Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil

Detalhes bibliográficos
Autor(a) principal: Tadielo, Leonardo Ereno
Data de Publicação: 2020
Outros Autores: Bremm, Tainara, Kasper, Neliton Flores, da Silva, Caroline Alvarez, Gayer, Taiani Ourique, Pereira, Juliano Gonçalves, Soares, Vanessa Mendonça, 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/42462
Resumo: Evaluating and characterizing production systems using farm characteristics allows the diagnosis of failing points. This diagnosis can be used to improve the productive and zootechnical indices. Little is known about the milk production systems in the state of Rio Grande do Sul, therefore, the aim of this study was to characterize the milk production systems of the Northwest, Center Western and Southwest mesoregions of Rio Grande do Sul, considering the infrastructure, milk handling, milk quantity and composition, and nutritional intake of the cattle. To conduct this study, 38 Milk Production Units (MPUs) registered at the Municipal Secretaries of Agriculture and Emater/Ascar-RS were randomly selected. After being randomly selected, the dairy farms were visited and a semi-structured guide questionnaire was applied and milk samples were collected from expansion tanks. The milk was analyzed for somatic cell counts (SCC) and total bacterial counts (TBC). Data were evaluated through principal component analysis and cluster analysis. Multivariate analysis allowed the investigated variables to be reduced into two main components (CP1 and CP2). These two showed eigenvalues ​​greater than 1 (alpha> 1) and together explained 55.05% of the characteristics variability of the 38 MPUs studied. CP1 contemplated productive capacity and factors related to nutritional management of the MPUs, interfering directly with reproductive performance. CP2 comprised milk handling and daily production. Using these main variables, the data set generated from the 38 MPUs studied were adjusted and classified into five groups (G1, G2, G3, G4, and G5). The characteristics of these groups differed statistically especially in infrastructure and nutritional management of the cattle. Due to their particularities, each of these five groups of MPUs requires strategic technical interventions to improve their productive indexes.
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spelling Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, BrazilCaracterização de unidades de produção de leite por variáveis sanitárias, nutricionais e de infraestrutura nas mesorregiões noroeste, centro ocidental e sudoeste do Rio Grande do Sul, BrasilManagement.Production SystemsMilk Quality.Agricultural SciencesGestão.Sistemas de ProduçãoQualidade do Leite.Evaluating and characterizing production systems using farm characteristics allows the diagnosis of failing points. This diagnosis can be used to improve the productive and zootechnical indices. Little is known about the milk production systems in the state of Rio Grande do Sul, therefore, the aim of this study was to characterize the milk production systems of the Northwest, Center Western and Southwest mesoregions of Rio Grande do Sul, considering the infrastructure, milk handling, milk quantity and composition, and nutritional intake of the cattle. To conduct this study, 38 Milk Production Units (MPUs) registered at the Municipal Secretaries of Agriculture and Emater/Ascar-RS were randomly selected. After being randomly selected, the dairy farms were visited and a semi-structured guide questionnaire was applied and milk samples were collected from expansion tanks. The milk was analyzed for somatic cell counts (SCC) and total bacterial counts (TBC). Data were evaluated through principal component analysis and cluster analysis. Multivariate analysis allowed the investigated variables to be reduced into two main components (CP1 and CP2). These two showed eigenvalues ​​greater than 1 (alpha> 1) and together explained 55.05% of the characteristics variability of the 38 MPUs studied. CP1 contemplated productive capacity and factors related to nutritional management of the MPUs, interfering directly with reproductive performance. CP2 comprised milk handling and daily production. Using these main variables, the data set generated from the 38 MPUs studied were adjusted and classified into five groups (G1, G2, G3, G4, and G5). The characteristics of these groups differed statistically especially in infrastructure and nutritional management of the cattle. Due to their particularities, each of these five groups of MPUs requires strategic technical interventions to improve their productive indexes.Avaliar e caracterizar sistemas de produção utilizando as características das propriedades permite diagnosticar os pontos falhos, visando melhorar os índices produtivos e zootécnicos, desse modo pouco se sabe sobre os sistemas de produção de leite no estado do Rio Grande do Sul. Assim, objetivou-se com este estudo caracterizar os sistemas de produção de leite das mesorregiões Noroeste, Centro-Oeste e Sudoeste do Rio Grande do Sul, considerando a infra-estrutura, a quantidade, qualidade e composição do leite e o manejo nutricional dos rebanhos. Para conduzir este estudo, 38 Unidades de Produção de Leite (UPLs) registradas nas Secretarias Municipais de Agricultura e Emater/Ascar-RS foram selecionadas aleatoriamente. Depois, as fazendas leiteiras foram visitadas, um questionário semi-estruturado foi aplicado e amostras de leite do tanque foram coletadas. O leite foi analisado quanto à contagem de células somáticas (CCS) e à contagem bacteriana total (CBT). Os dados foram avaliados através de análise de componentes principais e análise de cluster. A análise multivariada permitiu que as variáveis investigadas fossem reduzidas em dois componentes principais (CP1 e CP2). Estes apresentaram autovalores maiores que 1 (alfa> 1) e juntos explicaram 55,05% da variabilidade das características das 38 UPLs estudadas. O CP1 