• Asian-Australasian Journal of Animal Sciences
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• v.16 no.10
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• pp.1397-1401
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• 2003

The aim of this study was to determine genotypes of four genetic markers and to investigate their association with milk production traits in Brown Swiss cattle imported to Slovakia. The bovine $\kappa$-casein, $\beta$-lactoglobulin, growth hormone and prolactin genotypes of 107 cows were identified by polymerase chain reaction. Effects all four genetic markers on milk, fat, protein and lactose yields and fat, protein and lactose percentage were estimated from a data set of 249 lactations. The frequency of desirable B allele of $\kappa$-casein gene to milk production was 0.46, alleles A of $\beta$-lactoglobulin gene was 0.55, allele and L of growth hormone gene was 0.45 and allele A and B of bovine prolactin gene were 0.61 and 0.39. The results of milk production obtained in our work showed that BB genotypes of $\kappa$-CN gene, AA genotypes of $\beta$-LG gene, LL genotypes of bGH gene were significantly associated with better milk production traits, mainly about the fat content. Association of a bovine prolactin genotypes with milk production were not found.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1252-1256
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• 2006

This study estimated the effects of parity (1-3) and stage of lactation (early, mid and late) on daily milk yield (DMY), somatic cell score (SCS), milk urea nitrogen (MUN), blood glucose, and immunoglobulin G (IgG), their heritabilities and genetic correlations between them in Holsteins (n = 200). Means and standard deviations of DMY, SCS, MUN, blood glucose, and IgG in the experimental herd were $23.35{\pm}7.75kg$, $3.81{\pm}2.00$, $13.99{\pm}5.68mg/dl$, $44.91{\pm}13.12mg/dl$, and $30.36{\pm}6.72mg/ml$, respectively. DMY was the lowest in first parity, and in late lactation. SCS increased with parity; however, it was lowest in mid-lactation. MUN was lowest in first parity, and no difference was noted across stage of lactation. Blood glucose was similar between parities, however the highest blood glucose was observed during mid lactation. IgG level was significantly different between first and second parity; however, stage of lactation did not affect its level. Heritability of DMY was 0.16. Its genetic correlations with SCS and with blood glucose were -0.67 and 0.98, respectively. Heritability of SCS was 0.15. Genetic correlations of SCS with MUN, glucose, and IgG were -0.72, -0.59, and 0.68, respectively. Heritability of MUN was estimated to be 0.39 and had a genetic correlation of -0.35 with IgG. Heritabilities of blood glucose and IgG were 0.21 and 0.33, respectively. This study suggested that MUN, blood glucose and IgG could be considered important traits in future dairy selection programs to improve milk yield and its quality with better animal health and welfare. However, further studies are necessary involving more records to clarify the relationship between metabolic and immunological traits with DMY and its quality.

• Journal of Animal Science and Technology
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• v.48 no.4
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• pp.487-492
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• 2006

This study estimated characteristics and genetic parameters for milking traits in Holstein dairy cattle. Daily records (12,561) were available from a hundred fifty four lactating cows with sixty six sires at National Livestock Research Institute from November, 2005 to April, 2006. The cows were fed same rations, and were milked twice daily using milking parlour equipped with Alpro-system?? to collect milking records automatically. The experimental cows have averaged 1.9 parities, 139.7 days in milk, and 13kg milk yield per milking. Average milk flow was 64% of peak milk flow. Milking duration, peak milk flow, average milk flow, and milk yield per milking were 5.57±1.67 minutes, 3.58±0.79kg/minute, 2.28±0.51kg/minute, and 13.02±4.09kg, respectively. All traits in the morning milking were higher than those of in the evening milking, and were also increased with parity. Heritabilities for milking duration, peak and average milk flow, and milk yield per time were 0.49, 0.70 0.58 and 0.36, respectively. The genetic correlations of milking duration with peak milk flow, average milk flow, and milk yield per time were 0.48, 0.54, and 0.41, respectively. The correlations of milk yield per milking with peak milk flow and average milk flow were 0.23 and 0.30, respectively. In conclusion, milk flow was increased with milk yield; however milk flow was opposite relationship with milk duration. Further studies are not only necessary to warranty genetic parameters, but pre-installation of automatic recording system to collect daily milking record is also necessary.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.1
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• pp.7-10
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• 2002

The breeding data relating to Hariana herd spread over 18 years (1979-96) were analysed to estimate genetic, phenotypic and environmental changes in characters of economic importance which might have taken place during the several years of selective breeding practiced in the herd. The average genetic changes in a given character were estimated by four methods. The phenotypic trends observed for different economic traits were not significant. On changing the method of estimation, magnitude and direction of genetic trends changed. Comparison of estimates of genetic trends by different methods showed that adjustments for biases due to non-random allotment of dams with respect to their age and merit suggested by Powell and Freeman (1974) were useful for increasing the precision of the estimates. Hence, this method was found to be the best method for estimation of genetic trends. The estimate of genetic trends by this method were 4.03${\pm}$6.21 days, 3.24${\pm}$5.33 kg, 0.15${\pm}$0.43 days, 0.09${\pm}$0.59 days, 0.01${\pm}$0.02 kg and 0.01${\pm}$0.01 kg for age at first calving, first lactation milk yield, first lactation length, first calving interval, first lactation milk yield per day lactation length and first lactation milk yield per day of calving interval, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.12
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• pp.1693-1702
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• 2009

