Genetic parameters for production traits in primiparous Holstein cows estimated by random regression models

Abstract

-The objective of this study was to estimate genetic parameters for milk, fat and protein yields of Holstein cows using 56,508; 35,091 and 8,326 test-day milk records from 7,015, 4,476 and 1,114 cows, calves of 359, 246 and 90 bulls, respectively. The additive genetic and permanent environmental effects were estimated using REML. Random regression models with Legendre polynomials from order 3 to 6 were used. Residual variances were considered homogeneous over the lactation period. The estimates of variance components showed similar trends, with an increase of the polynomial order for each trait. The heritability estimates ranged from 0.14 to 0.31; 0.03 to 0.21 and 0.09 to 0.33 for milk, fat and protein yield, respectively. Genetic correlations among milk, fat and protein yields ranged from 0.02 to 1.00; 0.34 to 1.00 and 0.42 to 1.00, respectively. Models with higher order Legendre polynomials are the best suited to adjust test-day data for the three production traits studied. herdabilidade variaram, respectivamente, de 0,14 a 0,31; 0,03 a 0,21; e 0,09 a 0,33 para as produções de leite, de gordura e de proteína. As correlações genéticas entre produções de leite, gordura e proteína do leite variaram de 0,02 a 1,00; 0,34 a 1,00 e 0,42 a 1,00, respectivamente. Os modelos com polinômio de Legendre de maior ordem são os mais adequados para ajuste da produção no dia do controle das três características produtivas.Palavras-chave: dia do controle, herdabilidade, produção de gordura, produção de leite, produção de proteína Revista Brasileira de Zootecnia

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

“…Considering the Holstein breed in Brazil, heritability estimates for the test-day milk yield, adjusted with the Legendre polynomials, Wilmink, Ali & Schaeffer under RRM range from .11 to .31 (Cobuci et al, 2004;Cobuci et al, 2006;Araújo et al, 2006;Costa et al, 2008;Biassus, Cobuci, & Costa, 2011). These results are in agreement with heritability results observed in studies with Holsteins from other countries, ranging from 0.08 to 0.23 (Hahammi et al, 2008;Silvestre, Petim-Batista, & Colaço, 2006;Strabel & Misztal, 1999).…”

“…The residual variance was assumed to be constant throughout the lactation and independent between milk records (Costa et al, 2008;Biassus, Cobuci, & Costa, 2011). The different functions adopted, characterizing the different sub-models of random regression, have been adjusted in bz, az and pz in order to model the fixed and random animal effects and animal environmental permanent, respectively.…”

Reliability of breeding values between random regression and 305-day lactation models

“…In Brazil, genetic evaluations of Holstein cattle for these yields have been carried out using a 305-day lactation model (Ferreira et al, 2003;Costa et al, 2009;Biassus et al, 2011). Alternatively, many other approaches, as repeatability, autoregressive or random regression models (Melo et al, 2007;Costa et al, 2008Costa et al, , 2009Bignardi et al, 2011) proposed using the test-day records directly in test-day models (TDM) instead of lactation models (Jensen, 2001).…”

“…In fact, Germany, Canada, United Kingdom and Italy have already adopted random regression models in their national genetic evaluations, using Legendre polynomials of third, fourth or fifth orders (Muir et al, 2007;Yamazaki et al, 2013). Costa et al (2008), Biassus et al (2011), and Cobuci et al (2011) studied the use of random regression models with Legendre polynomials, in order to determine the best order for genetic evaluation of Holstein cattle in Brazil, and to substitute the current 305-day lactation model. However, there are few studies on milk and its components, as fat and protein, in tropical countries as Brazil, using random regression models in the genetic evaluations of Holstein breed (Costa et al, 2008;Biassus et al, 2010).…”

“…However, there are few studies on milk and its components, as fat and protein, in tropical countries as Brazil, using random regression models in the genetic evaluations of Holstein breed (Costa et al, 2008;Biassus et al, 2010). In general, the random regression models using Legendre polynomials of fourth, fifth and sixth orders have been indicated as a good option for conducting genetic evaluations of Holstein cattle; however, there are no comparisons between random regression and lactation models as for the advantages in the gain of reliability of breeding values from studies on Brazilian Holsteins (Costa et al, 2008;Biassus et al, 2010Biassus et al, , 2011.…”