Fatores determinantes da modernização agrícola na região sul do Brasil
Ano de defesa: | 2021 |
---|---|
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 Santa Maria
UFSM Palmeira das Missões |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Agronegócios
|
Departamento: |
Agronomia
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/21164 |
Resumo: | Over the years, Brazilian agricultural production has grown and stood out nationally and internationally due to technological advances and global demand for food. Brazilian agribusiness is one of the main players and agro-industrial producers in the world, besides it is one of the largest exporters of soy, orange, beef, pork and poultry. Its production and exports generate jobs, income and development apart from representing a large share of the Gross Domestic Product - GDP, generating balance in the Brazilian trade balance. Factors such as climate, relief, soil, rainfall, labor, technology employed and promoting public policies for production make Brazil one of the main food producers in the world. In order to identify the conditioning factors of agricultural modernization in the municipalities of the States of Rio Grande do Sul, Santa Catarina and Paraná, the factor analysis technique was used to calculate the Agricultural Modernization Index (AMI) so as to hierarchize the municipalities of the three States of the southern region of Brazil in terms of agricultural modernization. Then, Exploratory Spatial Data Analysis (ESDA) was applied to analyze how spatial distribution occurs in relation to the intensity of the modernization of agriculture in the three States of the southern region. The main contribution of the study focuses on answering whether there has been agricultural modernization in the southern Brazilian region over the years and, more specifically, in the last agricultural census in 2006 and 2017. This investigation is supported by previous studies on this theme and covers the entire southern region of the country, given its economic, productive and agricultural potential. Main results obtained show that the municipalities that obtained a high index of agricultural modernization are located in the northwestern and eastern center mesoregions of Rio Grande do Sul, in the Vale do Itajaí and west of Santa Catarina and west, central north and metropolitan mesoregions of Paraná. These regions concentrate several of the main agricultural producers of soy, corn, rice, wheat, cultivation of vines and horticultural, orchard and farm products besides allocating large cities with industrial development for agribusiness. Thus, through the Exploratory Spatial Data Analysis (ESDA), it was possible to corroborate the hypothesis that the spatial distribution of the modernization of agriculture is not random due to the positive correlation of the AMI. In this sense, through the analysis of LISA cluster maps, two different types of well-defined clusters were identified for 2006 and 2017. The first well-defined was of the high-high type (HH) and the second of the low-low type (LL). Finally, it can be said that in a certain way, there is a relativity in the Agricultural Modernization Index, because there is a contrast between the most developed regions in relation to the least developed ones, so generalizing that the municipalities are really technologically developed is imprecise. |
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2021-06-21T17:27:00Z2021-06-21T17:27:00Z2021-02-10http://repositorio.ufsm.br/handle/1/21164Over the years, Brazilian agricultural production has grown and stood out nationally and internationally due to technological advances and global demand for food. Brazilian agribusiness is one of the main players and agro-industrial producers in the world, besides it is one of the largest exporters of soy, orange, beef, pork and poultry. Its production and exports generate jobs, income and development apart from representing a large share of the Gross Domestic Product - GDP, generating balance in the Brazilian trade balance. Factors such as climate, relief, soil, rainfall, labor, technology employed and promoting public policies for production make Brazil one of the main food producers in the world. In order to identify the conditioning factors of agricultural modernization in the municipalities of the States of Rio Grande do Sul, Santa Catarina and Paraná, the factor analysis technique was used to calculate the Agricultural Modernization Index (AMI) so as to hierarchize the municipalities of the three States of the southern region of Brazil in terms of agricultural modernization. Then, Exploratory Spatial Data Analysis (ESDA) was applied to analyze how spatial distribution occurs in relation to the intensity of the modernization of agriculture in the three States of the southern region. The main contribution of the study focuses on answering whether there has been agricultural modernization in the southern Brazilian region over the years and, more specifically, in the last agricultural census in 2006 and 2017. This investigation is supported by previous studies on this theme and covers the entire southern region of the country, given its economic, productive and agricultural potential. Main results obtained show that the municipalities that obtained a high index of agricultural modernization are located in the northwestern and eastern center mesoregions of Rio Grande do Sul, in the Vale do Itajaí and west of Santa Catarina and west, central north and metropolitan mesoregions of Paraná. These regions concentrate several of the main agricultural producers