Correlations and Principal Components Analysis for Defining Management Zones in Cotton / Correlações e análise de componentes principais para definir zonas de gerenciamento em algodão
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
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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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) |
repository.mail.fl_str_mv |
||revistaveras@veracruz.edu.br |
_version_ |
1813645439663079424 |