Estimativas de parâmetros genéticos e de ambiente para medidas repetidas de produção de leite e de gordura em bovinos das raças Sindi e Guzerá

• Ano de defesa: 2007
• Autor(a) principal: CRUZ, George Rodrigo Beltrão da
• Orientador(a): RIBEIRO, Maria Norma
• Banca de defesa: ALBUQUERQUE, Lúcia Galvão de, BARBOSA, Severino Benone Paes, GONZAGA NETO, Severino
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal Rural de Pernambuco
• Programa de Pós-Graduação: Programa de Pós-Graduação em Zootecnia
• Departamento: Departamento de Zootecnia
• País: Brasil
• Palavras-chave em Português: Bovino; Curva de lactação; Parâmetro genético; Modelo não linear; Modelos estatístico
• Palavras-chave em Inglês: Bovine; Lactation curve; Genetic parameter; Nonlinear models; Statistical model
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::ZOOTECNIA
• Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/6770

The objective of this research was to identify the mathematical function that best fits the lactation curve of Guzerá and Sindi cattle. 840 lactations records (467 – Guzerá, 373 – Sindi) were used from animals raised at Carnauba ranch, in the town of Taperoá, Paraíba. Milk production yield was recorded in 35 days intervals, between the years of 1986 and 2004. Six mathematical functions were used to perform fit to the mean curve and individual lactations: the Polynomial Inverse function (FPI), Hyperbolic lineal (FLH), Gamma incomplete (FGI), Quadratic Logarithmic (FQL), Lineal (FL) and Quadratic (FQ) were fitted using interactive processes through Non-lineal regression. The criteria used to verify the fit quality for each function were: Fitted determination coefficient (Ra 2 ), percent of deviation between the total production observed and estimated, and percent of typical curves. Residual distribution graphics were used only to evaluate the mean curve fit. In the mean curve, the values of Ra 2 were more than 0,93 in all functions. Good fits were obtained based on Ra 2 >0,80, respectively in 61,4% and 66.7% of the lactations fitted by FPI and FGI functions for Guzerá cattle. For Sindi cattle, these values were 57,2% and 50,0%, respectively, showing good quality of fit. FPI and FGI were closest to the production oscillations throughout lactation, even though estimated deviations between total productions were observed and estimated that were similar to the other functions. For mean curve, all functions could be used, because the functions were close. For individual lactations, better estimates of total milk production could be obtained by the FPI and FGI.