Plant sampling grid determination in precision agriculture in coffee field
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | Coffee Science (Online) |
Texto Completo: | https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391 |
Resumo: | The aim of the present study was to evaluate different grid samples applied to plant properties of a coffee plantation by using precision coffee growing and geostatistical techniques. The study was performed at the Brejão Farm in the municipality of Três Pontas, MG, Brazil, using productivity, the maturation index and the detachment force difference, sampled at georeferenced points. With the intention of choosing an optimum grid, 20 grid samples were tested through semivariogram fitting and validation tests seeking to combine the accuracy and precision that the grid sample can present through an optimal grid indicator, allowing choosing a more suitable grid. It was possible to characterize the magnitude of the spatial variability of plant properties under study in all the proposed grids. The grid that best represented the three variables under study was the grid with 64 sample points in squared grid and nine zoom grid points. The proposed methodology for the present study allowed observing the difference among different grid samples and among the variables of plant productivity, maturity index and detachment force. |
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oai:coffeescience.ufla.br:article/1391 |
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Coffee Science (Online) |
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Plant sampling grid determination in precision agriculture in coffee fieldPrecision agriculturegeostatisticscoffee treespatial variability.The aim of the present study was to evaluate different grid samples applied to plant properties of a coffee plantation by using precision coffee growing and geostatistical techniques. The study was performed at the Brejão Farm in the municipality of Três Pontas, MG, Brazil, using productivity, the maturation index and the detachment force difference, sampled at georeferenced points. With the intention of choosing an optimum grid, 20 grid samples were tested through semivariogram fitting and validation tests seeking to combine the accuracy and precision that the grid sample can present through an optimal grid indicator, allowing choosing a more suitable grid. It was possible to characterize the magnitude of the spatial variability of plant properties under study in all the proposed grids. The grid that best represented the three variables under study was the grid with 64 sample points in squared grid and nine zoom grid points. The proposed methodology for the present study allowed observing the difference among different grid samples and among the variables of plant productivity, maturity index and detachment force.Editora UFLA2018-05-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documenthttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391Coffee Science - ISSN 1984-3909; Vol. 13 No. 1 (2018); 112-121Coffee Science; Vol. 13 Núm. 1 (2018); 112-121Coffee Science; v. 13 n. 1 (2018); 112-1211984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAengporhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391/PDF1391https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391/1849Copyright (c) 2018 Coffee Scienceinfo:eu-repo/semantics/openAccessFerraz, Gabriel Araújo e Silvade Oliveira, Marcelo Silvada Silva, Fábio MoreiraSales, Ronan SouzaCarvalho, Luis Carlos Cirilo2018-05-15T13:34:20Zoai:coffeescience.ufla.br:article/1391Revistahttps://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:2024-05-21T19:54:04.369240Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
Plant sampling grid determination in precision agriculture in coffee field |
title |
Plant sampling grid determination in precision agriculture in coffee field |
spellingShingle |
Plant sampling grid determination in precision agriculture in coffee field Ferraz, Gabriel Araújo e Silva Precision agriculture geostatistics coffee tree spatial variability. |
title_short |
Plant sampling grid determination in precision agriculture in coffee field |
title_full |
Plant sampling grid determination in precision agriculture in coffee field |
title_fullStr |
Plant sampling grid determination in precision agriculture in coffee field |
title_full_unstemmed |
Plant sampling grid determination in precision agriculture in coffee field |
title_sort |
Plant sampling grid determination in precision agriculture in coffee field |
author |
Ferraz, Gabriel Araújo e Silva |
author_facet |
Ferraz, Gabriel Araújo e Silva de Oliveira, Marcelo Silva da Silva, Fábio Moreira Sales, Ronan Souza Carvalho, Luis Carlos Cirilo |
author_role |
author |
author2 |
de Oliveira, Marcelo Silva da Silva, Fábio Moreira Sales, Ronan Souza Carvalho, Luis Carlos Cirilo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Ferraz, Gabriel Araújo e Silva de Oliveira, Marcelo Silva da Silva, Fábio Moreira Sales, Ronan Souza Carvalho, Luis Carlos Cirilo |
dc.subject.por.fl_str_mv |
Precision agriculture geostatistics coffee tree spatial variability. |
topic |
Precision agriculture geostatistics coffee tree spatial variability. |
description |
The aim of the present study was to evaluate different grid samples applied to plant properties of a coffee plantation by using precision coffee growing and geostatistical techniques. The study was performed at the Brejão Farm in the municipality of Três Pontas, MG, Brazil, using productivity, the maturation index and the detachment force difference, sampled at georeferenced points. With the intention of choosing an optimum grid, 20 grid samples were tested through semivariogram fitting and validation tests seeking to combine the accuracy and precision that the grid sample can present through an optimal grid indicator, allowing choosing a more suitable grid. It was possible to characterize the magnitude of the spatial variability of plant properties under study in all the proposed grids. The grid that best represented the three variables under study was the grid with 64 sample points in squared grid and nine zoom grid points. The proposed methodology for the present study allowed observing the difference among different grid samples and among the variables of plant productivity, maturity index and detachment force. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-05-15 |
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/1391 |
url |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391/PDF1391 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1391/1849 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Coffee Science info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Coffee Science |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/vnd.openxmlformats-officedocument.wordprocessingml.document |
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. 13 No. 1 (2018); 112-121 Coffee Science; Vol. 13 Núm. 1 (2018); 112-121 Coffee Science; v. 13 n. 1 (2018); 112-121 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_ |
1799874921129574400 |