Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes

Detalhes bibliográficos
Autor(a) principal: Silva, Caroline Alvares
Data de Publicação: 2021
Outros Autores: Tadielo, Leonardo Ereno, Kasper, Neliton Flores, Altermann, Othon Dalla Colletta, Gayer, Taiani Ourique, Krolow, Rodrigo Holz, Oaigen, Ricardo Pedroso, Castagnara, Deise Dalazen
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bioscience journal (Online)
Texto Completo: https://seer.ufu.br/index.php/biosciencejournal/article/view/42184
Resumo: This study aimed to characterize dairy production systems in Alegrete, RS, Brazil, based on productive indices, management practices, and technification. The present study was conducted on 43 farms distributed in 22 localities of the county. The collection of data on milk production systems was carried out through visits to the properties, using a semi-structured guide questionnaire. The data obtained with the questionnaires were tabulated in Excel and with the aid of the IBM SPSS Statistics 20.0 software, through multivariate statistics, data were submitted to main component analysis (MCA) and hierarchical clusters analysis (HCA), allowing the division of 43 production units into homogeneous groups. The studied variables were summarized through the MCA in two main components (1 and 2), which clarified 71.53% of the explained variance. The alpha-Cronbach values observed for the two main components totaled 0.977, a result that confirms the reliability of the questionnaire used and reveals the high correlation between the answers obtained. From the hierarchical classification analysis, the dataset of the 43-farm studied was reduced to six groups (G1, G2, G3, G4, G5, and G6). The quadrants obtained from the insertion of the axes of the main components 1 and 2 allowed the interpretation of the groups of systems, according to the characteristics related to milk production. G2 presented the highest number of farms of the six systems formed, representing 41.86% of the establishments studied. These are characterized by being a more productive farm, an average 881-1 L day, with greater technological adoption of production and greater area destined to milk production, corresponding to the average of 78 hectares. The productive aspects that define the characteristics of milk production systems in the county were related to the structure of the herd, pasture area, daily production, disposal criteria, and milking management. The main differences found in the different groups are related to the productive indexes, suggesting that the technical assistance and rural extension actions in the dairy production systems in the county of Alegrete should be directed according to the individual need of each group formed.
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spelling Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexesCluster AnalysisDairy PropertiesProduction SystemsTechnology.Veterinary MedicineThis study aimed to characterize dairy production systems in Alegrete, RS, Brazil, based on productive indices, management practices, and technification. The present study was conducted on 43 farms distributed in 22 localities of the county. The collection of data on milk production systems was carried out through visits to the properties, using a semi-structured guide questionnaire. The data obtained with the questionnaires were tabulated in Excel and with the aid of the IBM SPSS Statistics 20.0 software, through multivariate statistics, data were submitted to main component analysis (MCA) and hierarchical clusters analysis (HCA), allowing the division of 43 production units into homogeneous groups. The studied variables were summarized through the MCA in two main components (1 and 2), which clarified 71.53% of the explained variance. The alpha-Cronbach values observed for the two main components totaled 0.977, a result that confirms the reliability of the questionnaire used and reveals the high correlation between the answers obtained. From the hierarchical classification analysis, the dataset of the 43-farm studied was reduced to six groups (G1, G2, G3, G4, G5, and G6). The quadrants obtained from the insertion of the axes of the main components 1 and 2 allowed the interpretation of the groups of systems, according to the characteristics related to milk production. G2 presented the highest number of farms of the six systems formed, representing 41.86% of the establishments studied. These are characterized by being a more productive farm, an average 881-1 L day, with greater technological adoption of production and greater area destined to milk production, corresponding to the average of 78 hectares. The productive aspects that define the characteristics of milk production systems in the county were related to the structure of the herd, pasture area, daily production, disposal criteria, and milking management. The main differences found in the different groups are related to the productive indexes, suggesting that the technical assistance and rural extension actions in the dairy production systems in the county of Alegrete should be directed according to the individual need of each group formed.EDUFU2021-06-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/4218410.14393/BJ-v37n0a2021-42184Bioscience Journal ; Vol. 37 (2021): Continuous Publication; e37033Bioscience Journal ; v. 37 (2021): Continuous Publication; e370331981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/42184/32091Brazil; ContemporaryCopyright (c) 2021 Caroline Alvares Silva, Leonardo Ereno Tadielo, Neliton Flores Kasper, Othon Dalla Colletta Altermann, Taiani Ourique Gayer, Rodrigo Holz Krolow, Ricardo Pedroso Oaigen, Deise Dalazen Castagnarahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSilva, Caroline AlvaresTadielo, Leonardo ErenoKasper, Neliton FloresAltermann, Othon Dalla CollettaGayer, Taiani OuriqueKrolow, Rodrigo HolzOaigen, Ricardo PedrosoCastagnara, Deise Dalazen2022-05-25T12:16:13Zoai:ojs.www.seer.ufu.br:article/42184Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2022-05-25T12:16:13Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
title Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
spellingShingle Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
Silva, Caroline Alvares
Cluster Analysis
Dairy Properties
Production Systems
Technology.
