Spatial distribution of the chemical properties of the soil and of soybean yield in the field

Detalhes bibliográficos
Autor(a) principal: Gazolla-Neto,Alexandre
Data de Publicação: 2016
Outros Autores: Fernandes,Marciabela Correa, Vergara,Rafael de Oliveira, Gadotti,Gizele Ingrid, Villela,Francisco Amaral
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902016000200325
Resumo: ABSTRACT The aim of this study was to evaluate the spatial dependence between chemical properties of the soil and yield components in the soybean using precision farming techniques. Samples of the soil and plants were taken from georeferenced points to determine the chemical properties of the soil and the yield components. The results were submitted to Pearson correlation analysis, descriptive statistics and geostatistics. The coefficient of variation showed a wide range of distribution for the chemical attributes of the soil, with the highest indices being found for the levels of available phosphorus (102%) and potassium (72.65%). Soil pH and organic matter showed a coefficient of variation of 5.96 and 15.93% respectively. Semivariogram analysis of the yield components (productivity, 1,000-seed weight and number of seeds) and the chemical properties of the soil (organic matter, pH, phosphorus, potassium, calcium, magnesium, boron, manganese and zinc) fitted the spherical model with moderate spatial dependence, with values ranging from 200 to 700 m. Spatial distribution by means of map interpolation was efficient in evaluating spatial variability, allowing the identification and quantification of regions of low and high productivity in the production area, together with the distribution of soil attributes and their respective levels of availability to the soybean plants.
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spelling Spatial distribution of the chemical properties of the soil and of soybean yield in the fieldPrecision farmingSoil fertilitySpatial distributionSeed yieldABSTRACT The aim of this study was to evaluate the spatial dependence between chemical properties of the soil and yield components in the soybean using precision farming techniques. Samples of the soil and plants were taken from georeferenced points to determine the chemical properties of the soil and the yield components. The results were submitted to Pearson correlation analysis, descriptive statistics and geostatistics. The coefficient of variation showed a wide range of distribution for the chemical attributes of the soil, with the highest indices being found for the levels of available phosphorus (102%) and potassium (72.65%). Soil pH and organic matter showed a coefficient of variation of 5.96 and 15.93% respectively. Semivariogram analysis of the yield components (productivity, 1,000-seed weight and number of seeds) and the chemical properties of the soil (organic matter, pH, phosphorus, potassium, calcium, magnesium, boron, manganese and zinc) fitted the spherical model with moderate spatial dependence, with values ranging from 200 to 700 m. Spatial distribution by means of map interpolation was efficient in evaluating spatial variability, allowing the identification and quantification of regions of low and high productivity in the production area, together with the distribution of soil attributes and their respective levels of availability to the soybean plants.Universidade Federal do Ceará2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902016000200325Revista Ciência Agronômica v.47 n.2 2016reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20160038info:eu-repo/semantics/openAccessGazolla-Neto,AlexandreFernandes,Marciabela CorreaVergara,Rafael de OliveiraGadotti,Gizele IngridVillela,Francisco Amaraleng2016-03-23T00:00:00Zoai:scielo:S1806-66902016000200325Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2016-03-23T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Spatial distribution of the chemical properties of the soil and of soybean yield in the field
title Spatial distribution of the chemical properties of the soil and of soybean yield in the field
spellingShingle Spatial distribution of the chemical properties of the soil and of soybean yield in the field
Gazolla-Neto,Alexandre
Precision farming
Soil fertility
Spatial distribution
Seed yield
title_short Spatial distribution of the chemical properties of the soil and of soybean yield in the field
title_full Spatial distribution of the chemical properties of the soil and of soybean yield in the field
title_fullStr Spatial distribution of the chemical properties of the soil and of soybean yield in the field
title_full_unstemmed Spatial distribution of the chemical properties of the soil and of soybean yield in the field
title_sort Spatial distribution of the chemical properties of the soil and of soybean yield in the field
author Gazolla-Neto,Alexandre
author_facet Gazolla-Neto,Alexandre
Fernandes,Marciabela Correa
Vergara,Rafael de Oliveira
Gadotti,Gizele Ingrid
Villela,Francisco Amaral
author_role author
author2 Fernandes,Marciabela Correa
Vergara,Rafael de Oliveira
Gadotti,Gizele Ingrid
Villela,Francisco Amaral
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Gazolla-Neto,Alexandre
Fernandes,Marciabela Correa
Vergara,Rafael de Oliveira
Gadotti,Gizele Ingrid
Villela,Francisco Amaral
dc.subject.por.fl_str_mv Precision farming
Soil fertility
Spatial distribution
Seed yield
topic Precision farming
Soil fertility
Spatial distribution
Seed yield
description ABSTRACT The aim of this study was to evaluate the spatial dependence between chemical properties of the soil and yield components in the soybean using precision farming techniques. Samples of the soil and plants were taken from georeferenced points to determine the chemical properties of the soil and the yield components. The results were submitted to Pearson correlation analysis, descriptive statistics and geostatistics. The coefficient of variation showed a wide range of distribution for the chemical attributes of the soil, with the highest indices being found for the levels of available phosphorus (102%) and potassium (72.65%). Soil pH and organic matter showed a coefficient of variation of 5.96 and 15.93% respectively. Semivariogram analysis of the yield components (productivity, 1,000-seed weight and number of seeds) and the chemical properties of the soil (organic matter, pH, phosphorus, potassium, calcium, magnesium, boron, manganese and zinc) fitted the spherical model with moderate spatial dependence, with values ranging from 200 to 700 m. Spatial distribution by means of map interpolation was efficient in evaluating spatial variability, allowing the identification and quantification of regions of low and high productivity in the production area, together with the distribution of soil attributes and their respective levels of availability to the soybean plants.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-01
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=S1806-66902016000200325
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902016000200325
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/1806-6690.20160038
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 Universidade Federal do Ceará
publisher.none.fl_str_mv Universidade Federal do Ceará
dc.source.none.fl_str_mv Revista Ciência Agronômica v.47 n.2 2016
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
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