Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão

Detalhes bibliográficos
Autor(a) principal: Baio, Fabio Henrique Rojo
Data de Publicação: 2020
Outros Autores: Faraun, Rafael da Silva, Teodoro, Paulo Eduardo, Silva, Alexandra Fagioli da, Neves, Danilo Carvalho, Azevedo, Gileno Brito de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Veras
Texto Completo: https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/6899
Resumo: One approach for using variable rate fertilizer applications in precision agriculture is to divide an area into management zones. The objectives were: (i) to identify the chemical, physical and phenological properties that have the highest correlation with the yield; (ii) to use principal component analysis (PCA) to identify what physical, chemical, and phenological properties contribute to greater spatial variability; (iii) and to use these variables in the establishing management zones (MZ) for cotton through fuzzy k-means clustering analysis, associated with the geostatistics technique by the ordinary kriging method. The experiment was carried out in a cotton field in the Chapadões region in 2015. Phenological variables of cotton (plant height, number of bolls, number of capsules, opening percentage and Red Edge vegetation index) and chemical (pH, Ca, Mg, H+Al, V%, Ca/Mg, CEC, K, Al3+ and P) and physical (total soil porosity, soil density, soil moisture, soil mechanical resistance to penetration, clay content, and macro and micro-porosity) attributes of the soil were evaluated to define management zones. The variables that showed the highest correlation with cotton yield were pH, phosphorus, soil moisture measured at 39 and 70 days after cotton emergence (DAE), number of bolls at 107 DAE and red edge vegetation index at 53 DAE. The map with four MZ has a better representation, being the most indicated in the management of agricultural inputs applications at variable rates aiming to increase the cotton yield in the Brazilian Cerrado.
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spelling Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodãoGossypium hirsutumprecision agriculturemultivariate analysis.One approach for using variable rate fertilizer applications in precision agriculture is to divide an area into management zones. The objectives were: (i) to identify the chemical, physical and phenological properties that have the highest correlation with the yield; (ii) to use principal component analysis (PCA) to identify what physical, chemical, and phenological properties contribute to greater spatial variability; (iii) and to use these variables in the establishing management zones (MZ) for cotton through fuzzy k-means clustering analysis, associated with the geostatistics technique by the ordinary kriging method. The experiment was carried out in a cotton field in the Chapadões region in 2015. Phenological variables of cotton (plant height, number of bolls, number of capsules, opening percentage and Red Edge vegetation index) and chemical (pH, Ca, Mg, H+Al, V%, Ca/Mg, CEC, K, Al3+ and P) and physical (total soil porosity, soil density, soil moisture, soil mechanical resistance to penetration, clay content, and macro and micro-porosity) attributes of the soil were evaluated to define management zones. The variables that showed the highest correlation with cotton yield were pH, phosphorus, soil moisture measured at 39 and 70 days after cotton emergence (DAE), number of bolls at 107 DAE and red edge vegetation index at 53 DAE. The map with four MZ has a better representation, being the most indicated in the management of agricultural inputs applications at variable rates aiming to increase the cotton yield in the Brazilian Cerrado.Brazilian Journals Publicações de Periódicos e Editora Ltda.2020-02-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/689910.34117/bjdv6n2-151Brazilian Journal of Development; Vol. 6 No. 2 (2020); 7393-7407Brazilian Journal of Development; Vol. 6 Núm. 2 (2020); 7393-7407Brazilian Journal of Development; v. 6 n. 2 (2020); 7393-74072525-8761reponame:Revista Verasinstname:Instituto Superior de Educação Vera Cruz (VeraCruz)instacron:VERACRUZenghttps://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/6899/6081Copyright (c) 2020 Brazilian Journal of Developmentinfo:eu-repo/semantics/openAccessBaio, Fabio Henrique RojoFaraun, Rafael da SilvaTeodoro, Paulo EduardoSilva, Alexandra Fagioli daNeves, Danilo CarvalhoAzevedo, Gileno Brito de2020-03-18T16:24:26Zoai:ojs2.ojs.brazilianjournals.com.br:article/6899Revistahttp://site.veracruz.edu.br:8087/instituto/revistaveras/index.php/revistaveras/PRIhttp://site.veracruz.edu.br:8087/instituto/revistaveras/index.php/revistaveras/oai||revistaveras@veracruz.edu.br2236-57292236-5729opendoar:2024-10-15T16:05:06.235023Revista Veras - Instituto Superior de Educação Vera Cruz (VeraCruz)false
dc.title.none.fl_str_mv Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
title Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
spellingShingle Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
Baio, Fabio Henrique Rojo
Gossypium hirsutum
precision agriculture
multivariate analysis.
