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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/118298

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spelling 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
dc.date.none.fl_str_mv 2012-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
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 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
url 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
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-16202012000200006
info:eu-repo/semantics/altIdentifier/doi/10.4067/S0718-16202012000200006
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pontificia Universidad Católica Chile
publisher.none.fl_str_mv Pontificia Universidad Católica Chile
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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