Good agricultural practices in an association of familiar coffee producers by means of clusters analysis

Detalhes bibliográficos
Autor(a) principal: Rosa, Beatriz Terezinha
Data de Publicação: 2017
Outros Autores: Borges, Luís Antônio Coimbra, Pereira, Sérgio Parreiras, Antonialli, Luíz Marcelo, Souza, Sára Maria Chalfoun, Baliza, Danielle Pereira
Tipo de documento: Artigo
Idioma: por
Título da fonte: Coffee Science (Online)
Texto Completo: https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197
Resumo: Familiar farmers have attended to quality and differentiation requirements to achieve markets with higher values. The certification is a management tool that may be required in this context. The rules of certification are based on principles of Good Agricultural Practices. The aim in this study was characterize the good agricultural practices used in the coffee production by coffee producers of Association of Familiar Agriculturists of Santo Antonio do Amparo (AFASA), in Minas Gerais State, by means of Cluster analysis. The research was performed through a survey type structured questionnaire, which was answered by all Association members. The original questionnaire of the research was separated into two parts. However, in this study was used only the second part, which has 104 variables distributed in a rating scale: 1, “not applicable in the property”, 2, “not have or not carried out”, 3, “sometimes or partially”, 4, “always, or yes” in relation to practices done in the property. The data were tabulated and analyzed by SPSS software. It was calculated the cluster multivariate analysis, which has as objective to group the individuals (cases) with similar characteristics in function of a set of selected variables that separated, in this case, the producers in two different groups. In this study was discussed the variables that present significant differences higher than p< 0,05 by the test Qui-Square of Pearson between two groups of farmers. The farmers of group 2 exhibited characteristic of higher organization in relation to principles of Good Agricultural Practices.
id UFLA-4_40c98e077564413556ad367c548b2518
oai_identifier_str oai:coffeescience.ufla.br:article/1197
network_acronym_str UFLA-4
network_name_str Coffee Science (Online)
repository_id_str
spelling Good agricultural practices in an association of familiar coffee producers by means of clusters analysisEstudo sobre boas práticas agrícolas em uma associação de cafeicultores familiares por meio da análise de clustersSustainabilitytechnical assistancegood practices agriculturalcoffee productionSustentabilidadeboas práticas agrícolascertificaçãocafeiculturaFamiliar farmers have attended to quality and differentiation requirements to achieve markets with higher values. The certification is a management tool that may be required in this context. The rules of certification are based on principles of Good Agricultural Practices. The aim in this study was characterize the good agricultural practices used in the coffee production by coffee producers of Association of Familiar Agriculturists of Santo Antonio do Amparo (AFASA), in Minas Gerais State, by means of Cluster analysis. The research was performed through a survey type structured questionnaire, which was answered by all Association members. The original questionnaire of the research was separated into two parts. However, in this study was used only the second part, which has 104 variables distributed in a rating scale: 1, “not applicable in the property”, 2, “not have or not carried out”, 3, “sometimes or partially”, 4, “always, or yes” in relation to practices done in the property. The data were tabulated and analyzed by SPSS software. It was calculated the cluster multivariate analysis, which has as objective to group the individuals (cases) with similar characteristics in function of a set of selected variables that separated, in this case, the producers in two different groups. In this study was discussed the variables that present significant differences higher than p< 0,05 by the test Qui-Square of Pearson between two groups of farmers. The farmers of group 2 exhibited characteristic of higher organization in relation to principles of Good Agricultural Practices.Para acessar mercados de maior valor, faz-se necessário que os agricultores familiares atendam às exigências de qualidade e diferenciação sendo a certificação uma ferramenta de gestão que pode ser exigida neste contexto. As normas de certificação são baseadas nos princípios das boas práticas agrícolas. O objetivo neste estudo foi caracterizar as boas práticas agrícolas utilizadas para a produção de café pelos produtores da Associação de Agricultores Familiares (AFASA) em Santo Antônio do Amparo, MG, por meio da análise de Clusters. A pesquisa foi realizada por meio de um questionário estruturado do tipo survey, respondido por todos os membros da Associação. O questionário original da pesquisa foi dividido em duas partes. No entanto, para esta pesquisa foi utilizada apenas a segunda parte, que continha 104 variáveis em uma escala de pontos: 1, “não se aplica na propriedade”, 2, “não possuo ou não realizo”, 3, “de vez em quando ou parcialmente”, 4, “sempre, ou sim” em relação à realização das práticas agrícolas adotadas na propriedade. Os dados foram tabulados e analisados pelo software SPSS. Foi realizada a análise estatística multivariada de cluster; técnica que objetiva agrupar os indivíduos (casos) com características semelhantes em função de um conjunto de variáveis selecionadas que separou, neste caso, os produtores em dois grupos distintos. Neste artigo foram discutidas as variáveis da segunda parte do questionário que apresentaram diferenças significativas