Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans
- Autores
- Oreja, Fernando Hugo; Bastida, Fernando; Gonzalez Andújar, José L.
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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% reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27%) 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.
Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cultivos Industriales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina
Fil: Bastida, Fernando. Universidad de Huelva; España
Fil: Gonzalez Andújar, José L.. Consejo Superior de Investigaciones Científicas; España - Materia
-
CROP-WEED COMPETITION
DIGITARIA
GLYCINE MAX
HERBICIDES
LARGE CRABGRASS
SENSITIVITY ANALYSIS
TRANSGENIC CROP - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/118298
Ver los metadatos del registro completo
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Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeansSimulación de estrategias de control para la toma de decisión de Digitaria sanguinalis en soja resistente a glifosatoOreja, Fernando HugoBastida, FernandoGonzalez Andújar, José L.CROP-WEED COMPETITIONDIGITARIAGLYCINE MAXHERBICIDESLARGE CRABGRASSSENSITIVITY ANALYSISTRANSGENIC CROPhttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4A 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% reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27%) 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.Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cultivos Industriales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Bastida, Fernando. Universidad de Huelva; EspañaFil: Gonzalez Andújar, José L.. Consejo Superior de Investigaciones Científicas; EspañaPontificia Universidad Católica Chile2012-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/118298Oreja, Fernando Hugo; Bastida, Fernando; Gonzalez Andújar, José L.; Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans; Pontificia Universidad Católica Chile; Ciencia e Investigación Agraria; 39; 2; 8-2012; 299-3080304-56090718-1620CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-16202012000200006info:eu-repo/semantics/altIdentifier/doi/10.4067/S0718-16202012000200006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T10:48:30Zoai:ri.conicet.gov.ar:11336/118298instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-05 10:48:30.886CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans Simulación de estrategias de control para la toma de decisión de Digitaria sanguinalis en soja resistente a glifosato |
| 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 Gonzalez Andújar, José L. |
| author |
Oreja, Fernando Hugo |
| author_facet |
Oreja, Fernando Hugo Bastida, Fernando Gonzalez Andújar, José L. |
| author_role |
author |
| author2 |
Bastida, Fernando Gonzalez 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 |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.1 https://purl.org/becyt/ford/4 |
| dc.description.none.fl_txt_mv |
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% reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27%) 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. Fil: Oreja, Fernando Hugo. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cultivos Industriales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina Fil: Bastida, Fernando. Universidad de Huelva; España Fil: Gonzalez Andújar, José L.. Consejo Superior de Investigaciones Científicas; España |
| description |
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% reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27%) 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. |
| publishDate |
2012 |
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2012-08 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
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http://hdl.handle.net/11336/118298 Oreja, Fernando Hugo; Bastida, Fernando; Gonzalez Andújar, José L.; Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans; Pontificia Universidad Católica Chile; Ciencia e Investigación Agraria; 39; 2; 8-2012; 299-308 0304-5609 0718-1620 CONICET Digital CONICET |
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http://hdl.handle.net/11336/118298 |
| identifier_str_mv |
Oreja, Fernando Hugo; Bastida, Fernando; Gonzalez Andújar, José L.; Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans; Pontificia Universidad Católica Chile; Ciencia e Investigación Agraria; 39; 2; 8-2012; 299-308 0304-5609 0718-1620 CONICET Digital CONICET |
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eng |
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Pontificia Universidad Católica Chile |
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Pontificia Universidad Católica Chile |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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