Family coffee and good agricultural practices in Bom Sucesso - MG
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Coffee Science (Online) |
Texto Completo: | https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298 |
Resumo: | The objective in this study was to analyze the coffee familiar in the city of Bom Sucesso - MG, in relation to the adoption of Good Agricultural Practices, through the Cluster and discriminant analysis. It was held to recognize the current situation of the coffee familiar of the municipality with questionnaires structured type Survey in rural properties. It used the questionnaire to 26 family farmers associated with the Community Machado Association and the Association Our Lady of Badia. After the questionnaires, the results were tabulated and was performed multivariate statistical analysis of Cluster and later discriminant analysis. The Cluster analysis aims to group individuals (cases) with similar characteristics in terms of a set of selected variables that separated in this case the producers into two distinct groups. Already discriminant analysis showed the seven variables that most discriminate against another group, thus presenting the main differences between them. Group 1 producers have greater organizational characteristics than Group 2 for the adoption of Good Agricultural Practices. However, both the farmers Group 1 as Group 2 feature points that can be improved, which justifies the action planning and Technical Assistance and Rural Extension (ATER) for each group. Thus, it is expected that this study will assist in decision-making both by the local government as the family associations and farmers, so that this activity reach greater sustainability in the municipality. |
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Family coffee and good agricultural practices in Bom Sucesso - MGCafeicultura familiar e as boas práticas agrícolas em Bom Sucesso – MGSustainabilitytechnical assistancecertificationCluster analysisSustentabilidadeassistência técnicaanálise de ClustercertificaçãoThe objective in this study was to analyze the coffee familiar in the city of Bom Sucesso - MG, in relation to the adoption of Good Agricultural Practices, through the Cluster and discriminant analysis. It was held to recognize the current situation of the coffee familiar of the municipality with questionnaires structured type Survey in rural properties. It used the questionnaire to 26 family farmers associated with the Community Machado Association and the Association Our Lady of Badia. After the questionnaires, the results were tabulated and was performed multivariate statistical analysis of Cluster and later discriminant analysis. The Cluster analysis aims to group individuals (cases) with similar characteristics in terms of a set of selected variables that separated in this case the producers into two distinct groups. Already discriminant analysis showed the seven variables that most discriminate against another group, thus presenting the main differences between them. Group 1 producers have greater organizational characteristics than Group 2 for the adoption of Good Agricultural Practices. However, both the farmers Group 1 as Group 2 feature points that can be improved, which justifies the action planning and Technical Assistance and Rural Extension (ATER) for each group. Thus, it is expected that this study will assist in decision-making both by the local government as the family associations and farmers, so that this activity reach greater sustainability in the municipality.Objetivou-se, neste estudo, analisar a cafeicultura familiar do município de Bom Sucesso - MG, em relação à adoção das Boas Práticas Agrícolas, por meio das análises de Cluster e discriminante. Foi realizado o reconhecimento da situação atual da cafeicultura familiar do município, através da aplicação de questionários estruturados do tipo Survey, nas propriedades rurais. Aplicou-se o questionário para um total de 26 cafeicultores familiares associados à Associação Comunitária do Machado e à Associação Nossa Senhora da Badia. Após a aplicação dos questionários, os resultados foram tabulados e foi realizada a análise estatística multivariada de Cluster e, posteriormente a análise discriminante. A análise de Cluster tem como objetivo agrupar os indivíduos (casos) com características semelhantes em função de um conjunto de variáveis selecionadas que separaram, neste caso, os produtores em dois grupos distintos. Já a análise discriminante apresentou as sete variáveis que mais discriminam um grupo do outro, apresentando assim as principais diferenças entre eles. Os produtores do Grupo 1 apresentam características de maior organização diante do Grupo 2, em relação à adoção das Boas Práticas Agrícolas. No entanto, tanto os cafeicultores/propriedades do Grupo 1 quanto do Grupo 2 apresentam pontos que podem ser melhorados, o que justifica o planejamento de ações e políticas de Assistência Técnica e Extensão Rural (ATER), para cada um dos grupos. Dessa forma, espera-se que este estudo auxilie na tomada de decisão tanto por parte do poder público local quanto dos cafeicultores familiares e associações, a fim de que esta atividade alcance maior sustentabilidade no município.Editora UFLA2017-09-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentimage/jpegimage/jpeghttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298Coffee Science - ISSN 1984-3909; Vol. 12 No. 3 (2017); 365 - 373Coffee Science; Vol. 12 Núm. 3 (2017); 365 - 373Coffee Science; v. 12 n. 3 (2017); 365 - 3731984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/pdf_1298https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1761https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1762https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1763https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1764https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1765Copyright (c) 2017 Coffee Scienceinfo:eu-repo/semantics/openAccessPeixoto, Jaqueline Nicole SantosNunes, MárcioBaliza, Danielle PereiraPereira, Sérgio ParreirasRosa, Beatriz Terezinha2017-09-06T14:09:44Zoai:coffeescience.ufla.br:article/1298Revistahttps://coffeescience.ufla.br/index.php/CoffeesciencePUBhttps://coffeescience.ufla.br/index.php/Coffeescience/oaicoffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com1984-39091809-6875opendoar:2024-05-21T19:54:02.068835Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
