A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields

New technologies, such as Differential Global Positioning Systems (DGPS) and Geographic Information Systems (GIS), may be useful in order to create models to predict the spatio-temporal behaviour of weeds. The aim of this study was to generate a geometric model able to predict the patch expansion of...

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Authors: Andújar, Dionisio, Rodriguez, X., Rueda-Ayala, Víctor, Ribeiro Seijas, Ángela, Fernández Quintanilla, Cesar, Dorado, Jose
Format: article
Status:Published version
Publication Date:2017
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/375103
Online Access:http://hdl.handle.net/10261/375103
Access Level:Open access
Keyword:Triangular modeling
Rectangular modeling
Weed infestation
Tillage
Site-specific weed management (SSWM)
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spelling A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize FieldsAndújar, DionisioRodriguez, X.Rueda-Ayala, VíctorRibeiro Seijas, ÁngelaFernández Quintanilla, CesarDorado, JoseTriangular modelingRectangular modelingWeed infestationTillageSite-specific weed management (SSWM)New technologies, such as Differential Global Positioning Systems (DGPS) and Geographic Information Systems (GIS), may be useful in order to create models to predict the spatio-temporal behaviour of weeds. The aim of this study was to generate a geometric model able to predict the patch expansion of S. halepense, a problematic perennial weed in maize crops in Central Spain. From previous infestation maps, the model describes new possible spreading areas for the upcoming growing season, and therefore, herbicide treatments can be planned on time. Two different experiments were implemented, in which initial patch density and size were examined. Patches of different size (1, 10 and 100 m2) and density (4, 20 and 100 shoots m−2), were established. These patches were visually identified, their perimeter defined and their density characterized, during three growing seasons (from 2008 to 2010 campaigns). According to this information different descriptors were built: (1) area and density of each patch; (2) the relative growth in width and length, according to space and time and compared with previous years; and (3) the increased density ratio, calculated in relation of patch size and distance to previous patch in the new infestation areas of expansion. All these descriptors were added to the model in order to predict the patch expansion in the last studied season (i. e., 2010) using previous maps (i. e., season 2008 and 2009). The model uses geometrical assimilation to predict, and two expansion assumptions were considered: (a) a conservative approach based on triangular geometry; and (b) a rectangular geometry which maximizes the simulated infested area. The results were compared with the ground truth map created in 2010. Each method showed weaknesses and strengths. The triangular approach minimized the infested area, mainly in the small patches, and therefore it could predict the expansion of previously established patches, but not the emergence of new ones. In contrast, the rectangular approach simulated the position of new foci, maximizing the infested area. Therefore, although a substantial reduction of herbicides is possible using both models, a final decision must be taken individually for each field.The Spanish Ministry of Economy and Competitiveness has provided support for this research via project AGL2014-52465-C4-3.Peer reviewedSpringer NatureMinisterio de Economía y Competitividad (España)Andújar, Dionisio [0000-0002-5801-0944]Rodriguez, X.Rueda-Ayala, Víctor [ 0000-0002-9159-8276]Ribeiro, Angela [ 0000-0003-1453-5631]Fernández Quintanilla, Cesar [ 0000-0002-2886-9176]Dorado, José [ 0000-0002-2268-2562]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202420242017info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/375103reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/MINECO//AGL2014-52465-C4-3-Rhttps://doi.org/10.1007/s10343-017-0388-6Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3751032026-05-22T06:33:51Z
dc.title.none.fl_str_mv A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
title A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
spellingShingle A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
Andújar, Dionisio
Triangular modeling
Rectangular modeling
Weed infestation
Tillage
Site-specific weed management (SSWM)
title_short A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
title_full A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
title_fullStr A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
title_full_unstemmed A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
title_sort A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields
dc.creator.none.fl_str_mv Andújar, Dionisio
Rodriguez, X.
Rueda-Ayala, Víctor
Ribeiro Seijas, Ángela
Fernández Quintanilla, Cesar
Dorado, Jose
author Andújar, Dionisio
author_facet Andújar, Dionisio
Rodriguez, X.
Rueda-Ayala, Víctor
Ribeiro Seijas, Ángela
Fernández Quintanilla, Cesar
Dorado, Jose
author_role author
author2 Rodriguez, X.
Rueda-Ayala, Víctor
Ribeiro Seijas, Ángela
Fernández Quintanilla, Cesar
Dorado, Jose
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
Andújar, Dionisio [0000-0002-5801-0944]
Rodriguez, X.
Rueda-Ayala, Víctor [ 0000-0002-9159-8276]
Ribeiro, Angela [ 0000-0003-1453-5631]
Fernández Quintanilla, Cesar [ 0000-0002-2886-9176]
Dorado, José [ 0000-0002-2268-2562]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Triangular modeling
Rectangular modeling
Weed infestation
Tillage
Site-specific weed management (SSWM)
topic Triangular modeling
Rectangular modeling
Weed infestation
Tillage
Site-specific weed management (SSWM)
description New technologies, such as Differential Global Positioning Systems (DGPS) and Geographic Information Systems (GIS), may be useful in order to create models to predict the spatio-temporal behaviour of weeds. The aim of this study was to generate a geometric model able to predict the patch expansion of S. halepense, a problematic perennial weed in maize crops in Central Spain. From previous infestation maps, the model describes new possible spreading areas for the upcoming growing season, and therefore, herbicide treatments can be planned on time. Two different experiments were implemented, in which initial patch density and size were examined. Patches of different size (1, 10 and 100 m2) and density (4, 20 and 100 shoots m−2), were established. These patches were visually identified, their perimeter defined and their density characterized, during three growing seasons (from 2008 to 2010 campaigns). According to this information different descriptors were built: (1) area and density of each patch; (2) the relative growth in width and length, according to space and time and compared with previous years; and (3) the increased density ratio, calculated in relation of patch size and distance to previous patch in the new infestation areas of expansion. All these descriptors were added to the model in order to predict the patch expansion in the last studied season (i. e., 2010) using previous maps (i. e., season 2008 and 2009). The model uses geometrical assimilation to predict, and two expansion assumptions were considered: (a) a conservative approach based on triangular geometry; and (b) a rectangular geometry which maximizes the simulated infested area. The results were compared with the ground truth map created in 2010. Each method showed weaknesses and strengths. The triangular approach minimized the infested area, mainly in the small patches, and therefore it could predict the expansion of previously established patches, but not the emergence of new ones. In contrast, the rectangular approach simulated the position of new foci, maximizing the infested area. Therefore, although a substantial reduction of herbicides is possible using both models, a final decision must be taken individually for each field.
publishDate 2017
dc.date.none.fl_str_mv 2017
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/375103
url http://hdl.handle.net/10261/375103
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/MINECO//AGL2014-52465-C4-3-R
https://doi.org/10.1007/s10343-017-0388-6
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.198674

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