• Asian-Australasian Journal of Animal Sciences
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• v.16 no.11
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• pp.1560-1564
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• 2003

The study was carried out in Sahiwal, Holstein Friesian, Jersey and crossbred cattle to find out the effect of genotype of beta-lactoglobulin gene on milk production traits. The polymorphism at beta-lactoglobulin gene was identified by conducting PCRRFLP studies. A 398 bp fragment of the gene was amplified and digested with Hae III restriction enzyme. The two alleles A and B and three genotypes AA, AB and BB were identified in all cattle breeds. The frequency of B allele was comparatively higher than that of A allele. The AA genotype produced significantly higher milk yield in Sahiwal cattle whereas BB genotype yielded higher milk in Holstein friesian cattle. In other cattle breeds the genotypic effect was non-significant. In conclusion it may be stated that the genotype with significantly higher milk yield may be favoured in the farm along with other conventional selection criteria to enhance the milk production of animals.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.5
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• pp.627-632
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• 2002

Genetic parameters for dairy performance traits were estimated, breeding values for the traits of all breeding sires and cows were predicted and the genetic trends were estimated using the breeding values in the Central Cattle Breeding Station (CCBS). A total of 3,801 records for Bangladeshi Local, 756 records for Red Sindhi and 959 records for Sahiwal covering the period from 1961 to 1997 were used in this analysis. Traits considered were total milk production per lactation (TLP), lactation length (LL) and daily milk yield (DMY). The genetic parameters were estimated by the REML using MTDFREML program. The breeding values were predicted by a best linear unbiased prediction (BLUP). In all sets of data, the genetic trends for the dairy performance traits were computed as averages of breeding values for cows born in the particular year. The estimates of heritability for TLP (0.26 and 0.27) and DMY (0.28 and 0.27) were moderate in Bangladeshi local and Red Sindhi breed, respectively. Furthermore, the heritability estimate for LL (0.24) was moderate in Red Sindhi. The estimates of heritabilities for all traits were low in Sahiwal. The repeatability estimate was high for TLP, moderate for LL and moderate to high for DMY. All variances estimated in Bangladeshi Local were low, comparing the respective values estimated in both Red Sindhi and Sahiwal. On the other hand, additive genetic variances for the three traits were estimated very low in Sahiwal. The genetic trends for the three dairy production traits have not been positive except for the recent trend in Bangladeshi Local.

• Journal of Animal Science and Technology
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• v.58 no.10
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• pp.38.1-38.6
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• 2016

Background: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. Results: Marginal posterior means of heritability estimates for SCS ($0.03{\pm}0.002$) were distinctly lower than those for milk ($0.204{\pm}0.006$), fat ($0.096{\pm}0.004$) and protein ($0.147{\pm}0.005$) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative ($-0.177{\pm}0.007$, $-0.165{\pm}0.008$ and $-0.152{\pm}0.007$ between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from $0.01{\pm}0.039$ to $0.11{\pm}0.036$. This genetic opposition was distinctly higher for protein than for fat. Conclusion: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.245-251
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• 2015

Records of 490,767 cows collected from 1990 to 2012 by dairy herd milk test of National Agriculture Cooperative Federation The pedigree of dairy cattle were provided by Korea Animal Improvement Association. The data were used to analyze the longevity of dairy cows with the life traits such as days in milk, number of lactation, productive life, and life span. The data were also used to investigate genetic relationship of these longevity traits with profitability of dairy cows, including heritability and genetic correlation. The profitability was calculated with simulation of milk income and production costs for individual cows. Days in milk among the traits had -0.287, -0.572 and -0.536 of genetic correlation with number of lactations, productive life and lifespan, respectively. The heritabilities of life span, number of lactations, productive life, and days in milk were found to be 0.045, 0.047, 0.059 and 0.081, respectively. Genetic correlations of profit with productive life, number of lactations, and days in milk were identified as 0.072, 0.080, 0.098 and 0.101. These results suggested that days in milk was most desirable traits to represent longevity of Holstein dairy cattle. In general, since longevity and profitability were close genetic relationship each other, genetic improvement of longevity is necessary for better profitable cows.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.6
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• pp.784-790
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• 2014

In this study we aimed to evaluate the reduction in dimensionality of 20 linear type traits and more final score in 14,943 Holstein cows in Brazil using factor analysis, and indicate their relationship with longevity and 305 d first lactation milk production. Low partial correlations (-0.19 to 0.38), the medium to high Kaiser sampling mean (0.79) and the significance of the Bartlett sphericity test (p<0.001), indicated correlations between type traits and the suitability of these data for a factor analysis, after the elimination of seven traits. Two factors had autovalues greater than one. The first included width and height of posterior udder, udder texture, udder cleft, loin strength, bone quality and final score. The second included stature, top line, chest width, body depth, fore udder attachment, angularity and final score. The linear regression of the factors on several measures of longevity and 305 d milk production showed that selection considering only the first factor should lead to improvements in longevity and 305 milk production.

• Food Science of Animal Resources
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• v.25 no.3
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• pp.328-332
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• 2005

The effect of k-casein (k-CN) variant on milk production traits (milk yield, fat yield, protein yield, fat percentage and protein percentage) was estimated for 568 Holstein cows in the first lactation. The k-CN valiant were determined by PCR-RFLP (restriction fragment length polymorphism) technique at the DNA level. Single trait linear model was used for the statistical analysis of the data. Result of this study indicated that k-CN variant affected significantly milk yield (P<0.05) and protein yield (P<0.01). Animals with the BB variant produced 622kg milk more and had protein yield higher by 32kg compared with animals with the AA variant No associations between the k-CN variants and other milk production trait were found. Therefore, milk and protein yield may be improved through milk protein typing by increasing the frequencies of k-CN B variant in dairy cattle population. In cheese making, it will be also preferable to have milk with the B variant of k-CN, which gives higher yield having a better quality than the A variant milk.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.5
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• pp.607-614
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• 2016

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 $polynomials{\times}3$ 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.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.5
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• pp.636-642
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• 2018

Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

• Genomics & Informatics
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• v.13 no.4
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• pp.146-151
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• 2015

Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip ($h^2_G$). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.487-493
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• 2013

This experiment was conducted to investigate the possibility that milking speed traits can be improved by estimating their genetic parameters and to provide basic information when the goals for dairy cattle improvement are established. The amount of milk within the first three minutes (3MG) was 8.97 Kg and 57% of total milk was produced within 3 minutes, but it was lower than that of the recommended level (70%). The highest milk flow (HMF) and average milk flow (DMHG) in the main milking phase were 3.66kg/min and 2.43kg/min, respectively, which were lower than those of the recommended levels (4.0 5.0kg/min and 3.0 4.0kg/min), suggesting slower milking speed of domestic dairy cattle compared to that of foreign dairy cattle. The heritability estimates on the highest milk flow (HMF), maximum milk flow (HMG) in one minute and average milk flow (DMHG) in the main milking phase were 0.35, 0.31 and 0.29, respectively, which are suitable for the improvement of traits with medium heritability. The genetic correlation between total milk yields (MGG) and average milk flow (DMHG) in the main milking phase was 0.591, while the genetic correlations among milking speed traits including the highest milk flow (HMF), maximum milk flow (HMG) in one minute and average milk flow (DMHG) in the main milking phase were in the range of 0.889 0.997.