Economic values of 14 production and functional traits for two Slovak dairy sheep breeds (Improved Valachian and Tsigai) were calculated. Semi-extensive production systems with one lambing per year were simulated using a bio-economic deterministic computer model. The marginal economic value of a trait was defined as the partial derivative of the profit function with respect to that trait. The relative economic value expressed the percentage proportion of standardized economic value (marginal economic value${\times}$genetic standard deviation) of a trait in the sum of the absolute values of the standardized economic values over all traits. Milk yield was of highest relative importance (26% and 32% in Improved Valachian and Tsigai) followed by productive lifetime and conception rate of ewes (16% and 15% in Improved Valachian and Tsigai, in both traits). Conception rate of female lambs and litter size had nearly the same relative economic importance in both breeds (9% to 11%). Survival rate of lambs at lambing and till weaning reached slightly lower economic values (4% to 7%). The economic importance of all remaining traits was less than 4%.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.7
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• pp.923-930
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• 2009

This study was conducted to compare three models: two random regression models with and without considering heterogeneity in the residual variances and a lactation model (LM) for evaluating the genetic ability of Holstein cows in Korea. Two datasets were prepared for this study. To apply the test-day random regression model, 94,390 test-day records were prepared from 15,263 cows. The second data set consisted of 14,704 lactation records covering milk production over 305 days. Raw milk yield and composition data were collected from 1998 to 2002 by the National Agricultural Cooperative Federation' dairy cattle improvement center by way of its milk testing program, which is nationally based. The pedigree information for this analysis was collected by the Korean Animal Improvement Association. The random regression models (RRMs) are single-trait animal models that consider each lactation record as an independent trait. Estimates of covariance were assumed to be different ones. In order to consider heterogeneity of residual variance in the analysis, test-days were classified into 29 classes. By considering heterogeneity of residual variance, variation for lactation performance in the early lactation classes was higher than during the middle classes and variance was lower in the late lactation classes than in the other two classes. This may be due to feeding management system and physiological properties of Holstein cows in Korea. Over classes e6 to e26 (covering 61 to 270 DIM), there was little change in residual variance, suggesting that a model with homogeneity of variance be used restricting the data to these days only. Estimates of heritability for milk yield ranged from 0.154 to 0.455, for which the estimates were variable depending on different lactation periods. Most of the heritabilities for milk yield using the RRM were higher than in the lactation model, and the estimate of genetic variance of milk yield was lower in the late lactation period than in the early or middle periods.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1387-1399
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• 2020

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.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.687-693
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• 2015

Using 378,086 lactation records on dairy cattle, environmental factors influencing acetone and ${\beta}$-hydroxybutyrate acid contents in raw milk which are used as ketosis diagnosis indicator traits were analyzed in this experiment. Significance testing was conducted on farm, lactation stage, parity, milking time and month of age by traits. The results of this experiment indicated that there was a highly significant (p < 0.01) difference in all factors and lactation stage was the most significant factor. Linear regression coefficients of month of age on daily milk yields and acetone and ${\beta}$-hydroxybutyrate acid contents were all positive, while their quadratic linear regression coefficients were negative. Least square means for milk yield at second lactation stage (36~65 days) was 19.06kg which was higher than that of late lactation stage by 6.51kg. Least square means for acetone and ${\beta}$-hydroxybutyrate acid contents at the first lactation stage (5~35 days) were highest (0.1929mM/L and 0.0742mM/L, respectively), and there was a trend that they decreased as the milking progressed, but increased slightly at the late stage of milking. However, least square means for acetone and ${\beta}$-hydroxybutyrate acid contents at the first parity were 0.1414mM/L and 0.0522mM/L, respectively, which were higher than the average milk yield after the second parity. Least square means for acetone and ${\beta}$-hydroxybutyrate acid contents of PM milk yield (0.1372mM/L and 0.0534mM/L, respectively) were higher than those of AM milk yield collectively.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.9
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• pp.1250-1256
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• 2002

A novel fine-mapping method exploiting linkage disequilibrium (LD) was applied to better refine the quantitative trait loci (QTL) positions for milk production traits on bovine chromosome 14 in the pedigree comprising 22 paternal half-sib families of a Black-and-White Holstein-Friesian grand-daughter design in the Netherlands for a total of 1,034 sons. The chromosome map was constructed with the 31 genetic markers spanning 90 Kosambi cM with the average inter-marker distance of 3.5 cM. The linkage analyses, in which the effects of sire QTL alleles were assumed random and the random factor of the QTL allelic effects was incorporated into the Animal Model, found the QTL for milk, fat, and protein yield and fat and protein % with the Lod scores of 10.9, 2.3, 6.0, 25.4 and 3.2, respectively. The joint analyses including LD information by use of multi-marker haplotypes highly increased the evidence of the QTL (Lod scores were 25.1, 20.9, 11.0, 85.7 and 17.4 for the corresponding traits, respectively). The joint analyses including DGAT markers in the defined haplotypes again increased the QTL evidence and the most likely QTL positions for the five traits coincided with the position of the DGAT gene, supporting the hypothesis of the direct causal involvement of the DGAT gene. This study strongly indicates that the exploitation of LD information will allow additional gains of power and precision in finding and localising QTL of interest in livestock species, on the condition of high marker density around the QTL region.