N, Chavez, S (2019) Near doubling of Brazil’s intensive row crop area since 2000. Proc Natl Acad Sci USA 116:428–435 CrossRefGoogle ScholarPubMed