Precision agriculture to study soil chemical properties and the yield of a coffee field
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Coffee Science (Online) |
Texto Completo: | https://coffeescience.ufla.br/index.php/Coffeescience/article/view/204 |
Resumo: | Precision agriculture appears as an important tool in the management of coffee farms where the knowledge of some soil fertility characteristics associated with the coffee production could help in specific application of fertilizers with positive environmental and economic results. So the aim of this article was to use precision agriculture and geoestatistics to evaluate the availability of phosphorus, potassium and yield of the coffee plant by evaluating the semivariogram and kriging maps and show that these tools are important for coffee management. This study was conducted on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base we used soil chemical property data obtained by sampling in a georreferenced location using a quadricycle with a sampler and a GPS, and the yield data was obtained from manual harvest on the georreferenced location. The analysis of these data by using statistics and geostatistics tools allowed to characterize the spatial variability of the phosphorus, potassium, and the coffee yield, and allowed to analyze the relation among these variables. It was possible to observe that spatial dependence exists so it is possible to create maps of spatial distribution of the variables. |
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Coffee Science (Online) |
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Precision agriculture to study soil chemical properties and the yield of a coffee fieldAgricultura de precisão no estudo de atributos químicos do solo e da produtividade de lavoura cafeeiraGeostatisticSpatial variabilityKrigingSemivariogramcoffee plantGeoestatísticaVariabilidade espacialKrigagemSemivariogramacafeeiroPrecision agriculture appears as an important tool in the management of coffee farms where the knowledge of some soil fertility characteristics associated with the coffee production could help in specific application of fertilizers with positive environmental and economic results. So the aim of this article was to use precision agriculture and geoestatistics to evaluate the availability of phosphorus, potassium and yield of the coffee plant by evaluating the semivariogram and kriging maps and show that these tools are important for coffee management. This study was conducted on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base we used soil chemical property data obtained by sampling in a georreferenced location using a quadricycle with a sampler and a GPS, and the yield data was obtained from manual harvest on the georreferenced location. The analysis of these data by using statistics and geostatistics tools allowed to characterize the spatial variability of the phosphorus, potassium, and the coffee yield, and allowed to analyze the relation among these variables. It was possible to observe that spatial dependence exists so it is possible to create maps of spatial distribution of the variables.A agricultura de precisão surge como uma importante ferramenta para melhorar o gerenciamento de fazendas cafeeiras. O conhecimento de determinadas características relacionadas à fertilidade do solo, associada à resposta de produção do cafeeiro, podem facilitar a aplicação localizada e racional dos insumos, com resultados ambientais e econômicos positivos. Objetivou-se, com esse trabalho, utilizar ferramentas de agricultura de precisão e de geoestatística para avaliar a disponibilidade de fósforo, potássio e a produtividade do cafeeiro por meio de análises dos semivariogramas e de mapas de isolinhas, obtidos por krigagem, com o intuito de demonstrar que essas ferramentas são de grande valia para o manejo da fertilidade do solo na cultura do café. Este trabalho foi conduzido na fazenda Brejão, no município de Três Pontas, Minas Gerais, utilizando-se os atributos químicos do solo-fósforo e potássio amostrados com o auxílio de um quadriciclo equipado com calador e dados de produtividade obtidos por meio de colheita manual, ambos em pontos georreferenciados. A análise desses dados por meio das técnicas estatísticas e geoestatísticas possibilitaram caracterizar a variabilidade espacial do fósforo, potássio e da produtividade de uma lavoura cafeeira, permitindo-se a análise da relação entre essas variáveis. Foi possível observar que houve dependência espacial o que permitiu a confecção de mapas de distribuição espacial das variáveis.Editora UFLA2012-06-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/204Coffee Science - ISSN 1984-3909; Vol. 7 No. 1 (2012); 59-67Coffee Science; Vol. 7 Núm. 1 (2012); 59-67Coffee Science; v. 7 n. 1 (2012); 59-671984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/204/pdfCopyright (c) 2012 Coffee Science - ISSN 1984-3909https://creativecommons.org/info:eu-repo/semantics/openAccessFerraz, Gabriel Araújo e SilvaSilva, Fábio Moreira daCosta, Pedro Augusto Negrini daSilva, Antônio CarlosCarvalho, Francisval de Melo2013-02-24T13:03:06Zoai:coffeescience.ufla.br:article/204Revistahttps://coffeescience.ufla.br/index.php/CoffeesciencePUBhttps://coffeescience.ufla.br/index.php/Coffeescience/oaicoffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com1984-39091809-6875opendoar:2024-05-21T19:53:34.269550Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
