Spatial relation of weed competition and soil fertility in soybean farming
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.21475/ajcs.22.16.07.p3548 http://hdl.handle.net/11449/245966 |
Resumo: | Soybean is one of the main crops in Brazil, with a significant share of national agribusiness exports. Nonetheless, several factors such as weed competition and soil fertility directly affect soybean yield and productivity. This study aimed to analyse the spatial distribution of weeds as a function of soil fertility and soybean yield in farming fields. We carried out the experiment on a farm located in Brejo, Maranhão state, Brazil, through a geostatistical analysis of 60 sampling points on a regular grid of 10.0 m x 50.0 m. At these points, we collected phytosociological information on the weed community, soil fertility, and soybean yield. We performed principal component analysis (PCA) to determine the most responsive variables and to group them. We determined spatial dependence through geostatistical procedures, with the interpretation and adjustment of variogram components. We identified seven weed species, distributed across seven genera and six botanical families, of which 76.78% were eudicotyledons. In the cluster analysis, we grouped monocotyledonous species separately from eudicotyledons as explained by the morphophysiological contrasts between these botanical classes. Soybean yield did not correlate with soil fertility or weeds. These two factors can be considered only as a share of soybean productivity because their individual variations do not directly influence production factors. The efficient management of weeds and soil fertility should result in a more uniform and potencially more soybean yield when other conditioning factors are also effective. |
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Spatial relation of weed competition and soil fertility in soybean farmingGeostatisticsGlycine max (l.)MerrilPrincipal component analysisProductivitySoybean is one of the main crops in Brazil, with a significant share of national agribusiness exports. Nonetheless, several factors such as weed competition and soil fertility directly affect soybean yield and productivity. This study aimed to analyse the spatial distribution of weeds as a function of soil fertility and soybean yield in farming fields. We carried out the experiment on a farm located in Brejo, Maranhão state, Brazil, through a geostatistical analysis of 60 sampling points on a regular grid of 10.0 m x 50.0 m. At these points, we collected phytosociological information on the weed community, soil fertility, and soybean yield. We performed principal component analysis (PCA) to determine the most responsive variables and to group them. We determined spatial dependence through geostatistical procedures, with the interpretation and adjustment of variogram components. We identified seven weed species, distributed across seven genera and six botanical families, of which 76.78% were eudicotyledons. In the cluster analysis, we grouped monocotyledonous species separately from eudicotyledons as explained by the morphophysiological contrasts between these botanical classes. Soybean yield did not correlate with soil fertility or weeds. These two factors can be considered only as a share of soybean productivity because their individual variations do not directly influence production factors. The efficient management of weeds and soil fertility should result in a more uniform and potencially more soybean yield when other conditioning factors are also effective.Universidade Federal do Maranhão, CEP 65.500-000,MAUniversidade Federal do Tocantins, CEP 77.804-970,TOUniversidade Estadual Paulista Júlio Mesquita Filho, CEP 14.884-900,SPUniversidade Estadual Paulista Júlio Mesquita Filho, CEP 14.884-900,SPUniversidade Federal do MaranhãoUniversidade Federal do TocantinsUniversidade Estadual Paulista (UNESP)Furtado, José Augusto LimaAlmeida, Edmilson Igor Bernardode Oliveira, Leonardo Bernardes Tavernydos Santos, Antonio Clementinoda Costa, Tiago Vieirada Silva, Marcelo de SousaSouza, Jarlyson Bruno Costa [UNESP]da Silva Sousa, WashingtonPonte, Islana SilvaFreitas, José Roberto Brito2023-07-29T12:28:08Z2023-07-29T12:28:08Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article899-906http://dx.doi.org/10.21475/ajcs.22.16.07.p3548Australian Journal of Crop Science, v. 16, n. 7, p. 899-906, 2022.1835-27071835-2693http://hdl.handle.net/11449/24596610.21475/ajcs.22.16.07.p35482-s2.0-85138659349Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAustralian Journal of Crop Scienceinfo:eu-repo/semantics/openAccess2023-07-29T12:28:08Zoai:repositorio.unesp.br:11449/245966Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:45:49.413344Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Spatial relation of weed competition and soil fertility in soybean farming |
