Exportação concluída — 

Análise espacial da produtividade de café em Minas Gerais (2002-2017)

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Bernardes, Renan Serenini lattes
Orientador(a): Ramos, Patrícia De Siqueira lattes
Banca de defesa: Ferreira, Leandro, Nogueira, Denismar Alves
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Alfenas
Programa de Pós-Graduação: Programa de Pós-Graduação em Estatística Aplicada e Biometria
Departamento: Instituto de Ciências Exatas
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.unifal-mg.edu.br/handle/123456789/1407
Resumo: Brazil is the world’s largest coffee producer. For the last 20 years, has been responsible by approximately one third of world production. In Brazil, the most prominent state is Minas Gerais, which, according to estimates by CONAB - National Supply Company,In 2018 it produced over 53% of all coffee produced in the country. Considering the relevance of coffee and the state of Minas Gerais in the context, this paper aims to analyze thes patial distribution of productivity (measured by the ratio of coffee production over the harvested area) of the coffee in MG from 2002 to 2017 and to verify the evolution of production and productivity over the period. Specifically, the spatial distribution was analyzed through the division of the state in immediategeographicregions,thenewregionaldivisionpublishedbyTheBrazilianInstitueof Geography and Statistics (IBGE), in 2017. To achieve the objective, the series of production, productivity and harvested area were analyzed, verifying the existence of dependence between the regions and clusters of high or low productivity over the years.Spatial dependence was estimated using Moran’s I statistics and cluster indication or space outliers was verified by the local Moran’s I. The results indicated that the coffee productivity in Minas Gerais as a whole has been increasing in recent years. Some regions that had small areas of coffee stopped producing and other regions, which had large areas, but with low productivity levels, increased its productivity,indicating a concentration movement of production. It was identified that the spatial dependence of productivity was more significant in the first period (2002 to 2009) than in second (2010 to 2017). Some high productivity clusters have been identified, showing most significant in the first period. The results of the work can serve as subsidy for new research, implementing variables associated with coffee productivity, as well assupport for policy making in the sector.
id UNIFAL_8f95a58344a12f691be57f2d181d4752
oai_identifier_str oai:repositorio.unifal-mg.edu.br:123456789/1407
network_acronym_str UNIFAL
network_name_str Repositório Institucional da Universidade Federal de Alfenas - RiUnifal
repository_id_str
spelling Bernardes, Renan Sereninihttp://lattes.cnpq.br/7184150832649950Ferreira, LeandroNogueira, Denismar AlvesRamos, Patrícia De Siqueirahttp://lattes.cnpq.br/07853327664380822019-08-27T20:10:16Z2019-06-25BERNARDES, Renan Serenini. Análise espacial da produtividade de café em Minas Gerais (2002-2017). 2019. 67 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.https://repositorio.unifal-mg.edu.br/handle/123456789/1407Brazil is the world’s largest coffee producer. For the last 20 years, has been responsible by approximately one third of world production. In Brazil, the most prominent state is Minas Gerais, which, according to estimates by CONAB - National Supply Company,In 2018 it produced over 53% of all coffee produced in the country. Considering the relevance of coffee and the state of Minas Gerais in the context, this paper aims to analyze thes patial distribution of productivity (measured by the ratio of coffee production over the harvested area) of the coffee in MG from 2002 to 2017 and to verify the evolution of production and productivity over the period. Specifically, the spatial distribution was analyzed through the division of the state in immediategeographicregions,thenewregionaldivisionpublishedbyTheBrazilianInstitueof Geography and Statistics (IBGE), in 2017. To achieve the objective, the series of production, productivity and harvested area were analyzed, verifying the existence of dependence between the regions and clusters of high or low productivity over the years.Spatial dependence was estimated using Moran’s I statistics and cluster indication or space outliers was verified by the local Moran’s I. The results indicated that the coffee productivity in Minas Gerais as a whole has been increasing in recent years. Some regions that had small areas of