Characterization of milk production systems in the county of alegrete, rs, brazil, based on productive indexes
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.14393/BJ-v37n0a2021-42184 http://hdl.handle.net/11449/221957 |
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. |
id |
UNSP_f3d5483916abeedd9b8aad0beb357c54 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/221957 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Characterization of milk production systems in the county of alegrete, rs, brazil, based on productive indexesCluster AnalysisDairy PropertiesProduction SystemsTechnologyThis 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.Department of Veterinary Medicine University of Campanha RegionVeterinary Medicine São Paulo State UniversityPrivate PracticeVeterinary Medicine São Paulo State UniversityUniversity of Campanha RegionUniversidade Estadual Paulista (UNESP)Private PracticeSilva, Caroline AlvaresTadielo, Leonardo Ereno [UNESP]Kasper, Neliton FloresAltermann, Othon Dalla CollettaGayer, Taiani OuriqueKrolow, Rodrigo HolzOaigen, Ricardo PedrosoCastagnara, Deise Dalazen2022-04-28T19:41:33Z2022-04-28T19:41:33Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.14393/BJ-v37n0a2021-42184Bioscience Journal, v. 37.1981-31631516-3725http://hdl.handle.net/11449/22195710.14393/BJ-v37n0a2021-421842-s2.0-85110119724Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBioscience Journalinfo:eu-repo/semantics/openAccess2022-04-28T19:41:33Zoai:repositorio.unesp.br:11449/221957Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:37:31.130855Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)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 |
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 [UNESP] 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 [UNESP] 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.none.fl_str_mv |
University of Campanha Region Universidade Estadual Paulista (UNESP) Private Practice |
dc.contributor.author.fl_str_mv |
Silva, Caroline Alvares Tadielo, Leonardo Ereno [UNESP] 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 |
topic |
Cluster Analysis Dairy Properties Production Systems Technology |
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 |
2021-01-01 2022-04-28T19:41:33Z 2022-04-28T19:41:33Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.14393/BJ-v37n0a2021-42184 Bioscience Journal, v. 37. 1981-3163 1516-3725 http://hdl.handle.net/11449/221957 10.14393/BJ-v37n0a2021-42184 2-s2.0-85110119724 |
url |
http://dx.doi.org/10.14393/BJ-v37n0a2021-42184 http://hdl.handle.net/11449/221957 |
identifier_str_mv |
Bioscience Journal, v. 37. 1981-3163 1516-3725 10.14393/BJ-v37n0a2021-42184 2-s2.0-85110119724 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Bioscience Journal |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129342433132544 |