Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans
- Autores
- Oreja, Fernando Hugo; Bastida, Fernando; González Andújar, José L.
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
A bioeconomic model was developed for decision-making regarding large crabgrass (Digitaria sanguinalis) control in glyphosate-resistant soybeans in the Rolling Pampas of Argentina. The model was used to evaluate the economic returns of four different glyphosate-based strategies for weed control. In the absence of herbicide application (T1), the soil seed bank increases to an equilibrium density of 12,079 seeds m -2 in three years. A single herbicide application during the early stages of the crop (T2), which was intended to be highly effective in the control of an early weed cohort, allows a late, unaffected cohort to produce sufficient seeds to maintain population densities in the soil seed bank. A single, delayed herbicide application (T3), which was intended to control both early and late cohorts, results in a soil seed bank increase up to an equilibrium density similar to that achieved without treatment. Two sequential herbicide applications per year (T4), targeting the two cohorts, leads to a soil seed bank density after 10 years of 107 seeds m -2. Model predictions indicate that in the absence of control measures, a 93 percent reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27 percent) was predicted using strategy T4, which is the most common control measure used by local farmers. This strategy clearly outperforms the other options tested, leading to lower D. sanguinalis seed bank densities and higher soybean yields and economic returns compared to those obtained using the alternative strategies. - Fuente
- Ciencia e Investigación Agraria
Vol.39, no.2
299-308
http://agronomia.uc.cl/ - Materia
-
CROP-WEED COMPETITION
DIGITARIA
GLYCINE MAX
HERBICIDES
LARGE CRABGRASS
SENSITIVITY ANALYSIS
TRANSGENIC CROP - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- acceso abierto
- Repositorio
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- Institución
- Universidad de Buenos Aires. Facultad de Agronomía
- OAI Identificador
- snrd:2012Oreja
Ver los metadatos del registro completo
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| spelling |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeansOreja, Fernando HugoBastida, FernandoGonzález Andújar, José L.CROP-WEED COMPETITIONDIGITARIAGLYCINE MAXHERBICIDESLARGE CRABGRASSSENSITIVITY ANALYSISTRANSGENIC CROPFil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.A bioeconomic model was developed for decision-making regarding large crabgrass (Digitaria sanguinalis) control in glyphosate-resistant soybeans in the Rolling Pampas of Argentina. The model was used to evaluate the economic returns of four different glyphosate-based strategies for weed control. In the absence of herbicide application (T1), the soil seed bank increases to an equilibrium density of 12,079 seeds m -2 in three years. A single herbicide application during the early stages of the crop (T2), which was intended to be highly effective in the control of an early weed cohort, allows a late, unaffected cohort to produce sufficient seeds to maintain population densities in the soil seed bank. A single, delayed herbicide application (T3), which was intended to control both early and late cohorts, results in a soil seed bank increase up to an equilibrium density similar to that achieved without treatment. Two sequential herbicide applications per year (T4), targeting the two cohorts, leads to a soil seed bank density after 10 years of 107 seeds m -2. Model predictions indicate that in the absence of control measures, a 93 percent reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27 percent) was predicted using strategy T4, which is the most common control measure used by local farmers. This strategy clearly outperforms the other options tested, leading to lower D. sanguinalis seed bank densities and higher soybean yields and economic returns compared to those obtained using the alternative strategies.2012articleinfo:eu-repo/semantics/articlepublishedVersioninfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfdoi:10.4067/S0718-16202012000200006issn:0304-5609http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2012OrejaCiencia e Investigación AgrariaVol.39, no.2299-308http://agronomia.uc.cl/reponame:FAUBA Digital (UBA-FAUBA)instname:Universidad de Buenos Aires. Facultad de Agronomíaenginfo:eu-repo/semantics/openAccessopenAccesshttp://ri.agro.uba.ar/greenstone3/library/page/biblioteca#section42025-11-06T09:37:02Zsnrd:2012Orejainstacron:UBA-FAUBAInstitucionalhttp://ri.agro.uba.ar/Universidad públicaNo correspondehttp://ri.agro.uba.ar/greenstone3/oaiserver?verb=ListSetsmartino@agro.uba.ar;berasa@agro.uba.ar ArgentinaNo correspondeNo correspondeNo correspondeopendoar:27292025-11-06 09:37:03.173FAUBA Digital (UBA-FAUBA) - Universidad de Buenos Aires. Facultad de Agronomíafalse |