Family coffee and good agricultural practices in Bom Sucesso - MG Cafeicultura familiar e as boas práticas agrícolas em Bom Sucesso – MG |
title |
Family coffee and good agricultural practices in Bom Sucesso - MG |
spellingShingle |
Family coffee and good agricultural practices in Bom Sucesso - MG Peixoto, Jaqueline Nicole Santos Sustainability technical assistance certification Cluster analysis Sustentabilidade assistência técnica análise de Cluster certificação |
title_short |
Family coffee and good agricultural practices in Bom Sucesso - MG |
title_full |
Family coffee and good agricultural practices in Bom Sucesso - MG |
title_fullStr |
Family coffee and good agricultural practices in Bom Sucesso - MG |
title_full_unstemmed |
Family coffee and good agricultural practices in Bom Sucesso - MG |
title_sort |
Family coffee and good agricultural practices in Bom Sucesso - MG |
author |
Peixoto, Jaqueline Nicole Santos |
author_facet |
Peixoto, Jaqueline Nicole Santos Nunes, Márcio Baliza, Danielle Pereira Pereira, Sérgio Parreiras Rosa, Beatriz Terezinha |
author_role |
author |
author2 |
Nunes, Márcio Baliza, Danielle Pereira Pereira, Sérgio Parreiras Rosa, Beatriz Terezinha |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Peixoto, Jaqueline Nicole Santos Nunes, Márcio Baliza, Danielle Pereira Pereira, Sérgio Parreiras Rosa, Beatriz Terezinha |
dc.subject.por.fl_str_mv |
Sustainability technical assistance certification Cluster analysis Sustentabilidade assistência técnica análise de Cluster certificação |
topic |
Sustainability technical assistance certification Cluster analysis Sustentabilidade assistência técnica análise de Cluster certificação |
description |
The objective in this study was to analyze the coffee familiar in the city of Bom Sucesso - MG, in relation to the adoption of Good Agricultural Practices, through the Cluster and discriminant analysis. It was held to recognize the current situation of the coffee familiar of the municipality with questionnaires structured type Survey in rural properties. It used the questionnaire to 26 family farmers associated with the Community Machado Association and the Association Our Lady of Badia. After the questionnaires, the results were tabulated and was performed multivariate statistical analysis of Cluster and later discriminant analysis. The Cluster analysis aims to group individuals (cases) with similar characteristics in terms of a set of selected variables that separated in this case the producers into two distinct groups. Already discriminant analysis showed the seven variables that most discriminate against another group, thus presenting the main differences between them. Group 1 producers have greater organizational characteristics than Group 2 for the adoption of Good Agricultural Practices. However, both the farmers Group 1 as Group 2 feature points that can be improved, which justifies the action planning and Technical Assistance and Rural Extension (ATER) for each group. Thus, it is expected that this study will assist in decision-making both by the local government as the family associations and farmers, so that this activity reach greater sustainability in the municipality. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09-06 |
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://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298 |
url |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/pdf_1298 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1761 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1762 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1763 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1764 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1298/1765 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Coffee Science info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Coffee Science |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/vnd.openxmlformats-officedocument.wordprocessingml.document application/vnd.openxmlformats-officedocument.wordprocessingml.document application/vnd.openxmlformats-officedocument.wordprocessingml.document image/jpeg image/jpeg |
dc.publisher.none.fl_str_mv |
Editora UFLA |
publisher.none.fl_str_mv |
Editora UFLA |
dc.source.none.fl_str_mv |
Coffee Science - ISSN 1984-3909; Vol. 12 No. 3 (2017); 365 - 373 Coffee Science; Vol. 12 Núm. 3 (2017); 365 - 373 Coffee Science; v. 12 n. 3 (2017); 365 - 373 1984-3909 reponame:Coffee Science (Online) instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Coffee Science (Online) |
collection |
Coffee Science (Online) |
repository.name.fl_str_mv |
Coffee Science (Online) - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
coffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com |
_version_ |
1799874921056174080 |