of soy, corn, rice, wheat, cultivation of vines and horticultural, orchard and farm products besides allocating large cities with industrial development for agribusiness. Thus, through the Exploratory Spatial Data Analysis (ESDA), it was possible to corroborate the hypothesis that the spatial distribution of the modernization of agriculture is not random due to the positive correlation of the AMI. In this sense, through the analysis of LISA cluster maps, two different types of well-defined clusters were identified for 2006 and 2017. The first well-defined was of the high-high type (HH) and the second of the low-low type (LL). Finally, it can be said that in a certain way, there is a relativity in the Agricultural Modernization Index, because there is a contrast between the most developed regions in relation to the least developed ones, so generalizing that the municipalities are really technologically developed is imprecise.No decorrer dos anos, a produção agrícola brasileira vem crescendo e se destacando, tanto nacional quanto internacionalmente, devido aos avanços tecnológicos e à demanda global por alimentos. O agronegócio brasileiro encontrase entre os principais players e produtores agroindustriais mundiais, sendo um dos maiores exportadores de soja, laranja, carnes bovina, suína e de aves. Sua produção e exportações geram empregos, renda, divisas, desenvolvimento e representam uma grande fatia do Produto Interno Bruto (PIB), garantindo equilíbrio na balança comercial brasileira. Fatores como clima, relevo, solo, índices pluviométricos, mão de obra, tecnologia empregada, além de políticas públicas de fomento à produção, tornam o Brasil um dos principais produtores de alimentos do mundo. A fim de identificar os fatores condicionantes da modernização agrícola nos municípios dos estados do Rio Grande do Sul, Santa Catarina e Paraná, utilizou-se a técnica de análise fatorial para realizar o cálculo do Índice de Modernização Agrícola (IMA), com o intuito de hierarquizar os municípios dos três estados da Região Sul do Brasil em termos de modernização agrícola. Após, foi aplicada a Análise Exploratória de Dados Espaciais (AEDE), visando analisar como ocorre a distribuição espacial em relação à intensidade da modernização da agricultura nos três estados. A principal contribuição do estudo concentra-se em responder se houve modernização agrícola na Região Sul brasileira no decorrer dos anos e, mais especificamente, entre os Censos Agropecuários, de 2006 e 2017, amparando-se em estudos anteriores dessa temática e abrangendo toda a Região Sul do país, haja vista seu potencial econômico, produtivo e agropecuário. Os principais resultados obtidos apontam que os municípios que obtiveram elevado IMA estão localizados nas mesorregiões Noroeste e Centro Oriental gaúcha, Vale do Itajaí e Oeste Catarinense, e Oeste, Norte Central e Metropolitana Paranaense. Essas regiões concentram vários dos principais municípios produtores agrícolas de soja, milho, arroz, trigo, cultivo de videiras e hortifrutigranjeiros e, ainda, abrigam grandes cidades com desenvolvimento industrial voltado ao agronegócio. Desse modo, por meio da AEDE, foi possível confirmar a hipótese de que a distribuição espacial da modernização da agricultura é não aleatória, em virtude da correlação positiva do IMA. Nesse sentido, através da análise dos mapas de clusters LISA, identificaram-se dois tipos diferentes de clusters bem definidos, tanto para 2006 quanto para 2017. O primeiro bem definido foi do tipo alto-alto (AA), e o segundo, do tipo baixo-baixo (BB). Por fim, pode-se afirmar que, de certa forma, existe uma relatividade no IMA, havendo um contraste das regiões mais desenvolvidas com as menos desenvolvidas, sendo imprecisa a generalização de que os municípios sejam mesmo tecnologicamente desenvolvidos.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaUFSM Palmeira das MissõesPrograma de Pós-Graduação em AgronegóciosUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAgronegócioAgriculturaEstabelecimentos agropecuáriosCrescimentoMesorregiõesAgribusinessAgricultureAgricultural facilitiesGrowthMesoregionsCNPQ::CIENCIAS AGRARIAS::AGRONOMIAFatores determinantes da modernização agrícola na região sul do BrasilDecisive factors of agricultural modernization in southern Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisCoronel, Daniel Arrudahttp://lattes.cnpq.br/9265604274170933Pinto, Nelson Guilherme MachadoBender Filho, ReisoliSousa, Eliane Pinheiro dehttp://lattes.cnpq.br/6846218978446942Galle, Vitor500100000009600600600600600600c5f7e145-5c80-4b8f-b8ac-11b9902356578169bc0a-2db7-4d30-9b38-99bd30828d9088c36c9a-f702-4b6a-8b37-9569cb81d311aba31154-6717-477d-af99-6e82af79f363e19e88b5-7b18-46ec-b6f5-bf4aac84cea8reponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGAGRONEGOCIOS_2021_GALLE_VITOR.pdfDIS_PPGAGRONEGOCIOS_2021_GALLE_VITOR.pdfDissertaçãoapplication/pdf2305080http://repositorio.ufsm.br/bitstream/1/21164/1/DIS_PPGAGRONEGOCIOS_2021_GALLE_VITOR.pdfb7e7c25f5735ef4e15422c0173f0220aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv |
Fatores determinantes da modernização agrícola na região sul do Brasil |
dc.title.alternative.eng.fl_str_mv |
Decisive factors of agricultural modernization in southern Brazil |
title |
Fatores determinantes da modernização agrícola na região sul do Brasil |
spellingShingle |
Fatores determinantes da modernização agrícola na região sul do Brasil Galle, Vitor Agronegócio Agricultura Estabelecimentos agropecuários Crescimento Mesorregiões Agribusiness Agriculture Agricultural facilities Growth Mesoregions CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Fatores determinantes da modernização agrícola na região sul do Brasil |