maiores que p< 0,05 pelo teste de Qui-quadrado de Pearson entre os dois grupos de produtores. Os produtores do grupo 2 apresentaram características de maior organização diante dos princípios das BPA’s.Editora UFLA2017-03-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/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/1197Coffee Science - ISSN 1984-3909; Vol. 12 No. 1 (2017); 49 - 59Coffee Science; Vol. 12 Núm. 1 (2017); 49 - 59Coffee Science; v. 12 n. 1 (2017); 49 - 591984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/pdf_1197https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1685https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1686https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1687https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1688https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1689https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1690Copyright (c) 2017 Coffee Science - ISSN 1984-3909https://creativecommons.org/info:eu-repo/semantics/openAccessRosa, Beatriz TerezinhaBorges, Luís Antônio CoimbraPereira, Sérgio ParreirasAntonialli, Luíz MarceloSouza, Sára Maria ChalfounBaliza, Danielle Pereira2017-03-30T16:15:17Zoai:coffeescience.ufla.br:article/1197Revistahttps://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:2024-05-21T19:53:59.367632Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
Estudo sobre boas práticas agrícolas em uma associação de cafeicultores familiares por meio da análise de clusters
title Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
spellingShingle Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
Rosa, Beatriz Terezinha
Sustainability
technical assistance
good practices agricultural
coffee production
Sustentabilidade
boas práticas agrícolas
certificação
cafeicultura
title_short Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
title_full Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
title_fullStr Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
title_full_unstemmed Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
title_sort Good agricultural practices in an association of familiar coffee producers by means of clusters analysis
author Rosa, Beatriz Terezinha
author_facet Rosa, Beatriz Terezinha
Borges, Luís Antônio Coimbra
Pereira, Sérgio Parreiras
Antonialli, Luíz Marcelo
Souza, Sára Maria Chalfoun
Baliza, Danielle Pereira
author_role author
author2 Borges, Luís Antônio Coimbra
Pereira, Sérgio Parreiras
Antonialli, Luíz Marcelo
Souza, Sára Maria Chalfoun
Baliza, Danielle Pereira
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Rosa, Beatriz Terezinha
Borges, Luís Antônio Coimbra
Pereira, Sérgio Parreiras
Antonialli, Luíz Marcelo
Souza, Sára Maria Chalfoun
Baliza, Danielle Pereira
dc.subject.por.fl_str_mv Sustainability
technical assistance
good practices agricultural
coffee production
Sustentabilidade
boas práticas agrícolas
certificação
cafeicultura
topic Sustainability
technical assistance
good practices agricultural
coffee production
Sustentabilidade
boas práticas agrícolas
certificação
cafeicultura
description Familiar farmers have attended to quality and differentiation requirements to achieve markets with higher values. The certification is a management tool that may be required in this context. The rules of certification are based on principles of Good Agricultural Practices. The aim in this study was characterize the good agricultural practices used in the coffee production by coffee producers of Association of Familiar Agriculturists of Santo Antonio do Amparo (AFASA), in Minas Gerais State, by means of Cluster analysis. The research was performed through a survey type structured questionnaire, which was answered by all Association members. The original questionnaire of the research was separated into two parts. However, in this study was used only the second part, which has 104 variables distributed in a rating scale: 1, “not applicable in the property”, 2, “not have or not carried out”, 3, “sometimes or partially”, 4, “always, or yes” in relation to practices done in the property. The data were tabulated and analyzed by SPSS software. It was calculated the cluster multivariate analysis, which has as objective to group the individuals (cases) with similar characteristics in function of a set of selected variables that separated, in this case, the producers in two different groups. In this study was discussed the variables that present significant differences higher than p< 0,05 by the test Qui-Square of Pearson between two groups of farmers. The farmers of group 2 exhibited characteristic of higher organization in relation to principles of Good Agricultural Practices.
publishDate 2017
dc.date.none.fl_str_mv 2017-03-30
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/1197
url https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/pdf_1197
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1685
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1686
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1687
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1688
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1689
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/1197/1690
dc.rights.driver.fl_str_mv Copyright (c) 2017 Coffee Science - ISSN 1984-3909
https://creativecommons.org/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Coffee Science - ISSN 1984-3909
https://creativecommons.org/
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
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. 1 (2017); 49 - 59
Coffee Science; Vol. 12 Núm. 1 (2017); 49 - 59
Coffee Science; v. 12 n. 1 (2017); 49 - 59
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_ 1799874920979628032