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1.
Genetic parameters were estimated for loge somatic cell count (LSCC) for the first three lactations of 31 236 Holstein/Friesian cows with 308 534, 236 277 and 206 729 test day yields in parities 1, 2 and 3, respectively. An animal random regression model was employed in the analyses using Gibbs sampling with each parity regarded as different traits. Linear and quadratic functions were fitted for the animal and permanent environmental effects respectively, using orthogonal polynomials. Daily heritabilities increased with days in milk (DIM) and averaged about 0.07 in all three parities. This increase in heritabilities with DIM was due to an increase in genetic variance and decreases in both permanent and residual environmental variances with DIM. Environmental effects have a large influence on LSCC in early lactation in all three parities. Within lactation, genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. However, this decrease was slowest in parity one and greatest in parity three. The lowest correlation within lactation was 0.10 between DIM 7 and 305 in parity 3. Across lactations, genetic correlations were highest between parities 2 and 3, intermediate between 1 and 3, and lowest between 1 and 2. The genetic correlations computed for completed lactations were 0.69, 0.79 and 0.98 between parities 1 and 2, 1 and 3, and 2 and 3, respectively. Corresponding phenotypic correlations between parities were 0.38, 0.31 and 0.52, respectively. A test day model, accounting for these variations in heritabilities and genetic correlations, should result in a more accurate evaluation.  相似文献   

2.
A multiplicative random regression (M-RRM) test-day (TD) model was used to analyse daily milk yields from all available parities of German and Austrian Simmental dairy cattle. The method to account for heterogeneous variance (HV) was based on the multiplicative mixed model approach of Meuwissen. The variance model for the heterogeneity parameters included a fixed region x year x month x parity effect and a random herd x test-month effect with a within-herd first-order autocorrelation between test-months. Acceleration of variance model solutions after each multiplicative model cycle enabled fast convergence of adjustment factors and reduced total computing time significantly. Maximum Likelihood estimation of within-strata residual variances was enhanced by inclusion of approximated information on loss in degrees of freedom due to estimation of location parameters. This improved heterogeneity estimates for very small herds. The multiplicative model was compared with a model that assumed homogeneous variance. Re-estimated genetic variances, based on Mendelian sampling deviations, were homogeneous for the M-RRM TD model but heterogeneous for the homogeneous random regression TD model. Accounting for HV had large effect on cow ranking but moderate effect on bull ranking.  相似文献   

3.
The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents predicted by mid‐infrared spectrometry for first‐, second‐ and third‐parity Holstein cows. Edited data included records collected in the Walloon region of Belgium from 37 768 cows in parity 1, 22 566 cows in parity 2 and 8221 in parity 3. A total of 69 (23 traits for three parities) single‐trait random regression animal test‐day models were run. Approximate genetic correlations among traits were inferred from pairwise regressions among estimated breeding values of cow having observations. Heritability and genetic correlation estimates from this study reflected the origins of FA: de novo synthetized or originating from the diet and the body fat mobilization. Averaged daily heritabilities of FA contents in milk ranged between 0.18 and 0.47. Average daily genetic correlations (averaged across days in milk and parities) among groups and individual FA contents in milk ranged between 0.31 and 0.99. The genetic variability of FAs in combination with the moderate to high heritabilities indicated that FA contents in milk could be changed by genetic selection; however, desirable direction of change in these traits remains unclear and should be defined with respect to all issues of importance related to milk FA.  相似文献   

4.
The first three lactation curves of the Japanese Holstein cows were analyzed using a random regression (RR) test-day model with a cubic Legendre polynomial fitted to each of the three parities. The first three eigenvectors of the additive genetic RR covariance matrix explained 77.8, 10.9, and 4.2% of the total variance of the three parities and are associated mainly with the level of milk yield, the linear increase, and the concave curve, respectively. On a lactational basis, as the parity increases, the contribution of the first eigenvector to a lactational variation decreases whereas the contribution of the second eigenvector increases sharply. This means that the impact of the first eigenvector on the level of milk production decreases across parity whereas the effect of the second eigenvector on the shape of the lactation curve increases across parity. The first lactation curve was the most persistent, followed by the second and the third lactation. Persistency and days to reach peak yield decrease as the parity increases (45, 40, and 36 days for the first three parities). Daily heritabilities within lactation were lower for the first parity than for the second or the third parity. The first three lactation curves possess distinctive genetic characteristics that merit consideration when combining the proofs of the first three lactations to select for lifetime production. Within- and between-parity genetic correlations between the constant and the linear RR coefficients were all positive, suggesting that raising the level of milk production in one parity would increase the linear slope in all parities, thus improving persistency. Within- and between-parity genetic correlations between the constant and the quadratic RR coefficients were all negative, implying that increasing the level of production in one parity would deepen and/or widen the concave curve in all parities, thus decreasing persistency. The linear and quadratic RR coefficients were negatively correlated within or between parities and thus have antagonistic effects on persistency.  相似文献   