title_full |
Fatores determinantes da modernização agrícola na região sul do Brasil |
title_fullStr |
Fatores determinantes da modernização agrícola na região sul do Brasil |
title_full_unstemmed |
Fatores determinantes da modernização agrícola na região sul do Brasil |
title_sort |
Fatores determinantes da modernização agrícola na região sul do Brasil |
author |
Galle, Vitor |
author_facet |
Galle, Vitor |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Coronel, Daniel Arruda |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9265604274170933 |
dc.contributor.advisor-co1.fl_str_mv |
Pinto, Nelson Guilherme Machado |
dc.contributor.referee1.fl_str_mv |
Bender Filho, Reisoli |
dc.contributor.referee2.fl_str_mv |
Sousa, Eliane Pinheiro de |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6846218978446942 |
dc.contributor.author.fl_str_mv |
Galle, Vitor |
contributor_str_mv |
Coronel, Daniel Arruda Pinto, Nelson Guilherme Machado Bender Filho, Reisoli Sousa, Eliane Pinheiro de |
dc.subject.por.fl_str_mv |
Agronegócio Agricultura Estabelecimentos agropecuários Crescimento Mesorregiões |
topic |
Agronegócio Agricultura Estabelecimentos agropecuários Crescimento Mesorregiões Agribusiness Agriculture Agricultural facilities Growth Mesoregions CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Agribusiness Agriculture Agricultural facilities Growth Mesoregions |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
Over the years, Brazilian agricultural production has grown and stood out nationally and internationally due to technological advances and global demand for food. Brazilian agribusiness is one of the main players and agro-industrial producers in the world, besides it is one of the largest exporters of soy, orange, beef, pork and poultry. Its production and exports generate jobs, income and development apart from representing a large share of the Gross Domestic Product - GDP, generating balance in the Brazilian trade balance. Factors such as climate, relief, soil, rainfall, labor, technology employed and promoting public policies for production make Brazil one of the main food producers in the world. In order to identify the conditioning factors of agricultural modernization in the municipalities of the States of Rio Grande do Sul, Santa Catarina and Paraná, the factor analysis technique was used to calculate the Agricultural Modernization Index (AMI) so as to hierarchize the municipalities of the three States of the southern region of Brazil in terms of agricultural modernization. Then, Exploratory Spatial Data Analysis (ESDA) was applied to analyze how spatial distribution occurs in relation to the intensity of the modernization of agriculture in the three States of the southern region. The main contribution of the study focuses on answering whether there has been agricultural modernization in the southern Brazilian region over the years and, more specifically, in the last agricultural census in 2006 and 2017. This investigation is supported by previous studies on this theme and covers the entire southern region of the country, given its economic, productive and agricultural potential. Main results obtained show that the municipalities that obtained a high index of agricultural modernization are located in the northwestern and eastern center mesoregions of Rio Grande do Sul, in the Vale do Itajaí and west of Santa Catarina and west, central north and metropolitan mesoregions of Paraná. These regions concentrate several of the main agricultural producers of soy, corn, rice, wheat, cultivation of vines and horticultural, orchard and farm products besides allocating large cities with industrial development for agribusiness. Thus, through the Exploratory Spatial Data Analysis (ESDA), it was possible to corroborate the hypothesis that the spatial distribution of the modernization of agriculture is not random due to the positive correlation of the AMI. In this sense, through the analysis of LISA cluster maps, two different types of well-defined clusters were identified for 2006 and 2017. The first well-defined was of the high-high type (HH) and the second of the low-low type (LL). Finally, it can be said that in a certain way, there is a relativity in the Agricultural Modernization Index, because there is a contrast between the most developed regions in relation to the least developed ones, so generalizing that the municipalities are really technologically developed is imprecise. |
publishDate |
2021 |
dc.date.accessioned.fl_str_mv |
2021-06-21T17:27:00Z |
dc.date.available.fl_str_mv |
2021-06-21T17:27:00Z |
dc.date.issued.fl_str_mv |
2021-02-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/21164 |
url |
http://repositorio.ufsm.br/handle/1/21164 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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500100000009 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 600 600 |
dc.relation.authority.fl_str_mv |
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dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria UFSM Palmeira das Missões |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Agronegócios |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria UFSM Palmeira das Missões |
dc.source.none.fl_str_mv |
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institution |
UFSM |
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Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
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