Análise da atividade leiteira e caracterização de diferentes sistemas de produção na região Centro-Oriental do Paraná

• Ano de defesa: 2012
• Autor(a) principal: Schiavon, Raquel Schiavon
• Orientador(a): Bianchi, Ivan
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Pelotas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Veterinária
• Departamento: Veterinária
• País: BR
• Palavras-chave em Português: Propriedade leiteira; Produtividade; Rentabilidade; Custo de produção
• Palavras-chave em Inglês: Dairy farm; Productivity; Profitability; Production costs
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::MEDICINA VETERINARIA
• Link de acesso: https://guaiaca.ufpel.edu.br/handle/123456789/2485

The different dairy production systems and heterogeneity of processes in Brazil has different inputs impact on production. The production system is one of the factors that may influence the cost and profitability. The aim of this study was characterize the different production systems in Central Eastern of Paraná and identify variables that can predict performance in different economic systems. Monthly data of area, economic and productive performance and dairy quality results of 50 farms records were collected. The collected indicators were referent the period from November 2008 to October 2010. The Kruskal-Wallis test and descriptive analysis were doing to characterize and compare the production systems. After a factor analysis was performed too and the results were used in the Linear Regression Analysis. The systems were very different, defining the properties between intensive and semi intensive production, according to size, zootechnical and economical indicators performance. The variables were then grouped into six factors, according to Factor Analysis. The Factor II was composed by Fat (%) and protein (%) variables and the Factor III by rate capacity (UA/ha) and Productivity (l/ha/year) variable. The Factor II and Factor III were significant (p<0.05) on prediction of dependent variable Price Paid (R$/l). The Linear Regression result showed that approximately 13% of price paid to producers can be attributed to fat and protein milk composition and yield properties.