Jaegwan Choi

Estimation of Genetic Associations between Production and Meat Quality Traits in Duroc Pigs

Data collected from 690 purebred Duroc pigs from 2009 to 2012 were used to estimate the heritability, and genetic and phenotypic correlations between production and meat quality traits. Variance components were obtained through the restricted maximum likelihood procedure using Wombat and SAS version 9.0. Animals were raised under the same management in five different breeding farms. The average daily gain, loin muscle area (LMA), backfat thickness (BF), and lean percent (LP) were measured as production traits. Meat quality traits included pH, cooking loss, lightness (L*), redness (a*), yellowness (b*), marbling score (MS), moisture content (MC), water holding capacity (WHC), and shear force. The results showed that the heritability estimates for meat quality traits varied largely from 0.19 to 0.79. Production traits were moderate to highly heritable from 0.41 to 0.73. Genotypically, the BF was positively correlated (p<0.05) with MC (0.786), WHC (0.904), and pH (0.328) but negatively correlated with shear force (−0.533). The results of genetic correlations indicated that selection for less BF could decrease pH, moisture content, and WHC and increase the shear force of meat. Additionally, a significant positive correlation was recorded between average daily gain and WHC, which indicates pork from faster-growing animals has higher WHC. Furthermore, selection for larger LMA and LP could increase MS and lightness color of meat. The meat quality and production traits could be improved simultaneously if desired. Hence, to avoid further deterioration of pork characteristics, appropriate selection of traits should be considered.

Genetic Relationship of Productive Life, Production and Type Traits of Korean Holsteins at Early Lactations.

The present study was performed to study the genetic relationship of productive life with production and type traits of Korean Holsteins at first three lactations. The data for the analysis from 56,054, 28,997, and 11,816 animals of first, second and third parity cows which were born from 2006 to 2011 were collected by Dairy Cattle Improvement Center, National Agricultural Co-operative Federation. Milk, protein and fat yields adjusted for 305 days and average somatic cell score considered as production traits and analyzed type traits were stature, strength, body depth, dairy form, rump angle, rump width, rear leg side view, foot angle, front attachment placement, rear attachment height, rear attachment width, udder cleft, udder depth, front teat placement and front teat length. A multi trait genetic analysis was performed using Wombat program with restricted maximum likelihood animal model composed of fixed effect of birth year, farm and the random effect of animal and random residual effect according to the traits. Heritability estimates of productive life were between 0.06 and 0.13. Genetic and phenotypic correlations between production and productive life traits ranged from 0.35 to 0.04 for milk, 0.16 to 0.05 for protein and 0.18 to 0.02 f 15-0034 (2nd) 150520 or fat. Somatic cells score showed a negative genetic and phenotypic correlation with productive life and also udder type traits, indicating that the selection for higher udder traits will likely to improve resistance to mastitis and persistence in the herd. Among all dairy form type traits, udder characters such as udder cleft showed a significant relationship with productive life. However, a specific change of heritabilities or correlations were not observed with the change of parity. Moreover, further studies are needed to further confirm the significance of the above traits and the effect of parity on above relationships in order to minimize both voluntary and involuntary culling rates while improving herd health and maintaining high yielding dairy cows.

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.

A study for implementation of monitoring system for genetic improvement of swine breeding stock

This paper sketches the strategies and designs for monitoring system of swine genetic improvement. The system should reflect every side of pig production. The system leads us to assess the efficiency of pig production and the scope of the system includes not only nucleus, multiplying and commercial herds, but also packing and processing sectors. For more accurate statistics, data for this monitoring system must be collected from all above mentioned areas, but not by random sampling. Futhermore, data analysis results including seedstocks and distribution information of genetic trend should be included in the system. The schema of knowledge database system could be employed in the system. The monitoring system in the final destination would unify the systems derived from various sources and provide any solution in swine industry including pig breeding.

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.

The Outcomes of Selection in a Closed Herd on a Farm in Operation

A herd of Berkshire pigs was established in 2003 and subjected to selection without introduction of any genetic resources until 2007. The complete pedigree, including 410 boars and 916 sows, as well as the records from 5,845 pigs and 822 litters were used to investigate the results obtained from the selections. The index of selection for breeding values included days to 90 kg (D90kg), backfat thickness (BF) and number of piglets born alive (NBA). The average inbreeding coefficients of pigs were found to be 0.023, 0.008, 0.013, 0.025, 0.026, and 0.005 from 2003 to 2007, respectively. The genetic gains per year were 12.1 g, −0.04 mm, −3.13 days, and 0.181 head for average daily gain (ADG), BF, D90kg, and NBA, respectively. Breeding values of ADG, BF and D90kg were not significantly correlated with inbreeding coefficients of individuals, except for NBA (−0.21). The response per additional 1% of inbreeding was 0.0278 head reduction in NBA. The annual increase of inbreeding was 0.23% and the annual decrease in NBA due to inbreeding was 0.0064 head. This magnitude could be disregarded when compared with the annual gain in NBA (0.181 head). These results suggest that inbreeding and inbreeding depression on ordinary farms can be controlled with a proper breeding scheme and that breeding programs are economical and safe relative to the risks associated with importation of pigs.