Interactive system for integrated weed management. I. Weed identification
Autor(a) principal: | |
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Data de Publicação: | 1998 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | spa |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/4906 |
Resumo: | The success of sustainable agroecosystems is closely linked to the availability of high quality information. This sort of information will optimize management and decision making, improving profits and lowering the agrochemicals impact in the agroecosystems. This is the aim of SITRAMA (Interactive System for Weed Management), a system that deals with the weed management within soybean crop context, using knowledge engineering techniques. SITRAMA comprises four modules. The first one deals with weed recognition at seedling stage; the second is concerned with the different control and management strategies which take into account the crop system variables; the third deals with crop losses taken into account weed density & distribution; and the fourth is concerned with economic analysis under conventional techniques (revenues/costs) or novel ones (margin maximisation, risks & uncertainty). The goal of this paper is to present the developement of the first module, - weed recognition -, stressing the strategies followed to achieve the identification goal. The strategies used simplify the conventional dicotomic classification, focusing into relevant characters of the seedling. In such a way, information required to the user is minimized, emulating an expert reasoning. |
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Interactive system for integrated weed management. I. Weed identificationSistema interactivo para el tratamiento integral de malezas. I. Identificacion de malezasSistema interactivo para el tratamiento integral de malezas. I. Identificacion de malezasThe success of sustainable agroecosystems is closely linked to the availability of high quality information. This sort of information will optimize management and decision making, improving profits and lowering the agrochemicals impact in the agroecosystems. This is the aim of SITRAMA (Interactive System for Weed Management), a system that deals with the weed management within soybean crop context, using knowledge engineering techniques. SITRAMA comprises four modules. The first one deals with weed recognition at seedling stage; the second is concerned with the different control and management strategies which take into account the crop system variables; the third deals with crop losses taken into account weed density & distribution; and the fourth is concerned with economic analysis under conventional techniques (revenues/costs) or novel ones (margin maximisation, risks & uncertainty). The goal of this paper is to present the developement of the first module, - weed recognition -, stressing the strategies followed to achieve the identification goal. The strategies used simplify the conventional dicotomic classification, focusing into relevant characters of the seedling. In such a way, information required to the user is minimized, emulating an expert reasoning.La viabilidad de los sistemas agropecuarios sustentables está estrechamente vinculada con la disponibilidad de información de alta calidad que permita optimizar la toma de decisiones, maximizando la rentabilidad y disminuyendo el impacto ambiental de la agricultura. Con este propósito surge el Sistema Interactivo para el Tratamiento Integral de Malezas (SITRAMA), un sistema que se ocupa de la problemática de las malezas en cultivos de soja utilizando las técnicas de Ingeniería del Conocimiento. El conocimiento consta de cuatro módulos. El primero trata el reconocimiento de las malezas en estado de plántula; el segundo encara el problema del control de las malezas, considerando diferentes estrategias que tengan en cuenta variables del sistema de cultivo; el tercero calcula las pérdidas por competencia, teniendo en cuenta la densidad y distribución de malezas; y el cuarto realiza el análisis económico, tanto bajo un enfoque convencional (relación costo/beneficio) como novel (maximización de márgenes/ riesgo e incertidumbre). El objetivo de este artículo es presentar el desarrollo del primer módulo: el reconocimiento de una maleza en estado de plántula, destacando las estrategias seguidas para su clasificación. Esas estrategias simplifican la clasificación dicotómica, polarizando el reconocimiento en base a rasgos relevantes de las plántulas. De esta forma se minimiza la información sobre la plántula requerida al usuario, y se emula el razonamiento experto, arribando al reconocimiento de la maleza de forma mucho más rápida.La viabilidad de los sistemas agropecuarios sustentables está estrechamente vinculada con la disponibilidad de información de alta calidad que permita optimizar la toma de decisiones, maximizando la rentabilidad y disminuyendo el impacto ambiental de la agricultura. Con este propósito surge el Sistema Interactivo para el Tratamiento Integral de Malezas (SITRAMA), un sistema que se ocupa de la problemática de las malezas en cultivos de soja utilizando las técnicas de Ingeniería del Conocimiento. El conocimiento consta de cuatro módulos. El primero