Comparison between the soil chemical atributes sampled conventionaly and in grid

Detalhes bibliográficos
Autor(a) principal: Ferraz, Gabriel Araújo e Silva
Data de Publicação: 2017
Outros Autores: Silva, Fábio Moreira da, Oliveira, Marcelo Silva de, Silva, Flávio Castro da, Carvalho, Luis Carlos Cirilo
Tipo de documento: Artigo
Idioma: por
Título da fonte: Coffee Science (Online)
Texto Completo: https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188
Resumo: The aim in this article was to characterize the structure and magnitude of the spatial distribution of soil attributes on a coffee field and map these attributes in order to identify the spatial dependence of them. It was aimed to compare the attribute amount when it was sampled conventionally or in grid sampling. This study was carried out on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base were used pH, P, Prem, K, Ca, Mg, Al, H + Al, m, T, t, SB, V e MO sampled conventionally or sampled in a 64 point squared grid georeferenced with 36 points from grid zoom as well. The analysis of these data by geostatistics tools allowed characterize the spatial variability which allowed creating maps of spatial distribution of the variables. It was possible to identify differences presented in the amount of soil attributes sampled conventionally and in georreferenced grid sampling in precision coffee culture.
id UFLA-4_6aa90c9ee8f5e9699886375279368a20
oai_identifier_str oai:coffeescience.ufla.br:article/1188
network_acronym_str UFLA-4
network_name_str Coffee Science (Online)
repository_id_str
spelling Comparison between the soil chemical atributes sampled conventionaly and in gridComparativo entre os atributos químicos do solo amostrados de forma convencional e em malhaPrecision Agriculturegeostatisticsmanagementcoffee plantAgricultura de PrecisãogeoestatísticagerenciamentocafeeiroThe aim in this article was to characterize the structure and magnitude of the spatial distribution of soil attributes on a coffee field and map these attributes in order to identify the spatial dependence of them. It was aimed to compare the attribute amount when it was sampled conventionally or in grid sampling. This study was carried out on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base were used pH, P, Prem, K, Ca, Mg, Al, H + Al, m, T, t, SB, V e MO sampled conventionally or sampled in a 64 point squared grid georeferenced with 36 points from grid zoom as well. The analysis of these data by geostatistics tools allowed characterize the spatial variability which allowed creating maps of spatial distribution of the variables. It was possible to identify differences presented in the amount of soil attributes sampled conventionally and in georreferenced grid sampling in precision coffee culture.O objetivo do presente trabalho foi caracterizar a estrutura e a magnitude da distribuição espacial de atributos do solo de uma lavoura cafeeira, realizando o mapeamento destes atributos para visualizar a distribuição espacial. Objetivou-se ainda comparar os teores apresentados pelos atributos do solo na amostragem convencional e amostragem em grade. Este trabalho foi conduzido na fazenda Brejão no município de Três Pontas, Minas Gerais, utilizando-se os atributos do solo: pH, P, Prem, K, Ca, Mg, Al, H + Al, m, T, t, SB, V e MO amostrados de forma convencional e em grade amostral quadrada de 64 pontos georreferenciados acrescida de 36 pontos de grade zoom. A análise destes dados por meio das técnicas geoestatísticas possibilitou caracterizar a variabilidade espacial dos atributos do solo em estudo, permitindo o mapeamento destas variáveis. Foi possível identificar as diferenças apresentadas nos teores dos atributos do solo comparativamente para a amostragem convencional e em grade georreferenciada para aplicação na cafeicultura de precisão.Editora UFLA2017-03-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188Coffee Science - ISSN 1984-3909; Vol. 12 No. 1 (2017); 17 - 29Coffee Science; Vol. 12 Núm. 1 (2017); 17 - 29Coffee Science; v. 12 n. 1 (2017); 17 - 291984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188/pdf_1188https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188/1662Copyright (c) 2017 Coffee Science - ISSN 1984-3909https://creativecommons.org/info:eu-repo/semantics/openAccessFerraz, Gabriel Araújo e SilvaSilva, Fábio Moreira daOliveira, Marcelo Silva deSilva, Flávio Castro daCarvalho, Luis Carlos Cirilo2017-03-30T16:15:17Zoai:coffeescience.ufla.br:article/1188Revistahttps://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:2024-05-21T19:53:59.059639Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Comparison between the soil chemical atributes sampled conventionaly and in grid
Comparativo entre os atributos químicos do solo amostrados de forma convencional e em malha
title Comparison between the soil chemical atributes sampled conventionaly and in grid
spellingShingle Comparison between the soil chemical atributes sampled conventionaly and in grid
Ferraz, Gabriel Araújo e Silva
Precision Agriculture
geostatistics
management
coffee plant
Agricultura de Precisão
geoestatística
gerenciamento
cafeeiro
title_short Comparison between the soil chemical atributes sampled conventionaly and in grid
title_full Comparison between the soil chemical atributes sampled conventionaly and in grid
title_fullStr Comparison between the soil chemical atributes sampled conventionaly and in grid
title_full_unstemmed Comparison between the soil chemical atributes sampled conventionaly and in grid
title_sort Comparison between the soil chemical atributes sampled conventionaly and in grid
author Ferraz, Gabriel Araújo e Silva
author_facet Ferraz, Gabriel Araújo e Silva
Silva, Fábio Moreira da
Oliveira, Marcelo Silva de
Silva, Flávio Castro da
Carvalho, Luis Carlos Cirilo
author_role author
author2 Silva, Fábio Moreira da
Oliveira, Marcelo Silva de
Silva, Flávio Castro da
Carvalho, Luis Carlos Cirilo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Ferraz, Gabriel Araújo e Silva
Silva, Fábio Moreira da
Oliveira, Marcelo Silva de
Silva, Flávio Castro da
Carvalho, Luis Carlos Cirilo
dc.subject.por.fl_str_mv Precision Agriculture
geostatistics
management
coffee plant
Agricultura de Precisão
geoestatística
gerenciamento
cafeeiro
topic Precision Agriculture
geostatistics
management
coffee plant
Agricultura de Precisão
geoestatística
gerenciamento
cafeeiro
description The aim in this article was to characterize the structure and magnitude of the spatial distribution of soil attributes on a coffee field and map these attributes in order to identify the spatial dependence of them. It was aimed to compare the attribute amount when it was sampled conventionally or in grid sampling. This study was carried out on the Brejão farm in Três Pontas, Minas Gerais state, Brazil. As a data base were used pH, P, Prem, K, Ca, Mg, Al, H + Al, m, T, t, SB, V e MO sampled conventionally or sampled in a 64 point squared grid georeferenced with 36 points from grid zoom as well. The analysis of these data by geostatistics tools allowed characterize the spatial variability which allowed creating maps of spatial distribution of the variables. It was possible to identify differences presented in the amount of soil attributes sampled conventionally and in georreferenced grid sampling in precision coffee culture.
publishDate 2017
dc.date.none.fl_str_mv 2017-03-30
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/1188
url https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188/pdf_1188
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1188/1662
dc.rights.driver.fl_str_mv Copyright (c) 2017 Coffee Science - ISSN 1984-3909
https://creativecommons.org/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Coffee Science - ISSN 1984-3909
https://creativecommons.org/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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. 12 No. 1 (2017); 17 - 29
Coffee Science; Vol. 12 Núm. 1 (2017); 17 - 29
Coffee Science; v. 12 n. 1 (2017); 17 - 29
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_ 1799874920972288000

Registros relacionados