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
FAUBA Digital (UBA-FAUBA)
Institución
Universidad de Buenos Aires. Facultad de Agronomía
OAI Identificador
snrd:2012Oreja

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oai_identifier_str snrd:2012Oreja
network_acronym_str FAUBA
repository_id_str 2729
network_name_str FAUBA Digital (UBA-FAUBA)
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
reponame_str FAUBA Digital (UBA-FAUBA)
collection FAUBA Digital (UBA-FAUBA)
instname_str Universidad de Buenos Aires. Facultad de Agronomía
repository.name.fl_str_mv FAUBA Digital (UBA-FAUBA) - Universidad de Buenos Aires. Facultad de Agronomía
repository.mail.fl_str_mv martino@agro.uba.ar;berasa@agro.uba.ar
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