Precision agriculture to study soil chemical properties and the yield of a coffee field Agricultura de precisão no estudo de atributos químicos do solo e da produtividade de lavoura cafeeira |
title |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
spellingShingle |
Precision agriculture to study soil chemical properties and the yield of a coffee field Ferraz, Gabriel Araújo e Silva Geostatistic Spatial variability Kriging Semivariogram coffee plant Geoestatística Variabilidade espacial Krigagem Semivariograma cafeeiro |
title_short |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
title_full |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
title_fullStr |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
title_full_unstemmed |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
title_sort |
Precision agriculture to study soil chemical properties and the yield of a coffee field |
author |
Ferraz, Gabriel Araújo e Silva |
author_facet |
Ferraz, Gabriel Araújo e Silva Silva, Fábio Moreira da Costa, Pedro Augusto Negrini da Silva, Antônio Carlos Carvalho, Francisval de Melo |
author_role |
author |
author2 |
Silva, Fábio Moreira da Costa, Pedro Augusto Negrini da Silva, Antônio Carlos Carvalho, Francisval de Melo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Ferraz, Gabriel Araújo e Silva Silva, Fábio Moreira da Costa, Pedro Augusto Negrini da Silva, Antônio Carlos Carvalho, Francisval de Melo |
dc.subject.por.fl_str_mv |
Geostatistic Spatial variability Kriging Semivariogram coffee plant Geoestatística Variabilidade espacial Krigagem Semivariograma cafeeiro |
topic |
Geostatistic Spatial variability Kriging Semivariogram coffee plant Geoestatística Variabilidade espacial Krigagem Semivariograma cafeeiro |
description |
Precision agriculture appears as an important tool in the management of coffee farms where the knowledge of some soil fertility characteristics associated with the coffee production could help in specific application of fertilizers with positive environmental and economic results. So the aim of this article was to use precision agriculture and geoestatistics to evaluate the availability of phosphorus, potassium and yield of the coffee plant by evaluating the semivariogram and kriging maps and show that these tools are important for coffee management. This study was conducted on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base we used soil chemical property data obtained by sampling in a georreferenced location using a quadricycle with a sampler and a GPS, and the yield data was obtained from manual harvest on the georreferenced location. The analysis of these data by using statistics and geostatistics tools allowed to characterize the spatial variability of the phosphorus, potassium, and the coffee yield, and allowed to analyze the relation among these variables. It was possible to observe that spatial dependence exists so it is possible to create maps of spatial distribution of the variables. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-06-27 |
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://coffeescience.ufla.br/index.php/Coffeescience/article/view/204 |
url |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/204 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/204/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2012 Coffee Science - ISSN 1984-3909 https://creativecommons.org/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2012 Coffee Science - ISSN 1984-3909 https://creativecommons.org/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora UFLA |
publisher.none.fl_str_mv |
Editora UFLA |
dc.source.none.fl_str_mv |
Coffee Science - ISSN 1984-3909; Vol. 7 No. 1 (2012); 59-67 Coffee Science; Vol. 7 Núm. 1 (2012); 59-67 Coffee Science; v. 7 n. 1 (2012); 59-67 1984-3909 reponame:Coffee Science (Online) instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Coffee Science (Online) |
collection |
Coffee Science (Online) |
repository.name.fl_str_mv |
Coffee Science (Online) - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
coffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com |
_version_ |
1799874918901350400 |