coffee stopped producing and other regions, which had large areas, but with low productivity levels, increased its productivity,indicating a concentration movement of production. It was identified that the spatial dependence of productivity was more significant in the first period (2002 to 2009) than in second (2010 to 2017). Some high productivity clusters have been identified, showing most significant in the first period. The results of the work can serve as subsidy for new research, implementing variables associated with coffee productivity, as well assupport for policy making in the sector.O Brasil é o maior produtor mundial de café. Nos últimos 20 anos, foi responsável por aproximadamente um terço da produção mundial. No Brasil, o estado de maior destaque é Minas Gerais, que, segundo estimativas da CONAB - Companhia Nacional de Abastecimento, em 2018 produziu mais de 53% de todo o café produzido no país. Considerando a relevância do café e do estado de Minas Gerais no contexto, este trabalho tem como objetivo analisar a distribuição espacial da produtividade (medida pela produção de café sobre a área colhida) do café em MG no período de 2002 a 2017 e verificar a evolução da produção e da produtividade ao longo do período. Especificamente, foi analisada a distribuição espacial através da divisão do estado em regiões geográficas imediatas, nova divisão regional publicada pelo Instituto Brasileiro de Geografia e Estatística (IBGE), em 2017. Para atingir o objetivo foram analisadas as séries de produção, produtividade e área colhida, verificando a existência de dependência espacial entre as regiões e clusters de alta ou baixa produtividade ao longo dos anos analisados. A dependência espacial foi estimada através da estatística I de Moran e a indicação de clusters ou outliers espaciais foi verificada pelo I de Moran local. Os resultados indicaram que a produtividade do café em Minas Gerais como um todo vem aumentando nos últimos anos. Algumas regiões que possuíam pequenas áreas de café deixaram de produzir e outras regiões, que possuíam grandesáreas,mascomníveisdeprodutividadebaixos, aumentaramaprodutividade,indicandoum movimento de concentração da produção. Foi identificado que a dependência espacial da produtividade se mostrou mais expressiva no primeiro período (2002 a 2009) do que no segundo (2010 a 2017). Alguns clusters de alta produtividade foram identificados, mostrando-se mais expressivos no primeiro período. Os resultados do trabalho podem servir como subsídio para novas pesquisas,implementando variáveis associadas à produtividade do café, bem com o apoio à tomada de decisões para políticas do setor.application/pdfporUniversidade Federal de AlfenasPrograma de Pós-Graduação em Estatística Aplicada e BiometriaUNIFAL-MGBrasilInstituto de Ciências Exatasinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Análise espacial (Estatística)Produtividade - CaféEstatística ProdutividadeCIENCIAS AGRARIAS::AGRONOMIAAnálise espacial da produtividade de café em Minas Gerais (2002-2017)info:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/publishedVersion-8156311678363143599600600-3091138714907603907reponame:Repositório Institucional da Universidade Federal de Alfenas - RiUnifalinstname:Universidade Federal de Alfenas (UNIFAL)instacron:UNIFALBernardes, Renan SereniniLICENSElicense.txtlicense.txttext/plain; charset=utf-81987https://repositorio.unifal-mg.edu.br/bitstreams/41d63060-94be-4551-b4e4-76ad38ffe9f0/download31555718c4fc75849dd08f27935d4f6bMD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849https://repositorio.unifal-mg.edu.br/bitstreams/ef1d3d23-f3c4-49c4-bd1e-6368ce6251ab/download4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-80https://repositorio.unifal-mg.edu.br/bitstreams/744100a6-3ec4-4d6f-85be-796086cb2ed7/downloadd41d8cd98f00b204e9800998ecf8427eMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-80https://repositorio.unifal-mg.edu.br/bitstreams/b280db4c-2467-4ce4-94af-37cd6089f6ac/downloadd41d8cd98f00b204e9800998ecf8427eMD54ORIGINALDissertação de Renan Serenini Bernardes.pdfDissertação de Renan Serenini Bernardes.pdfapplication/pdf4225689https://repositorio.unifal-mg.edu.br/bitstreams/baa471c4-3da6-4cf9-8038-3e6dcdf8d7b2/downloadbdbdd19789b42dc872d30c2b58eff48eMD55TEXTDissertação de Renan Serenini Bernardes.pdf.txtDissertação de Renan Serenini Bernardes.pdf.txtExtracted texttext/plain92748https://repositorio.unifal-mg.edu.br/bitstreams/69612c1e-f0e8-4ff7-9c3f-1cab64e014ad/download5ce6ef9f18237bc6d0f8a66581a5044cMD510THUMBNAILDissertação de Renan Serenini Bernardes.pdf.jpgDissertação de Renan Serenini Bernardes.pdf.jpgGenerated Thumbnailimage/jpeg2395https://repositorio.unifal-mg.edu.br/bitstreams/3f2c1d18-2c70-4fca-a930-f4e2982f1dfc/download5bbc6205d3a9c80ab3bbfc3cb28317cbMD59123456789/14072026-01-07 14:34:36.421http://creativecommons.org/licenses/by-nc-nd/4.0/open.accessoai:repositorio.unifal-mg.edu.br:123456789/1407https://repositorio.unifal-mg.edu.brRepositório InstitucionalPUBhttps://bdtd.unifal-mg.edu.br:8443/oai/requestrepositorio@unifal-mg.edu.bropendoar:2026-01-07T17:34:36Repositório Institucional da Universidade Federal de Alfenas - RiUnifal - Universidade Federal de Alfenas (UNIFAL)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