contemplou a capacidade produtiva e os fatores relacionados ao manejo nutricional das UPLs, interferindo diretamente no desempenho produtivo. CP2 compreendeu manipulação de leite e produção diária. Utilizando essas variáveis principais, os dados gerados a partir das 38 UPLs estudadas foram ajustados e estas classificadas em cinco grupos (G1, G2, G3, G4 e G5). As características desses grupos diferiram estatisticamente, especialmente em infraestrutura e manejo nutricional do rebanho. Devido a suas particularidades, cada um desses cinco grupos de MPUs requer intervenções técnicas estratégicas para melhorar seus índices produtivos.EDUFU2020-08-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/4246210.14393/BJ-v36n5a2020-42462Bioscience Journal ; Vol. 36 No. 5 (2020): Sept./Oct.; 1705-1714Bioscience Journal ; v. 36 n. 5 (2020): Sept./Oct.; 1705-17141981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/42462/29629Brazil; ContemporaryCopyright (c) 2020 Leonardo Ereno Tadielo, Tainara Bremm, Neliton Flores Kasper, Caroline Alvarez da Silva, Taiani Ourique Gayer, Juliano Gonçalves Pereira, Vanessa Mendonça Soares, Deise Dalazen Castagnarahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessTadielo, Leonardo ErenoBremm, TainaraKasper, Neliton Floresda Silva, Caroline AlvarezGayer, Taiani OuriquePereira, Juliano GonçalvesSoares, Vanessa MendonçaCastagnara, Deise Dalazen2022-06-14T11:23:10Zoai:ojs.www.seer.ufu.br:article/42462Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2022-06-14T11:23:10Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
Caracterização de unidades de produção de leite por variáveis sanitárias, nutricionais e de infraestrutura nas mesorregiões noroeste, centro ocidental e sudoeste do Rio Grande do Sul, Brasil
title Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
spellingShingle Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
Tadielo, Leonardo Ereno
Management.
Production Systems
Milk Quality.
Agricultural Sciences
Gestão.
Sistemas de Produção
Qualidade do Leite.
title_short Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
title_full Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
title_fullStr Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
title_full_unstemmed Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
title_sort Milk production units characterized by sanitary, nutritional and infrastructure variables in the northwest, center western and southwest mesoregions of Rio Grande do Sul, Brazil
author Tadielo, Leonardo Ereno
author_facet Tadielo, Leonardo Ereno
Bremm, Tainara
Kasper, Neliton Flores
da Silva, Caroline Alvarez
Gayer, Taiani Ourique
Pereira, Juliano Gonçalves
Soares, Vanessa Mendonça
Castagnara, Deise Dalazen
author_role author
author2 Bremm, Tainara
Kasper, Neliton Flores
da Silva, Caroline Alvarez
Gayer, Taiani Ourique
Pereira, Juliano Gonçalves
Soares, Vanessa Mendonça
Castagnara, Deise Dalazen
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Tadielo, Leonardo Ereno
Bremm, Tainara
Kasper, Neliton Flores
da Silva, Caroline Alvarez
Gayer, Taiani Ourique
Pereira, Juliano Gonçalves
Soares, Vanessa Mendonça
Castagnara, Deise Dalazen
dc.subject.por.fl_str_mv Management.
Production Systems
Milk Quality.
Agricultural Sciences
Gestão.
Sistemas de Produção
Qualidade do Leite.
topic Management.
Production Systems
Milk Quality.
Agricultural Sciences
Gestão.
Sistemas de Produção
Qualidade do Leite.
description Evaluating and characterizing production systems using farm characteristics allows the diagnosis of failing points. This diagnosis can be used to improve the productive and zootechnical indices. Little is known about the milk production systems in the state of Rio Grande do Sul, therefore, the aim of this study was to characterize the milk production systems of the Northwest, Center Western and Southwest mesoregions of Rio Grande do Sul, considering the infrastructure, milk handling, milk quantity and composition, and nutritional intake of the cattle. To conduct this study, 38 Milk Production Units (MPUs) registered at the Municipal Secretaries of Agriculture and Emater/Ascar-RS were randomly selected. After being randomly selected, the dairy farms were visited and a semi-structured guide questionnaire was applied and milk samples were collected from expansion tanks. The milk was analyzed for somatic cell counts (SCC) and total bacterial counts (TBC). Data were evaluated through principal component analysis and cluster analysis. Multivariate analysis allowed the investigated variables to be reduced into two main components (CP1 and CP2). These two showed eigenvalues ​​greater than 1 (alpha> 1) and together explained 55.05% of the characteristics variability of the 38 MPUs studied. CP1 contemplated productive capacity and factors related to nutritional management of the MPUs, interfering directly with reproductive performance. CP2 comprised milk handling and daily production. Using these main variables, the data set generated from the 38 MPUs studied were adjusted and classified into five groups (G1, G2, G3, G4, and G5). The characteristics of these groups differed statistically especially in infrastructure and nutritional management of the cattle. Due to their particularities, each of these five groups of MPUs requires strategic technical interventions to improve their productive indexes.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-13
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/42462
10.14393/BJ-v36n5a2020-42462
url https://seer.ufu.br/index.php/biosciencejournal/article/view/42462
identifier_str_mv 10.14393/BJ-v36n5a2020-42462
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/biosciencejournal/article/view/42462/29629
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. 36 No. 5 (2020): Sept./Oct.; 1705-1714
Bioscience Journal ; v. 36 n. 5 (2020): Sept./Oct.; 1705-1714
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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