Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables

Detalhes bibliográficos
Autor(a) principal: Gabriel, Caroline Cristina Engel
Data de Publicação: 2022
Outros Autores: Uribe Opazo, Miguel Angel, Dalposso, Gustavo Henrique, Cima, Elizabeth Giron
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/25962
Resumo: This paper aimed to analyze the spatial autocorrelation of soybean yield and its bivariate spatial correlation with theagrometeorological variables rainfall, mean temperature, and mean global solar radiation in 2014/2015, 2015/2016, and 2016/2017 crop years in the West of the State of Paraná – Brazil. To achieve this objective, techniques of spatial statistics of areas were used, which, through autocorrelation and spatial correlation indices, sought to identify patterns of association between soybean yield and agrometeorological variables. This research is justified because in addition to the soybean crop being the main source of food protein and vegetable oil in the world and the agrometeorological variables being the factors that most influence it, the western mesoregion of Paraná stands out with the highest production values in the state.  Thus, it is important to monitor its development through spatial analysis to obtain information that will support decision making. The global and local Moran’s indices showed that soybean yield is self-correlated in the municipalities of Western Paraná, identifying clusters to the west and east of the mesoregion. The significance of the bivariate spatial correlation indices confirmed the influence of the variables rainfall, mean temperature, and average global solar radiation on soybean yield.
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spelling Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variablesAnálisis especial del rendimiento de la soja en la mesorregión occidental de Paraná utilizando variable agrometeorológicas Análise espacial da produtividade da soja na mesorregião Oeste do Paraná utilizando variáveis agrometeorológicasAutocorrelación espacialCorrelación espacialAnálisis espacial de datos.Spatial AutocorrelationSpatial CorrelationSpatial data analysis.Autocorrelação EspacialCorrelação EspacialAnálises Espacial de dados.This paper aimed to analyze the spatial autocorrelation of soybean yield and its bivariate spatial correlation with theagrometeorological variables rainfall, mean temperature, and mean global solar radiation in 2014/2015, 2015/2016, and 2016/2017 crop years in the West of the State of Paraná – Brazil. To achieve this objective, techniques of spatial statistics of areas were used, which, through autocorrelation and spatial correlation indices, sought to identify patterns of association between soybean yield and agrometeorological variables. This research is justified because in addition to the soybean crop being the main source of food protein and vegetable oil in the world and the agrometeorological variables being the factors that most influence it, the western mesoregion of Paraná stands out with the highest production values in the state.  Thus, it is important to monitor its development through spatial analysis to obtain information that will support decision making. The global and local Moran’s indices showed that soybean yield is self-correlated in the municipalities of Western Paraná, identifying clusters to the west and east of the mesoregion. The significance of the bivariate spatial correlation indices confirmed the influence of the variables rainfall, mean temperature, and average global solar radiation on soybean yield.Esta investigación tuvo como objetivo analizar la autocorrelación espacial del rendimiento de la soya y su correlación espacial bivariado con las variables agrometeorológicas como lluvia, temperatura media y radiación solar global media en las cosechas 2014/2015, 2015/2016 y 2016/2017 en la mesorregión Oeste de Paraná – Brasil. Para lograr este objetivo, se utilizaron técnicas de estadística espacial de áreas que, por medio de los índices de autocorrelación y la correlación espacial, buscando identificar patrones de asociación entre el rendimiento de la soja y las variables agrometeorológicas. Esta investigación se justifica porque, además de que el cultivo de la soya es la principal fuente de proteína alimentaria y aceite vegetal en el mundo, las variables agrometeorológicas son los factores que más influyen en él. Así, también se destaca la mesorregión occidental de Paraná con los valores más altos de producción en el estado.  Por ello, es importante monitorear su desarrollo mediante el análisis espacial para obtener informaciones que sirvan de apoyo a la toma de decisiones. Los índices de Moran globales y locales mostraron que la productividad de la soya está autocorrelacionada en los municipios del oeste de Paraná, identificando conglomerados al oeste y al este de la mesorregión. La importancia de los índices de correlación espacial bivariados confirmó la influencia de la lluvia, la temperatura media y la radiación solar global media en el rendimiento de la soya.Esta pesquisa teve por objetivo analisar a autocorrelação espacial da produtividade da soja e sua correlação espacial bivariada com as variáveis agrometeorológicas precipitação pluvial, temperatura média e radiação solar global média nos anos-safra 2014/2015, 2015/2016 e 2016/2017 na mesorregião Oeste do Paraná - Brasil. Para atingir este objetivo, utilizou-se de técnicas da estatística espacial de áreas, a qual por meio de índices de autocorrelação e correlação espacial buscaram identificar padrões de associação entre a produtividade da soja