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Characterization of milk production systems in the county of Alegrete, RS, Brazil, based on productive indexes
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.
Afiliação
  • Silva, Caroline Alvares; University of Campanha Region. Alegrete. BR
  • Tadielo, Leonardo Ereno; São Paulo State University. Botucatu. BR
  • Kasper, Neliton Flores; Private Practice. Uruguaiana. BR
  • Altermann, Othon Dalla Colletta; Private Practice. Uruguaiana. BR
  • Gayer, Taiani Ourique; University of Campanha Region. Alegrete. BR
  • Krolow, Rodrigo Holz; University of Campanha Region. Alegrete. BR
  • Oaigen, Ricardo Pedroso; University of Campanha Region. Alegrete. BR
  • Castagnara, Deise Dalazen; University of Campanha Region. Alegrete. BR
Biosci. j. (Online) ; 37: e37033, Jan.-Dec. 2021. tab, graf
Artigo em Inglês | LILACS | ID: biblio-1358899
Biblioteca responsável: BR396.1
ABSTRACT
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.
Assuntos


Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: LILACS Assunto principal: Indústria de Laticínios / Tecnologia de Produtos País/Região como assunto: América do Sul / Brasil Idioma: Inglês Revista: Biosci. j. (Online) Assunto da revista: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: Brasil Instituição/País de afiliação: Private Practice/BR / São Paulo State University/BR / University of Campanha Region/BR

Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: LILACS Assunto principal: Indústria de Laticínios / Tecnologia de Produtos País/Região como assunto: América do Sul / Brasil Idioma: Inglês Revista: Biosci. j. (Online) Assunto da revista: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: Brasil Instituição/País de afiliação: Private Practice/BR / São Paulo State University/BR / University of Campanha Region/BR
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