Linear and spatial correlation of the yield components and soybean yield

Detalhes bibliográficos
Autor(a) principal: Dalchiavon, Flávio Carlos
Data de Publicação: 2012
Outros Autores: Carvalho, Morel de Passos e
Tipo de documento: Artigo
Idioma: por
Título da fonte: Semina. Ciências Agrárias (Online)
Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/6441
Resumo:  The soybean is the crop most cultivated in Brazil, with great socioeconomic importance. In the agriculture year 2008/09 in Selvíria County, Mato Grosso do Sul State, in the Brazilian Savannah, was analyzed the production components and the soybean yield cultivated in a Typic Acrustox on no-tillage. The main purpose objective was select among the production components number of pods per plant, number of grains per pod, number of grains per plant, mass of a thousand grains, mass of grains per plant and population of plants, which of the best linear and spatial correlation aiming explain the soybean yield variability. The irregular geostatistical grid was installed to collect of data, with 120 sampling points, in an area of 8.34 ha. The values of spatial dependence range to be utilized should be among 38.1 and 114.7 meters. The model of the adjusted semivariograma was predominantly the spherical. Of the lineal and spatial point of view, the number of pods per plant and the mass of grains per plant they were correlated in a direct way with the soybean yield, demonstrating be the best components to esteem her.
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spelling Linear and spatial correlation of the yield components and soybean yieldCorrelação linear e espacial dos componentes de produção e produtividade da sojaPrecision agricultureGeoestatisticsGlycine maxSpatial variability.Agricultura de precisãoGeoestatísticaGlycine MaxVariabilidade espacial. The soybean is the crop most cultivated in Brazil, with great socioeconomic importance. In the agriculture year 2008/09 in Selvíria County, Mato Grosso do Sul State, in the Brazilian Savannah, was analyzed the production components and the soybean yield cultivated in a Typic Acrustox on no-tillage. The main purpose objective was select among the production components number of pods per plant, number of grains per pod, number of grains per plant, mass of a thousand grains, mass of grains per plant and population of plants, which of the best linear and spatial correlation aiming explain the soybean yield variability. The irregular geostatistical grid was installed to collect of data, with 120 sampling points, in an area of 8.34 ha. The values of spatial dependence range to be utilized should be among 38.1 and 114.7 meters. The model of the adjusted semivariograma was predominantly the spherical. Of the lineal and spatial point of view, the number of pods per plant and the mass of grains per plant they were correlated in a direct way with the soybean yield, demonstrating be the best components to esteem her.A soja é a cultura de grãos mais cultivada no Brasil, com enorme importância socioeconômica. No ano agrícola de 2008/09, no município de Selvíria (MS), no Cerrado Brasileiro, foram analisados os componentes de produção e a produtividade da soja cultivada em Latossolo Vermelho distroférrico em sistema plantio direto. O objetivo foi selecionar entre os componentes de produção número de vagens por planta, número de grãos por vagem, número de grãos por planta, massa de mil grãos, massa de grãos por planta e população de plantas, aquele com a melhor correlação, linear e espacial, visando explicar a variabilidade da produtividade da soja. Foi instalada a malha geoestatística irregular, para a coleta de dados, com 120 pontos amostrais, numa área de 8,34 ha. Os valores dos alcances da dependência espacial a serem empregados deverão estar compreendidos entre 38,1 e 114,7 metros. O modelo dos semivariogramas ajustados foi predominantemente o esférico. Do ponto de vista linear e espacial, o número de vagens por planta e a massa de grãos por planta correlacionaram-se de forma direta com a produtividade da soja, demonstrando serem os melhores componentes para estimá-la.UEL2012-05-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/644110.5433/1679-0359.2012v33n2p541Semina: Ciências Agrárias; Vol. 33 No. 2 (2012); 541-552Semina: Ciências Agrárias; v. 33 n. 2 (2012); 541-5521679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELporhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/6441/10471Copyright (c) 2012 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessDalchiavon, Flávio CarlosCarvalho, Morel de Passos e2023-01-27T15:14:39Zoai:ojs.pkp.sfu.ca:article/6441Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2023-01-27T15:14:39Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false
dc.title.none.fl_str_mv Linear and spatial correlation of the yield components and soybean yield
Correlação linear e espacial dos componentes de produção e produtividade da soja
title Linear and spatial correlation of the yield components and soybean yield
spellingShingle Linear and spatial correlation of the yield components and soybean yield
Dalchiavon, Flávio Carlos
Precision agriculture
Geoestatistics
Glycine max
Spatial variability.
Agricultura de precisão
Geoestatística
Glycine Max
Variabilidade espacial.
title_short Linear and spatial correlation of the yield components and soybean yield
title_full Linear and spatial correlation of the yield components and soybean yield
title_fullStr Linear and spatial correlation of the yield components and soybean yield
title_full_unstemmed Linear and spatial correlation of the yield components and soybean yield
title_sort Linear and spatial correlation of the yield components and soybean yield
author Dalchiavon, Flávio Carlos
author_facet Dalchiavon, Flávio Carlos
Carvalho, Morel de Passos e
author_role author
author2 Carvalho, Morel de Passos e
author2_role author
dc.contributor.author.fl_str_mv Dalchiavon, Flávio Carlos
Carvalho, Morel de Passos e
dc.subject.por.fl_str_mv Precision agriculture
Geoestatistics
Glycine max
Spatial variability.
Agricultura de precisão
Geoestatística
Glycine Max
Variabilidade espacial.
topic Precision agriculture
Geoestatistics
Glycine max
Spatial variability.
Agricultura de precisão
Geoestatística
Glycine Max
Variabilidade espacial.
description  The soybean is the crop most cultivated in Brazil, with great socioeconomic importance. In the agriculture year 2008/09 in Selvíria County, Mato Grosso do Sul State, in the Brazilian Savannah, was analyzed the production components and the soybean yield cultivated in a Typic Acrustox on no-tillage. The main purpose objective was select among the production components number of pods per plant, number of grains per pod, number of grains per plant, mass of a thousand grains, mass of grains per plant and population of plants, which of the best linear and spatial correlation aiming explain the soybean yield variability. The irregular geostatistical grid was installed to collect of data, with 120 sampling points, in an area of 8.34 ha. The values of spatial dependence range to be utilized should be among 38.1 and 114.7 meters. The model of the adjusted semivariograma was predominantly the spherical. Of the lineal and spatial point of view, the number of pods per plant and the mass of grains per plant they were correlated in a direct way with the soybean yield, demonstrating be the best components to esteem her.
publishDate 2012
dc.date.none.fl_str_mv 2012-05-15
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://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/6441
10.5433/1679-0359.2012v33n2p541
url https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/6441
identifier_str_mv 10.5433/1679-0359.2012v33n2p541
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/6441/10471
dc.rights.driver.fl_str_mv Copyright (c) 2012 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2012 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UEL
publisher.none.fl_str_mv UEL
dc.source.none.fl_str_mv Semina: Ciências Agrárias; Vol. 33 No. 2 (2012); 541-552
Semina: Ciências Agrárias; v. 33 n. 2 (2012); 541-552
1679-0359
1676-546X
reponame:Semina. Ciências Agrárias (Online)
instname:Universidade Estadual de Londrina (UEL)
instacron:UEL
instname_str Universidade Estadual de Londrina (UEL)
instacron_str UEL
institution UEL
reponame_str Semina. Ciências Agrárias (Online)
collection Semina. Ciências Agrárias (Online)
repository.name.fl_str_mv Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)
repository.mail.fl_str_mv semina.agrarias@uel.br
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