Model to estimate the sampling density for establishment of yield mapping
Autor(a) principal: | |
---|---|
Data de Publicação: | 2012 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662012000400016 |
Resumo: | Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor. |
id |
UFCG-1_e85e38224a08105ab5b8b562ad94b702 |
---|---|
oai_identifier_str |
oai:scielo:S1415-43662012000400016 |
network_acronym_str |
UFCG-1 |
network_name_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository_id_str |
|
spelling |
Model to estimate the sampling density for establishment of yield mappingprecision agriculturethematic mapspatial variabilityYield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor.Departamento de Engenharia Agrícola - UFCG2012-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662012000400016Revista Brasileira de Engenharia Agrícola e Ambiental v.16 n.4 2012reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/S1415-43662012000400016info:eu-repo/semantics/openAccessSpezia,Graciele R.Souza,Eduardo G. deNóbrega,Lúcia H. P.Uribe-Opazo,Miguel A.Milan,MarcosBazzi,Claudio L.eng2012-03-12T00:00:00Zoai:scielo:S1415-43662012000400016Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2012-03-12T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false |
dc.title.none.fl_str_mv |
Model to estimate the sampling density for establishment of yield mapping |
title |
Model to estimate the sampling density for establishment of yield mapping |
spellingShingle |
Model to estimate the sampling density for establishment of yield mapping Spezia,Graciele R. precision agriculture thematic map spatial variability |
title_short |
Model to estimate the sampling density for establishment of yield mapping |
title_full |
Model to estimate the sampling density for establishment of yield mapping |
title_fullStr |
Model to estimate the sampling density for establishment of yield mapping |
title_full_unstemmed |
Model to estimate the sampling density for establishment of yield mapping |
title_sort |
Model to estimate the sampling density for establishment of yield mapping |
author |
Spezia,Graciele R. |
author_facet |
Spezia,Graciele R. Souza,Eduardo G. de Nóbrega,Lúcia H. P. Uribe-Opazo,Miguel A. Milan,Marcos Bazzi,Claudio L. |
author_role |
author |
author2 |
Souza,Eduardo G. de Nóbrega,Lúcia H. P. Uribe-Opazo,Miguel A. Milan,Marcos Bazzi,Claudio L. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Spezia,Graciele R. Souza,Eduardo G. de Nóbrega,Lúcia H. P. Uribe-Opazo,Miguel A. Milan,Marcos Bazzi,Claudio L. |
dc.subject.por.fl_str_mv |
precision agriculture thematic map spatial variability |
topic |
precision agriculture thematic map spatial variability |
description |
Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662012000400016 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662012000400016 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1415-43662012000400016 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
dc.source.none.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental v.16 n.4 2012 reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online) instname:Universidade Federal de Campina Grande (UFCG) instacron:UFCG |
instname_str |
Universidade Federal de Campina Grande (UFCG) |
instacron_str |
UFCG |
institution |
UFCG |
reponame_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
collection |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
_version_ |
1750297681299767296 |