dc.title.pt-BR.fl_str_mv Análise espacial da produtividade de café em Minas Gerais (2002-2017)
title Análise espacial da produtividade de café em Minas Gerais (2002-2017)
spellingShingle Análise espacial da produtividade de café em Minas Gerais (2002-2017)
Bernardes, Renan Serenini
Análise espacial (Estatística)
Produtividade - Café
Estatística Produtividade
CIENCIAS AGRARIAS::AGRONOMIA
title_short Análise espacial da produtividade de café em Minas Gerais (2002-2017)
title_full Análise espacial da produtividade de café em Minas Gerais (2002-2017)
title_fullStr Análise espacial da produtividade de café em Minas Gerais (2002-2017)
title_full_unstemmed Análise espacial da produtividade de café em Minas Gerais (2002-2017)
title_sort Análise espacial da produtividade de café em Minas Gerais (2002-2017)
author Bernardes, Renan Serenini
author_facet Bernardes, Renan Serenini
author_role author
dc.contributor.author.fl_str_mv Bernardes, Renan Serenini
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/7184150832649950
dc.contributor.referee1.fl_str_mv Ferreira, Leandro
dc.contributor.referee2.fl_str_mv Nogueira, Denismar Alves
dc.contributor.advisor1.fl_str_mv Ramos, Patrícia De Siqueira
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/0785332766438082
contributor_str_mv Ferreira, Leandro
Nogueira, Denismar Alves
Ramos, Patrícia De Siqueira
dc.subject.por.fl_str_mv Análise espacial (Estatística)
Produtividade - Café
Estatística Produtividade
topic Análise espacial (Estatística)
Produtividade - Café
Estatística Produtividade
CIENCIAS AGRARIAS::AGRONOMIA
dc.subject.cnpq.fl_str_mv CIENCIAS AGRARIAS::AGRONOMIA
description Brazil is the world’s largest coffee producer. For the last 20 years, has been responsible by approximately one third of world production. In Brazil, the most prominent state is Minas Gerais, which, according to estimates by CONAB - National Supply Company,In 2018 it produced over 53% of all coffee produced in the country. Considering the relevance of coffee and the state of Minas Gerais in the context, this paper aims to analyze thes patial distribution of productivity (measured by the ratio of coffee production over the harvested area) of the coffee in MG from 2002 to 2017 and to verify the evolution of production and productivity over the period. Specifically, the spatial distribution was analyzed through the division of the state in immediategeographicregions,thenewregionaldivisionpublishedbyTheBrazilianInstitueof Geography and Statistics (IBGE), in 2017. To achieve the objective, the series of production, productivity and harvested area were analyzed, verifying the existence of dependence between the regions and clusters of high or low productivity over the years.Spatial dependence was estimated using Moran’s I statistics and cluster indication or space outliers was verified by the local Moran’s I. The results indicated that the coffee productivity in Minas Gerais as a whole has been increasing in recent years. Some regions that had small areas of coffee stopped producing and other regions, which had large areas, but with low productivity levels, increased its productivity,indicating a concentration movement of production. It was identified that the spatial dependence of productivity was more significant in the first period (2002 to 2009) than in second (2010 to 2017). Some high productivity clusters have been identified, showing most significant in the first period. The results of the work can serve as subsidy for new research, implementing variables associated with coffee productivity, as well assupport for policy making in the sector.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-08-27T20:10:16Z
dc.date.issued.fl_str_mv 2019-06-25
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv BERNARDES, Renan Serenini. Análise espacial da produtividade de café em Minas Gerais (2002-2017). 2019. 67 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.