title_short Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
title_full Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
title_fullStr Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
title_full_unstemmed Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
title_sort Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
author Baio, Fabio Henrique Rojo
author_facet Baio, Fabio Henrique Rojo
Faraun, Rafael da Silva
Teodoro, Paulo Eduardo
Silva, Alexandra Fagioli da
Neves, Danilo Carvalho
Azevedo, Gileno Brito de
author_role author
author2 Faraun, Rafael da Silva
Teodoro, Paulo Eduardo
Silva, Alexandra Fagioli da
Neves, Danilo Carvalho
Azevedo, Gileno Brito de
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Baio, Fabio Henrique Rojo
Faraun, Rafael da Silva
Teodoro, Paulo Eduardo
Silva, Alexandra Fagioli da
Neves, Danilo Carvalho
Azevedo, Gileno Brito de
dc.subject.por.fl_str_mv Gossypium hirsutum
precision agriculture
multivariate analysis.
topic Gossypium hirsutum
precision agriculture
multivariate analysis.
description One approach for using variable rate fertilizer applications in precision agriculture is to divide an area into management zones. The objectives were: (i) to identify the chemical, physical and phenological properties that have the highest correlation with the yield; (ii) to use principal component analysis (PCA) to identify what physical, chemical, and phenological properties contribute to greater spatial variability; (iii) and to use these variables in the establishing management zones (MZ) for cotton through fuzzy k-means clustering analysis, associated with the geostatistics technique by the ordinary kriging method. The experiment was carried out in a cotton field in the Chapadões region in 2015. Phenological variables of cotton (plant height, number of bolls, number of capsules, opening percentage and Red Edge vegetation index) and chemical (pH, Ca, Mg, H+Al, V%, Ca/Mg, CEC, K, Al3+ and P) and physical (total soil porosity, soil density, soil moisture, soil mechanical resistance to penetration, clay content, and macro and micro-porosity) attributes of the soil were evaluated to define management zones. The variables that showed the highest correlation with cotton yield were pH, phosphorus, soil moisture measured at 39 and 70 days after cotton emergence (DAE), number of bolls at 107 DAE and red edge vegetation index at 53 DAE. The map with four MZ has a better representation, being the most indicated in the management of agricultural inputs applications at variable rates aiming to increase the cotton yield in the Brazilian Cerrado.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-14
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://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/6899
10.34117/bjdv6n2-151
url https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/6899
identifier_str_mv 10.34117/bjdv6n2-151
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/6899/6081
dc.rights.driver.fl_str_mv Copyright (c) 2020 Brazilian Journal of Development
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Brazilian Journal of Development
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Brazilian Journals Publicações de Periódicos e Editora Ltda.
publisher.none.fl_str_mv Brazilian Journals Publicações de Periódicos e Editora Ltda.
dc.source.none.fl_str_mv Brazilian Journal of Development; Vol. 6 No. 2 (2020); 7393-7407
Brazilian Journal of Development; Vol. 6 Núm. 2 (2020); 7393-7407
Brazilian Journal of Development; v. 6 n. 2 (2020); 7393-7407
2525-8761
reponame:Revista Veras
instname:Instituto Superior de Educação Vera Cruz (VeraCruz)
instacron:VERACRUZ
instname_str Instituto Superior de Educação Vera Cruz (VeraCruz)
instacron_str VERACRUZ
institution VERACRUZ
reponame_str Revista Veras
collection Revista Veras
repository.name.fl_str_mv Revista Veras - Instituto Superior de Educação Vera Cruz (VeraCruz)
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