Show simple item record

dc.contributor.authorOreja, Fernando H.
dc.contributor.authorBastida Milián, Fernando 
dc.contributor.authorGonzález Andújar, José Luis
dc.date.accessioned2017-03-16T12:35:54Z
dc.date.available2017-03-16T12:35:54Z
dc.date.issued2012
dc.identifier.citationOreja, F.H., Bastida Milián, F., González Andújar, J.L.: "Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans". Ciencia e Investigación Agraria. Vol. 39, n. 2, págs. 299-308, (2012). DOI: 10.4067/S0718-16202012000200006en_US
dc.identifier.issn10.4067/S0718-16202012000200006
dc.identifier.issn0718-1620
dc.identifier.urihttp://hdl.handle.net/10272/13453
dc.description.abstractA bioeconomic model was developed for decision-making regarding large crabgrass (Digitaria sanguinalis) control in glyphosate-resistant soybeans in the Rolling Pampas ofArgentina. 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.en_US
dc.description.sponsorshipThis work was supported in part by FEDER funds and the Spanish Ministry of Innovation and Science (project AGL 2009-7883). We thank the Carolina Foundation for providing a grant to the first author, and we also thank Pilar Castro, Dr. Leguizamon and Dr. Tuesca for their help with this work.en_US
dc.language.isospaen_US
dc.publisherPontificia Universidad Católica de Chileen_US
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherCrop-weed competitionen_US
dc.subject.otherDigitariaen_US
dc.subject.otherHerbicidesen_US
dc.subject.otherGlycine maxen_US
dc.subject.otherLarge crabgrassen_US
dc.subject.otherSensitivity analysisen_US
dc.subject.otherTransgenic cropen_US
dc.titleSimulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeansen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Spanish Ministry of Innovation and Science [AGL 2009-7883]en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Atribución-NoComercial-SinDerivadas 3.0 España
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España

Copyright © 2008-2010. ARIAS MONTANO. Repositorio Institucional de la Universidad de Huelva
Contact Us | Send Feedback |