dc.identifier.uri.fl_str_mv https://repositorio.unifal-mg.edu.br/handle/123456789/1407
identifier_str_mv BERNARDES, Renan Serenini. Análise espacial da produtividade de café em Minas Gerais (2002-2017). 2019. 67 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.
url https://repositorio.unifal-mg.edu.br/handle/123456789/1407
dc.language.iso.fl_str_mv por
language por
dc.relation.department.fl_str_mv -8156311678363143599
dc.relation.confidence.fl_str_mv 600
600
dc.relation.cnpq.fl_str_mv -3091138714907603907
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Alfenas
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Estatística Aplicada e Biometria
dc.publisher.initials.fl_str_mv UNIFAL-MG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Instituto de Ciências Exatas
publisher.none.fl_str_mv Universidade Federal de Alfenas
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal de Alfenas - RiUnifal
instname:Universidade Federal de Alfenas (UNIFAL)
instacron:UNIFAL
instname_str Universidade Federal de Alfenas (UNIFAL)
instacron_str UNIFAL
institution UNIFAL
reponame_str Repositório Institucional da Universidade Federal de Alfenas - RiUnifal
collection Repositório Institucional da Universidade Federal de Alfenas - RiUnifal
bitstream.url.fl_str_mv https://repositorio.unifal-mg.edu.br/bitstreams/41d63060-94be-4551-b4e4-76ad38ffe9f0/download
https://repositorio.unifal-mg.edu.br/bitstreams/ef1d3d23-f3c4-49c4-bd1e-6368ce6251ab/download
https://repositorio.unifal-mg.edu.br/bitstreams/744100a6-3ec4-4d6f-85be-796086cb2ed7/download
https://repositorio.unifal-mg.edu.br/bitstreams/b280db4c-2467-4ce4-94af-37cd6089f6ac/download
https://repositorio.unifal-mg.edu.br/bitstreams/baa471c4-3da6-4cf9-8038-3e6dcdf8d7b2/download
https://repositorio.unifal-mg.edu.br/bitstreams/69612c1e-f0e8-4ff7-9c3f-1cab64e014ad/download
https://repositorio.unifal-mg.edu.br/bitstreams/3f2c1d18-2c70-4fca-a930-f4e2982f1dfc/download
bitstream.checksum.fl_str_mv 31555718c4fc75849dd08f27935d4f6b
4afdbb8c545fd630ea7db775da747b2f
d41d8cd98f00b204e9800998ecf8427e
d41d8cd98f00b204e9800998ecf8427e
bdbdd19789b42dc872d30c2b58eff48e
5ce6ef9f18237bc6d0f8a66581a5044c
5bbc6205d3a9c80ab3bbfc3cb28317cb
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositório Institucional da Universidade Federal de Alfenas - RiUnifal - Universidade Federal de Alfenas (UNIFAL)
repository.mail.fl_str_mv repositorio@unifal-mg.edu.br
_version_ 1859830885641093120