title |
Spatial relation of weed competition and soil fertility in soybean farming |
spellingShingle |
Spatial relation of weed competition and soil fertility in soybean farming Furtado, José Augusto Lima Geostatistics Glycine max (l.) Merril Principal component analysis Productivity |
title_short |
Spatial relation of weed competition and soil fertility in soybean farming |
title_full |
Spatial relation of weed competition and soil fertility in soybean farming |
title_fullStr |
Spatial relation of weed competition and soil fertility in soybean farming |
title_full_unstemmed |
Spatial relation of weed competition and soil fertility in soybean farming |
title_sort |
Spatial relation of weed competition and soil fertility in soybean farming |
author |
Furtado, José Augusto Lima |
author_facet |
Furtado, José Augusto Lima Almeida, Edmilson Igor Bernardo de Oliveira, Leonardo Bernardes Taverny dos Santos, Antonio Clementino da Costa, Tiago Vieira da Silva, Marcelo de Sousa Souza, Jarlyson Bruno Costa [UNESP] da Silva Sousa, Washington Ponte, Islana Silva Freitas, José Roberto Brito |
author_role |
author |
author2 |
Almeida, Edmilson Igor Bernardo de Oliveira, Leonardo Bernardes Taverny dos Santos, Antonio Clementino da Costa, Tiago Vieira da Silva, Marcelo de Sousa Souza, Jarlyson Bruno Costa [UNESP] da Silva Sousa, Washington Ponte, Islana Silva Freitas, José Roberto Brito |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal do Maranhão Universidade Federal do Tocantins Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Furtado, José Augusto Lima Almeida, Edmilson Igor Bernardo de Oliveira, Leonardo Bernardes Taverny dos Santos, Antonio Clementino da Costa, Tiago Vieira da Silva, Marcelo de Sousa Souza, Jarlyson Bruno Costa [UNESP] da Silva Sousa, Washington Ponte, Islana Silva Freitas, José Roberto Brito |
dc.subject.por.fl_str_mv |
Geostatistics Glycine max (l.) Merril Principal component analysis Productivity |
topic |
Geostatistics Glycine max (l.) Merril Principal component analysis Productivity |
description |
Soybean is one of the main crops in Brazil, with a significant share of national agribusiness exports. Nonetheless, several factors such as weed competition and soil fertility directly affect soybean yield and productivity. This study aimed to analyse the spatial distribution of weeds as a function of soil fertility and soybean yield in farming fields. We carried out the experiment on a farm located in Brejo, Maranhão state, Brazil, through a geostatistical analysis of 60 sampling points on a regular grid of 10.0 m x 50.0 m. At these points, we collected phytosociological information on the weed community, soil fertility, and soybean yield. We performed principal component analysis (PCA) to determine the most responsive variables and to group them. We determined spatial dependence through geostatistical procedures, with the interpretation and adjustment of variogram components. We identified seven weed species, distributed across seven genera and six botanical families, of which 76.78% were eudicotyledons. In the cluster analysis, we grouped monocotyledonous species separately from eudicotyledons as explained by the morphophysiological contrasts between these botanical classes. Soybean yield did not correlate with soil fertility or weeds. These two factors can be considered only as a share of soybean productivity because their individual variations do not directly influence production factors. The efficient management of weeds and soil fertility should result in a more uniform and potencially more soybean yield when other conditioning factors are also effective. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 2023-07-29T12:28:08Z 2023-07-29T12:28:08Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.21475/ajcs.22.16.07.p3548 Australian Journal of Crop Science, v. 16, n. 7, p. 899-906, 2022. 1835-2707 1835-2693 http://hdl.handle.net/11449/245966 10.21475/ajcs.22.16.07.p3548 2-s2.0-85138659349 |
url |
http://dx.doi.org/10.21475/ajcs.22.16.07.p3548 http://hdl.handle.net/11449/245966 |
identifier_str_mv |
Australian Journal of Crop Science, v. 16, n. 7, p. 899-906, 2022. 1835-2707 1835-2693 10.21475/ajcs.22.16.07.p3548 2-s2.0-85138659349 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Australian Journal of Crop Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
899-906 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128273163485184 |