Veterinary Medicine
title_short Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
title_full Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
title_fullStr Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
title_full_unstemmed Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
title_sort Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
author Silva, Caroline Alvares
author_facet Silva, Caroline Alvares
Tadielo, Leonardo Ereno
Kasper, Neliton Flores
Altermann, Othon Dalla Colletta
Gayer, Taiani Ourique
Krolow, Rodrigo Holz
Oaigen, Ricardo Pedroso
Castagnara, Deise Dalazen
author_role author
author2 Tadielo, Leonardo Ereno
Kasper, Neliton Flores
Altermann, Othon Dalla Colletta
Gayer, Taiani Ourique
Krolow, Rodrigo Holz
Oaigen, Ricardo Pedroso
Castagnara, Deise Dalazen
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Silva, Caroline Alvares
Tadielo, Leonardo Ereno
Kasper, Neliton Flores
Altermann, Othon Dalla Colletta
Gayer, Taiani Ourique
Krolow, Rodrigo Holz
Oaigen, Ricardo Pedroso
Castagnara, Deise Dalazen
dc.subject.por.fl_str_mv Cluster Analysis
Dairy Properties
Production Systems
Technology.
Veterinary Medicine
topic Cluster Analysis
Dairy Properties
Production Systems
Technology.
Veterinary Medicine
description This study aimed to characterize dairy production systems in Alegrete, RS, Brazil, based on productive indices, management practices, and technification. The present study was conducted on 43 farms distributed in 22 localities of the county. The collection of data on milk production systems was carried out through visits to the properties, using a semi-structured guide questionnaire. The data obtained with the questionnaires were tabulated in Excel and with the aid of the IBM SPSS Statistics 20.0 software, through multivariate statistics, data were submitted to main component analysis (MCA) and hierarchical clusters analysis (HCA), allowing the division of 43 production units into homogeneous groups. The studied variables were summarized through the MCA in two main components (1 and 2), which clarified 71.53% of the explained variance. The alpha-Cronbach values observed for the two main components totaled 0.977, a result that confirms the reliability of the questionnaire used and reveals the high correlation between the answers obtained. From the hierarchical classification analysis, the dataset of the 43-farm studied was reduced to six groups (G1, G2, G3, G4, G5, and G6). The quadrants obtained from the insertion of the axes of the main components 1 and 2 allowed the interpretation of the groups of systems, according to the characteristics related to milk production. G2 presented the highest number of farms of the six systems formed, representing 41.86% of the establishments studied. These are characterized by being a more productive farm, an average 881-1 L day, with greater technological adoption of production and greater area destined to milk production, corresponding to the average of 78 hectares. The productive aspects that define the characteristics of milk production systems in the county were related to the structure of the herd, pasture area, daily production, disposal criteria, and milking management. The main differences found in the different groups are related to the productive indexes, suggesting that the technical assistance and rural extension actions in the dairy production systems in the county of Alegrete should be directed according to the individual need of each group formed.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-28
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://seer.ufu.br/index.php/biosciencejournal/article/view/42184
10.14393/BJ-v37n0a2021-42184
url https://seer.ufu.br/index.php/biosciencejournal/article/view/42184
identifier_str_mv 10.14393/BJ-v37n0a2021-42184
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/biosciencejournal/article/view/42184/32091
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Brazil; Contemporary
dc.publisher.none.fl_str_mv EDUFU
publisher.none.fl_str_mv EDUFU
dc.source.none.fl_str_mv Bioscience Journal ; Vol. 37 (2021): Continuous Publication; e37033
Bioscience Journal ; v. 37 (2021): Continuous Publication; e37033
1981-3163
reponame:Bioscience journal (Online)
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Bioscience journal (Online)
collection Bioscience journal (Online)
repository.name.fl_str_mv Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv biosciencej@ufu.br||
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