| dc.title.none.fl_str_mv |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| title |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| spellingShingle |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans Oreja, Fernando Hugo CROP-WEED COMPETITION DIGITARIA GLYCINE MAX HERBICIDES LARGE CRABGRASS SENSITIVITY ANALYSIS TRANSGENIC CROP |
| title_short |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| title_full |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| title_fullStr |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| title_full_unstemmed |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| title_sort |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans |
| dc.creator.none.fl_str_mv |
Oreja, Fernando Hugo Bastida, Fernando González Andújar, José L. |
| author |
Oreja, Fernando Hugo |
| author_facet |
Oreja, Fernando Hugo Bastida, Fernando González Andújar, José L. |
| author_role |
author |
| author2 |
Bastida, Fernando González Andújar, José L. |
| author2_role |
author author |
| dc.subject.none.fl_str_mv |
CROP-WEED COMPETITION DIGITARIA GLYCINE MAX HERBICIDES LARGE CRABGRASS SENSITIVITY ANALYSIS TRANSGENIC CROP |
| topic |
CROP-WEED COMPETITION DIGITARIA GLYCINE MAX HERBICIDES LARGE CRABGRASS SENSITIVITY ANALYSIS TRANSGENIC CROP |
| dc.description.none.fl_txt_mv |
Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina. A bioeconomic model was developed for decision-making regarding large crabgrass (Digitaria sanguinalis) control in glyphosate-resistant soybeans in the Rolling Pampas of Argentina. The model was used to evaluate the economic returns of four different glyphosate-based strategies for weed control. In the absence of herbicide application (T1), the soil seed bank increases to an equilibrium density of 12,079 seeds m -2 in three years. A single herbicide application during the early stages of the crop (T2), which was intended to be highly effective in the control of an early weed cohort, allows a late, unaffected cohort to produce sufficient seeds to maintain population densities in the soil seed bank. A single, delayed herbicide application (T3), which was intended to control both early and late cohorts, results in a soil seed bank increase up to an equilibrium density similar to that achieved without treatment. Two sequential herbicide applications per year (T4), targeting the two cohorts, leads to a soil seed bank density after 10 years of 107 seeds m -2. Model predictions indicate that in the absence of control measures, a 93 percent reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27 percent) was predicted using strategy T4, which is the most common control measure used by local farmers. This strategy clearly outperforms the other options tested, leading to lower D. sanguinalis seed bank densities and higher soybean yields and economic returns compared to those obtained using the alternative strategies. |
| description |
Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina. |
| publishDate |
2012 |
| dc.date.none.fl_str_mv |
2012 |
| dc.type.none.fl_str_mv |
article info:eu-repo/semantics/article publishedVersion info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
doi:10.4067/S0718-16202012000200006 issn:0304-5609 http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2012Oreja |
| identifier_str_mv |
doi:10.4067/S0718-16202012000200006 issn:0304-5609 |
| url |
http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2012Oreja |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess openAccess http://ri.agro.uba.ar/greenstone3/library/page/biblioteca#section4 |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
openAccess http://ri.agro.uba.ar/greenstone3/library/page/biblioteca#section4 |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.source.none.fl_str_mv |
Ciencia e Investigación Agraria Vol.39, no.2 299-308 http://agronomia.uc.cl/ reponame:FAUBA Digital (UBA-FAUBA) instname:Universidad de Buenos Aires. Facultad de Agronomía |
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FAUBA Digital (UBA-FAUBA) |
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FAUBA Digital (UBA-FAUBA) |
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Universidad de Buenos Aires. Facultad de Agronomía |
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FAUBA Digital (UBA-FAUBA) - Universidad de Buenos Aires. Facultad de Agronomía |
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martino@agro.uba.ar;berasa@agro.uba.ar |
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