Plant sampling grid determination in precision agriculture in coffee field

Detalhes bibliográficos
Autor(a) principal: Ferraz, Gabriel Araújo e Silva
Data de Publicação: 2018
Outros Autores: de Oliveira, Marcelo Silva, da Silva, Fábio Moreira, Sales, Ronan Souza, Carvalho, Luis Carlos Cirilo
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.
id UFLA-4_00a78f81d92c769787775b1486c2211a
oai_identifier_str oai:coffeescience.ufla.br:article/1391
network_acronym_str UFLA-4
network_name_str Coffee Science (Online)
repository_id_str
spelling 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