Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
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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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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1797069079792582656 |