Genetic parameters for somatic cell score in the first three lactations of Czech Holstein and Fleckvieh breeds using a random regression model

Abstract

ABSTRACT:A multiple-lactation random regression model was applied to test-day somatic cell score (SCS) records from the first three lactations of Czech Holstein and Fleckvieh cows. For Holstein, the data included 26 314 cows, with 244 953, 76 188 and 26 153 test-day records in the first, second and third lactation, respectively. For Fleckvieh, the data included 24 061 cows, with 223 421, 93 358 and 31 305 test-day records in the first, second and third lactation, respectively. The linear model for SCS included the following factors (for the given parity): fixed herd-test date effect, fixed regressions on days in milk within the age-season class, random regressions for the animal genetic and random regressions for the permanent environmental effect of the cow. Third-degree Legendre polynomials were used for all regressions. Gibbs sampling was used to generate samples from the marginal posterior distributions of the model parameters. The resulting daily heritability ranged from 0.08 to 0.11 in the middle part of lactation and it increased only slightly with parity. Extremely high values (0.25, 0.21) observed especially at the beginning and end of the third lactation for Holstein might be caused by the "end-of-range" problem. The average daily heritabilities computed for the part of lactation between 45 and 255 days in milk (DIM) were in the range from 0.10 to 0.14. Daily permanent environmental variances were higher than the genetic variances and daily residual variances decreased with DIM. The residual variances in early lactation increased with lactation number. For both breeds, the highest genetic correlations computed for the part of lactation between DIM 45 and DIM 255 were obtained between the second and third lactation (0.95). The lowest daily genetic correlations of SCS in the same DIM between different lactations occurred at the beginning of lactation, especially between the first and third lactation. The permanent environmental correlations for selected DIM were lower than the respective genetic correlations.

Genetic and environmental parameters estimation for milk traits in Slovenian dairy sheep using random regression model

“…Besides additive genetic effect, our model contained in its random part the common flock environment effect and two permanent environment effects. Other studies treat the common flock environment effect mainly in the fixed part of the model, while only the permanent environment effect over lactations and additive genetic effect were fitted random (Ligda et al, 2000;Kominakis et al, 2001;Horstick et al, 2002;Cadavez et al, 2011;Zavadilová et al, 2011). The permanent environment effect within lactation partly refers to the animal, thus, the heritability estimates in our study could be lower than in the literature.…”

“…Schaeffer and Deckers (1994) were the first researchers who proposed random regression model to model test-day records of milk traits in dairy cattle. Soon afterwards, similar analyses were done in dairy cattle by Jamrozik and Schaeffer (1997), Van der Werf et al (1998), Olori et al (1999), Kettunen et al (2000), Cobuci et al (2005Cobuci et al ( , 2011, Druet et al (2005), Zavadilová et al (2011), and many others. Random regression model was also used for the genetic parameter estimation of milk traits in dairy sheep by Ligda et al (2000), Kominakis et al (2001), Horstick et al (2002), Banos et al (2005), Cadavez et al (2011), and even in dairy goats (Breda et al, 2006;Menéndez-Buxadera et al, 2010;Menezes et al, 2011).…”

Methods for calculating the breeding values of missing traits and their comparison

“…More correlated traits must be brought into calculation of the CBVs in cases of low correlation between the missing trait and other traits. Zavadilová et al (2011) stated the importance of sufficiently high correlation between selected BVs when considering to estimate the BV for a trait that is itself difficult to measure for selection purposes.…”

Bio-economic Models for Efficient Dairy Cattle Breeding

“…SCC is frequently used to consider the quality payments to dairy producers. It is the main reason why the SCC is daily checked by farmers during milking and secondly this trait is included in the breeding goals and selection schemes of many dairy cattle breeds (Zavadilová et al, 2011).…”