Análise espacial da produtividade de café em Minas Gerais (2002-2017)
| Ano de defesa: | 2019 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | , |
| 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. |
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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; 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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. |
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2019 |
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2019-08-27T20:10:16Z |
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2019-06-25 |
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info:eu-repo/semantics/masterThesis |
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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. |
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https://repositorio.unifal-mg.edu.br/handle/123456789/1407 |
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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. |
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