Hossain, K.B.;Takayanagi, S.;Miyake, T.;Moriya, K.;Bhuiyan, A.K.F.H.;Sasaki, Y.
Asian-Australasian Journal of Animal Sciences
/
v.15
no.5
/
pp.627-632
/
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.
Kim, E.T.;Lee, S.S.;Kim, H.J.;Song, J.Y.;Kim, C.H.;Ha, Jong-K.
Asian-Australasian Journal of Animal Sciences
/
v.25
no.5
/
pp.653-658
/
2012
This study was conducted to estimate the potential acid production value (PAPV) of major diets and to determine the relationship between dietary PAPV and dairy production traits. Estimation of PAPV of major cattle feeds was based on an in vitro technique, which determined the degree of Ca dissociation from $CaCO_3$. Data on feeds and production traits were collected on 744 multiparous lactating Holstein dairy cows from five different farms. Grains had high PAPV with variable protein sources and by-products. High PAPV feedstuffs had a higher total gas production and lower pH compared to those with low PAPV. Dietary PAPV had a positive correlation with intake of dry matter, NDF, ADF, milk yield and milk solid production but a negative correlation with milk protein and milk fat concentration. Current results indicate that dietary PAPV can be utilized in predicting dairy production traits.
Lee, Yun-Mi;Dang, Chang-Gwon;Alam, Mohammad Z.;Kim, You-Sam;Cho, Kwang-Hyeon;Park, Kyung-Do;Kim, Jong-Joo
Asian-Australasian Journal of Animal Sciences
/
v.33
no.3
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pp.382-389
/
2020
Objective: This study was conducted to test the efficiency of genomic selection for milk production traits in a Korean Holstein cattle population. Methods: A total of 506,481 milk production records from 293,855 animals (2,090 heads with single nucleotide polymorphism information) were used to estimate breeding value by single step best linear unbiased prediction. Results: The heritability estimates for milk, fat, and protein yields in the first parity were 0.28, 0.26, and 0.23, respectively. As the parity increased, the heritability decreased for all milk production traits. The estimated generation intervals of sire for the production of bulls (LSB) and that for the production of cows (LSC) were 7.9 and 8.1 years, respectively, and the estimated generation intervals of dams for the production of bulls (LDB) and cows (LDC) were 4.9 and 4.2 years, respectively. In the overall data set, the reliability of genomic estimated breeding value (GEBV) increased by 9% on average over that of estimated breeding value (EBV), and increased by 7% in cows with test records, about 4% in bulls with progeny records, and 13% in heifers without test records. The difference in the reliability between GEBV and EBV was especially significant for the data from young bulls, i.e. 17% on average for milk (39% vs 22%), fat (39% vs 22%), and protein (37% vs 22%) yields, respectively. When selected for the milk yield using GEBV, the genetic gain increased about 7.1% over the gain with the EBV in the cows with test records, and by 2.9% in bulls with progeny records, while the genetic gain increased by about 24.2% in heifers without test records and by 35% in young bulls without progeny records. Conclusion: More genetic gains can be expected through the use of GEBV than EBV, and genomic selection was more effective in the selection of young bulls and heifers without test records.
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.
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.
The present investigation was undertaken to study the milkability characteristics of Holstein cows. Out of 6,660 initial records 4,607 records were finally included in the analysis after deleting some records with an abnormal range of values for the traits considered. These 4,607 Holstein cows belonged to a total of 122 herds located in a province in Korea. The 'LactoCorder' instrument was used to electronically record the milkability traits at the milking parlor. A total of 19 traits were studied which were broadly classified into milk yield, milking speed, milking time and the electrical conductivity related traits. The SAS 9.1 statistical software was used to carry out analyses. The average maximum milk flow per minute was 3.21 kg/min, while the average milking speed during the main milking process (DMHG) had a mean value of 2.30 kg/min. The total milk yield was 14.14 kg, 62% of which was milked during the first three minutes of the milking. The average total milking time was 8.23 min. Among the three phases of the main milking process, the time of stable milk flow had the longest time (2.97 min) followed by the time at the decline phase (2.62 min). The average time taken to reach the plateau phase was 1.08 min, which can still be reduced further through improved managemental practices. Among milk yield traits, milk yield during the first two (MG2) and three (MG3) minutes of milking had high positive correlation with milking speed traits and negative correlations with almost all the milking time traits except time of incline in milk flow from 0.5 kg/min till the attainment of the plateau phase (tAN). Milking speed traits had negative correlations with total milking time, time at main milking process, time at plateau and with the time at decline. Since there was medium to high negative correlation between the milking speed and the time at plateau, there is a need for selection of cows which have intermediate milking speed so that it could require less milking time and also the optimum (higher and longer) plateau time. Proper pre-stimulation and avoiding over milking will help in further reducing the milking time and thus will add to the net profit of the farmer.
Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.
Lactose synthase catalyses the formation of lactose which is the major osmole of bovine milk and regulates the milk volume. Alpha-lactalbumin (${\alpha}$-LA) is involved in the synthesis of lactose synthase in the mammary gland. Therefore ${\alpha}$-LA is regarded as a plausible candidate gene for the milk yield trait. To determine whether ${\alpha}$-LA is associated with milk performance traits, 1,028 Chinese Holstein cows were used to detect polymorphisms in the ${\alpha}$-LA by means of single-strand conformation polymorphism (SSCP). Two nucleotide transitions were identified in the 5'flanking region and intron 3 of ${\alpha}$-LA. Associations of such polymorphisms with five milk performance traits were analyzed using a general linear model procedure. No significant associations were observed between these polymorphisms and the five milk performance traits (p>0.05). RH mapping placed ${\alpha}$-LA on BTA5q21, linked most closely to markers U63110, CC537786 and L10347 (LOD>8.3), which is far distant from the region of the quantitative trait locus (QTL) on bovine chromosome 5 for variation in the milk yield trait. In summary, based on our findings, we eliminated these SNPs from having an effect on milk performance traits.
Associations were analysed between polymorphisms localized in intron 3 of the growth hormone gene (GH-MspI) and milk production traits of 543 China Holstein cows. A PCR-RFLP method was used for identification of genotypes. The following frequencies of genotypes and alleles were found: 0.77, 0.21 and 0.02 for +/+, +/- and -/-, respectively, and 0.87 and 0.13 for $GH^+$ and $GH^-$, respectively. Significant differences between herds were observed in the frequencies of both genotypes and alleles. The results of least squares analysis showed that in all three lactation phases the GH +/+ cows yielded most milk (p<0.01 for lactation I and p<0.05 for lactations II and III), whereas +/- cows showed higher milk fat content than +/+ individuals (p<0.05 for lactation I and II, and p<0.01 for lactation III). The +/+ cows yielded more fat than +/- individuals (p<0.01 only in lactation I). The +/+ cows yielded more milk protein than +/- individuals (p<0.01 for lactation I, II, and III). The +/+ cows produced milk of higher protein content than that of +/- individuals (p<0.05 only in lactation II). Based on these results, we conclude that the +/+ of GH locus should be the favored genotype in China Holstein cow breeds for use in marker-assisted selection programmes.
Objective: The present study was aimed primarily for estimating various genetic parameters (heritability, genetic correlations) of reproduction (age at first calving [AFC], first service period [FSP]); production (first lactation milk, solid-not fat, and fat yield) and lifetime traits (lifetime milk yield, productive life [PL], herd life [HL]) in Tharparkar cattle to check the association of reproduction traits with lifetime traits through two different methods (Frequentist and Bayesian) for comparative purpose. Methods: Animal breeding data of Tharparkar cattle (n = 964) collected from Livestock farm unit of ICAR-NDRI Karnal for the period 1990 through 2019 were analyzed using a Frequentist least squares maximum likelihood method (LSML; Harvey, 1990) and a multi-trait Bayesian-Gibbs sampler approach (MTGSAM) for genetic correlations estimation of all the traits. Estimated breeding values of sires was obtained by BLUP and Bayesian analysis for the production traits. Results: Heritability estimates of most of the traits were medium to high with the LSML (0.20±0.44 to 0.49±0.71) and Bayesian approach (0.24±0.009 to 0.61±0.017), respectively. However, more reliable estimates were obtained using the Bayesian technique. A higher heritability estimate was obtained for AFC (0.61±0.017) followed by first lactation fat yield, first lactation solid-not fat yield, FSP, first lactation milk yield (FLMY), PL (0.60±0.013, 0.60±0.006, 0.57±0.024, 0.57±0.020, 0.42±0.025); while a lower estimate for HL (0.38±0.034) by MTGSAM approach. Genetic and phenotypic correlations were negative for AFC-PL, AFC-HL, FSP-PL, and FSP-HL (-0.59±0.19, -0.59±0.24, -0.38±0.101 and -0.34±0.076) by the multi-trait Bayesian analysis. Conclusion: Breed and traits of economic importance are important for selection decisions to ensure genetic gain in cattle breeding programs. Favourable genetic and phenotypic correlations of AFC with production and lifetime traits compared to that of FSP indicated better scope of AFC for indirect selection of life-time traits at an early age. This also indicated that the present Tharparkar cattle herd had sufficient genetic diversity through the selection of AFC for the improvement of first lactation production and lifetime traits.
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