e as variáveis agrometeorológicas. Esta pesquisa justifica-se, pois, além da cultura da soja ser a principal fonte de proteína alimentar e óleo vegetal do mundo e as variáveis agrometeorológicas serem os fatores que mais a influenciam, a mesorregião Oeste do Paraná se destaca com os maiores valores de produção no estado. Assim, é importante o acompanhamento do seu desenvolvimento por meio das análises espaciais visando obter informações que venham subsidiar a tomada de decisão. Os índices  de Moran global e local mostraram que a produtividade da soja está autocorrelacionada nos municípios do Oeste do Paraná, identificando-se agrupamentos a oeste e leste da mesorregião. A significância dos índices de correlação espacial bivariada confirmaram a influência das variáveis precipitação pluvial, temperatura média e radiação solar global média na produtividade da soja.Research, Society and Development2022-02-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2596210.33448/rsd-v11i3.25962Research, Society and Development; Vol. 11 No. 3; e7911325962Research, Society and Development; Vol. 11 Núm. 3; e7911325962Research, Society and Development; v. 11 n. 3; e79113259622525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/25962/23011Copyright (c) 2022 Caroline Cristina Engel Gabriel; Miguel Angel Uribe Opazo; Gustavo Henrique Dalposso; Elizabeth Giron Cimahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGabriel, Caroline Cristina EngelUribe Opazo, Miguel Angel Dalposso, Gustavo HenriqueCima, Elizabeth Giron2022-03-09T13:44:38Zoai:ojs.pkp.sfu.ca:article/25962Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:44:07.088086Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
Análisis especial del rendimiento de la soja en la mesorregión occidental de Paraná utilizando variable agrometeorológicas
Análise espacial da produtividade da soja na mesorregião Oeste do Paraná utilizando variáveis agrometeorológicas
title Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
spellingShingle Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
Gabriel, Caroline Cristina Engel
Autocorrelación espacial
Correlación espacial
Análisis espacial de datos.
Spatial Autocorrelation
Spatial Correlation
Spatial data analysis.
Autocorrelação Espacial
Correlação Espacial
Análises Espacial de dados.
title_short Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
title_full Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
title_fullStr Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
title_full_unstemmed Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
title_sort Spatial analysis of soybean yield in the western mesoregion of Paraná using agrometeorological variables
author Gabriel, Caroline Cristina Engel
author_facet Gabriel, Caroline Cristina Engel
Uribe Opazo, Miguel Angel
Dalposso, Gustavo Henrique
Cima, Elizabeth Giron
author_role author
author2 Uribe Opazo, Miguel Angel
Dalposso, Gustavo Henrique
Cima, Elizabeth Giron
author2_role author
author
author
dc.contributor.author.fl_str_mv Gabriel, Caroline Cristina Engel
Uribe Opazo, Miguel Angel
Dalposso, Gustavo Henrique
Cima, Elizabeth Giron
dc.subject.por.fl_str_mv Autocorrelación espacial
Correlación espacial
Análisis espacial de datos.
Spatial Autocorrelation
Spatial Correlation
Spatial data analysis.
Autocorrelação Espacial
Correlação Espacial
Análises Espacial de dados.
topic Autocorrelación espacial
Correlación espacial
Análisis espacial de datos.
Spatial Autocorrelation
Spatial Correlation
Spatial data analysis.
Autocorrelação Espacial
Correlação Espacial
Análises Espacial de dados.
description This paper aimed to analyze the spatial autocorrelation of soybean yield and its bivariate spatial correlation with theagrometeorological variables rainfall, mean temperature, and mean global solar radiation in 2014/2015, 2015/2016, and 2016/2017 crop years in the West of the State of Paraná – Brazil. To achieve this objective, techniques of spatial statistics of areas were used, which, through autocorrelation and spatial correlation indices, sought to identify patterns of association between soybean yield and agrometeorological variables. This research is justified because in addition to the soybean crop being the main source of food protein and vegetable oil in the world and the agrometeorological variables being the factors that most influence it, the western mesoregion of Paraná stands out with the highest production values in the state.  Thus, it is important to monitor its development through spatial analysis to obtain information that will support decision making. The global and local Moran’s indices showed that soybean yield is self-correlated in the municipalities of Western Paraná, identifying clusters to the west and east of the mesoregion. The significance of the bivariate spatial correlation indices confirmed the influence of the variables rainfall, mean temperature, and average global solar radiation on soybean yield.
publishDate 2022
dc.date.none.fl_str_mv 2022-02-13
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://rsdjournal.org/index.php/rsd/article/view/25962
10.33448/rsd-v11i3.25962
url https://rsdjournal.org/index.php/rsd/article/view/25962
identifier_str_mv 10.33448/rsd-v11i3.25962
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/25962/23011
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 11 No. 3; e7911325962
Research, Society and Development; Vol. 11 Núm. 3; e7911325962
Research, Society and Development; v. 11 n. 3; e7911325962
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052792669470720

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