Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3–L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of polynomials×3 types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

Genetic parameters for yearling weight, carcass traits, and primal-cut yields of Hanwoo cattle

Genetic parameters associated with yearling weight, carcass traits, and primal-cut yields of male Hanwoo cattle were investigated using univariate and bivariate animal models. The mean yearling weight (YWT), carcass weight (CWT), longissimus muscle area (LMA), backfat thickness (BFT), and marbling score (MS) were 352.47 ± 0.40 kg, 337.39 ± 0.64 kg, 78.28 ± 0.13 cm2, 8.45 ± 0.05 mm, and 3.25 ± 0.03, respectively. Total primal-cut yield (TPC) was 78.95 ± 0.10% of CWT, of which 42.3% was contributed by the forequarters (chuck, CHK; shoulder, SLD; ribs, RIB; and brisket and flank, BAF). Loins, top round (TRND), and round (RND) were associated with yields of 13.57%, 5.45 ± 0.01%, and 8.87 ± 0.02%, respectively. The largest cut studied was ribs (15.67 ± 0.03%). The estimated heritabilities (h2) of YWT, CWT, LMA, BFT, and MS were 0.18 ± 0.02, 0.29 ± 0.04, 0.38 ± 0.05, 0.45 ± 0.05, and 0.62 ± 0.07, respectively. Shoulder yield was highly heritable in Hanwoo steers (0.83 ± 0.13), followed by the yields of round (0.66 ± 0.12), striploin (0.64 ± 0.12), top round (0.62 ± 0.12), sirloin (0.60 ± 0.12), and total primal-cut yield (0.52 ± 0.11). The h2 values of CHK, BAF, RIB, and tenderloin (TLN) ranged from 0.19 ± 0.09 to 0.41 ± 0.11. Generally, the genetic CV was low for most traits (2.33%-6.15%), except for CHK, BFT, and MS. The genetic correlation (rg) was strong between YWT and CWT (0.77 ± 0.06). The greatest positive and negative rg among carcass traits were those between LMA and CWT (0.52 ± 0.08) and between LMA and BFT (-0.30 ± 0.09), respectively. The correlation between CHK and SLD (0.81 ± 0.14), and those between SLD, TLN, TRND, and RND, were mostly strong (0.77-0.87), but the rg between RIB and other traits were strongly negative. The TPC yield showed moderate to high rg with most primal cuts. The YWT, CWT, and LMA correlated notably with CHK, SLD, and loin yields, especially LMA. However, BFT and MS were negatively correlated with many primal cuts but RIB. Those rg estimates were also opposite of that of LMA and CWT with primal cuts. Phenotypic correlations (rp) were generally weaker than rg estimates. The rp of YWT, CWT, and LMA were either zero or moderately negative compared to those of the BFT and MS with primal cuts. Most primal cuts yielded positive rp estimates among them, except for RIB. Our results suggest that direct selection for YWT, various carcass traits, and primal-cut yields may increase the carcass value of Hanwoo males.

Estimation of Genetic Parameters for Somatic Cell Scores of Holsteins Using Multi-trait Lactation Models in Korea

The study was conducted to analyze the genetic parameters of somatic cell score (SCS) of Holstein cows, which is an important indicator to udder health. Test-day records of somatic cell counts (SCC) of 305-day lactation design from first to fifth lactations were collected on Holsteins in Korea during 2000 to 2012. Records of animals within 18 to 42 months, 30 to 54 months, 42 to 66 months, 54 to 78 months, and 66 to 90 months of age at the first, second, third, fourth and fifth parities were analyzed, respectively. Somatic cell scores were calculated, and adjusted for lactation production stages by Wilmink's function. Lactation averages of SCS (LSCS1 through LSCS5) were derived by further adjustments of each test-day SCS for five age groups in particular lactations. Two datasets were prepared through restrictions on number of sires/herd and dams/herd, progenies/sire, and number of parities/cow to reduce data size and attain better relationships among animals. All LSCS traits were treated as individual trait and, analyzed through multiple-trait sire models and single trait animal models via VCE 6.0 software package. Herd-year was fitted as a random effect. Age at calving was regressed as a fixed covariate. The mean LSCS of five lactations were between 3.507 and 4.322 that corresponded to a SCC range between 71,000 and 125,000 cells/mL; with coefficient of variation from 28.2% to 29.9%. Heritability estimates from sire models were within the range of 0.10 to 0.16 for all LSCS. Heritability was the highest at lactation 2 from both datasets (0.14/0.16) and lowest at lactation 5 (0.11/0.10) using sire model. Heritabilities from single trait animal model analyses were slightly higher than sire models. Genetic correlations between LSCS traits were strong (0.62 to 0.99). Very strong associations (0.96 to 0.99) were present between successive records of later lactations. Phenotypic correlations were relatively weaker (<0.55). All correlations became weaker at distant lactations. The estimated breeding values (EBVs) of LSCS traits were somewhat similar over the years for a particular lactation, but increased with lactation number increment. The lowest EBV in first lactation indicated that selection for SCS (mastitis resistance) might be better with later lactation records. It is expected that results obtained from these multi-trait lactation model analyses, being the first large scale SCS data analysis in Korea, would create a good starting step for application of advanced statistical tools for future genomic studies focusing on selection for mastitis resistance in Holsteins of Korea.

Effect of carcass traits on carcass prices of holstein steers in Korea

The present study investigated the contribution of carcass traits on carcass prices of Holstein steers in Korea. Phenotypic data consisted of 76,814 slaughtered Holsteins (1 to 6 yrs) from all over Korea. The means for live body weight at slaughter (BWT), chilled carcass weight (CWT), dressing percentage (DP), quantity grade index (QGI), eye muscle area (EMA), backfat thickness (BF) and marbling score (MS), carcass unit price (CUP), and carcass sell prices (CSP) were 729.0 kg, 414.2 kg, 56.79%, 64.42, 75.26 cm², 5.77 mm, 1.98, 8,952.80 Korean won/kg and 3,722.80 Thousand Korean won/head. Least squares means were significantly different by various age groups, season of slaughter, marbling scores and yield grades. Pearson’s correlation coefficients of CUP with carcass traits ranged from 0.12 to 0.62. Besides, the relationships of carcass traits with CSP were relatively stronger than those with CUP. The multiple regression models for CUP and CSP with carcass traits accounted 39 to 63% of the total variation, respectively. Marbling score had maximum economic effects (partial coefficients) on both prices. In addition, the highest standardized partial coefficients (relative economic weights) for CUP and CSP were calculated to be on MS and CWT by 0.608 and 0.520, respectively. Path analyses showed that MS (0.376) and CWT (0.336) had maximum total effects on CUP and CSP, respectively; whereas BF contributed negatively. Further sub-group (age and season of slaughter) analyses also confirmed the overall outcomes. However, the relative economic weights and total path contributions also varied among the animal sub-groups. This study suggested the significant influences of carcass traits on carcass prices; especially MS and CWT were found to govern the carcass prices of Holstein steers in Korea.