trata el reconocimiento de las malezas en estado de plántula; el segundo encara el problema del control de las malezas, considerando diferentes estrategias que tengan en cuenta variables del sistema de cultivo; el tercero calcula las pérdidas por competencia, teniendo en cuenta la densidad y distribución de malezas; y el cuarto realiza el análisis económico, tanto bajo un enfoque convencional (relación costo/beneficio) como novel (maximización de márgenes/ riesgo e incertidumbre). El objetivo de este artículo es presentar el desarrollo del primer módulo: el reconocimiento de una maleza en estado de plántula, destacando las estrategias seguidas para su clasificación. Esas estrategias simplifican la clasificación dicotómica, polarizando el reconocimiento en base a rasgos relevantes de las plántulas. De esta forma se minimiza la información sobre la plántula requerida al usuario, y se emula el razonamiento experto, arribando al reconocimiento de la maleza de forma mucho más rápida.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCasali, AnaCorti, RosaDip, LeonorFaccini, DelmaLeguizamon, EduardoPluss, Jorge JuanD'Agostino, Estela1998-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/4906Pesquisa Agropecuaria Brasileira; v.33, n.6, jun. 1998; 809-821Pesquisa Agropecuária Brasileira; v.33, n.6, jun. 1998; 809-8211678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAspahttps://seer.sct.embrapa.br/index.php/pab/article/view/4906/7031info:eu-repo/semantics/openAccess2014-12-08T18:25:51Zoai:ojs.seer.sct.embrapa.br:article/4906Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2014-12-08T18:25:51Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Interactive system for integrated weed management. I. Weed identification Sistema interactivo para el tratamiento integral de malezas. I. Identificacion de malezas Sistema interactivo para el tratamiento integral de malezas. I. Identificacion de malezas |
title |
Interactive system for integrated weed management. I. Weed identification |
spellingShingle |
Interactive system for integrated weed management. I. Weed identification Casali, Ana |
title_short |
Interactive system for integrated weed management. I. Weed identification |
title_full |
Interactive system for integrated weed management. I. Weed identification |
title_fullStr |
Interactive system for integrated weed management. I. Weed identification |
title_full_unstemmed |
Interactive system for integrated weed management. I. Weed identification |
title_sort |
Interactive system for integrated weed management. I. Weed identification |
author |
Casali, Ana |
author_facet |
Casali, Ana Corti, Rosa Dip, Leonor Faccini, Delma Leguizamon, Eduardo Pluss, Jorge Juan D'Agostino, Estela |
author_role |
author |
author2 |
Corti, Rosa Dip, Leonor Faccini, Delma Leguizamon, Eduardo Pluss, Jorge Juan D'Agostino, Estela |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Casali, Ana Corti, Rosa Dip, Leonor Faccini, Delma Leguizamon, Eduardo Pluss, Jorge Juan D'Agostino, Estela |
dc.subject.none.fl_str_mv |
|
description |
The success of sustainable agroecosystems is closely linked to the availability of high quality information. This sort of information will optimize management and decision making, improving profits and lowering the agrochemicals impact in the agroecosystems. This is the aim of SITRAMA (Interactive System for Weed Management), a system that deals with the weed management within soybean crop context, using knowledge engineering techniques. SITRAMA comprises four modules. The first one deals with weed recognition at seedling stage; the second is concerned with the different control and management strategies which take into account the crop system variables; the third deals with crop losses taken into account weed density & distribution; and the fourth is concerned with economic analysis under conventional techniques (revenues/costs) or novel ones (margin maximisation, risks & uncertainty). The goal of this paper is to present the developement of the first module, - weed recognition -, stressing the strategies followed to achieve the identification goal. The strategies used simplify the conventional dicotomic classification, focusing into relevant characters of the seedling. In such a way, information required to the user is minimized, emulating an expert reasoning. |
publishDate |
1998 |
dc.date.none.fl_str_mv |
1998-06-01 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/4906 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/4906 |
dc.language.iso.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/4906/7031 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; v.33, n.6, jun. 1998; 809-821 Pesquisa Agropecuária Brasileira; v.33, n.6, jun. 1998; 809-821 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
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Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
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EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
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Pesquisa Agropecuária Brasileira (Online) |
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Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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