5.
Heat stress in tropical regions is a major cause that strongly negatively affects to milk production in dairy cattle. Genetic selection for dairy heat tolerance is powerful technique to improve genetic performance. Therefore, the current study aimed to estimate genetic parameters and investigate the threshold point of heat stress for milk yield. Data included 52 701 test‐day milk yield records for the first parity from 6247 Thai Holstein dairy cattle, covering the period 1990 to 2007. The random regression test day model with EM‐REML was used to estimate variance components, genetic parameters and milk production loss. A decline in milk production was found when temperature and humidity index (THI) exceeded a threshold of 74, also it was associated with the high percentage of Holstein genetics. All variance component estimates increased with THI. The estimate of heritability of test‐day milk yield was 0.231. Dominance variance as a proportion to additive variance (0.035) indicated that non‐additive effects might not be of concern for milk genetics studies in Thai Holstein cattle. Correlations between genetic and permanent environmental effects, for regular conditions and due to heat stress, were ? 0.223 and ? 0.521, respectively. The heritability and genetic correlations from this study show that simultaneous selection for milk production and heat tolerance is possible.  相似文献   

6.
We estimated genetic parameters for number born alive (NBA) from the first to the seventh parities in Landrace and Large White pigs using three models. Analyzing 55,160 farrowing records for 12,677 Landrace dams and 43,839 for 10,405 Large White dams, we used a single‐trait animal model to estimate the heritability of NBA at each parity and a two‐trait animal model and a single‐trait random regression model to estimate the genetic correlations between parities. Heritability estimates of NBA at each parity ranged from 0.08 to 0.13 for Landrace and from 0.05 to 0.16 for Large White. Estimated genetic correlations between parities in all cases were positive. Genetic correlations between the first and second parities were slightly lower than those between other neighboring parities. Genetic correlations between more distant parities tended to be lower, in some cases <0.8. The results indicate the necessity to investigate the applicability of evaluating NBA at different parities as different traits (e.g., the first and later parities), although a repeatability model might still be reasonable.  相似文献   

7.
This study aimed to analyse genetic background of variation in reproductive performance between parities of a sow and to investigate selection strategies to change the “parity curve”. Total number born (TNB) recorded in Large White sows was provided by Topigs Norsvin. Analysis with basic (BM) and random regression (RRM) models was done in ASReml 4.1. The BM included only a fixed “parity curve”, while RRM included 3rd order polynomials for additive genetic and permanent sow effects. Parameters from RRM were used in simulations in SelAction 2.1. Based on Akaike information criterion, RRM was a better model for TNB data. Genetic variance and heritability estimates of TNB from BM and RRM were increasing with parity from parity 2. Genetically, parity 1 is the most different from parities 7 to 10, whereas most similar to parities 2 and 3. This indicates presence of genetic variation to change the “parity curve”. Based on simulations, the selection to increase litter size in parity 1 only increases TNB in all parities, but does not change the observed shape of “parity curve”, whereas selection for increased TNB in parity 1 and reduced TNB in parity 5 decreases differences between parities, but also reduces overall TNB in all parities. Changing the “parity curve” will be difficult as the genetic and phenotypic relationships between the parities are hard to overcome even when selecting for one parity.  相似文献   

8.
The breeding goal for Simmental cattle is derived for intensively managed dairy farms. Its suitability for extensive farms was addressed by analysing possible genotype by environment interaction (G × E) between the management levels for first lactation milk yield traits. A first analysis was performed with the data collected from 300 000 purebred daughters of 278 second crop bulls born in Bavaria in 1993 and 1994. The farms were classified by herd‐year‐effect, using the sum of fat and protein yields into two levels of management, either with 33 or 10% quantiles, corresponding to approximately 100 000 cows and 30 000 cows, respectively. The comparison was based on ‘daughter yield’ deviations (DYD). Correlations between DYD of extensive and intensive environments were 0.90, 0.91 and 0.87 for milk, fat and protein yield (kg) for 33% quantiles, respectively. Corresponding correlations for 10% quantiles were 0.85, 0.83 and 0.77. Despite high correlations, 50 out of 149 sires showed significant differences between DYD in different environments. Bulls with higher DYD for milk yield on intensive farms were superior in all environments. For the second analysis extensive and intensive farms in northern and southern Bavaria were chosen at random. Approximately 20 000 cows in each management class were used for the estimation of genetic parameters. In both regions phenotypic and additive‐genetic variances were higher in the intensively managed herds. Likewise heritabilities were higher for fat and protein yield, but not for milk where higher heritabilities were observed in 33% quantiles. Genetic correlations between extensive and intensive environments were 0.97 and above (33% quantiles). Ten per cent quantiles led to lower genetic correlations (0.90–0.95). Although no serious re‐ranking effects of sires were evident, the scale effect and the differences in genetic parameters should be taken into consideration in practical breeding.  相似文献   

9.
本研究旨在应用随机回归测定日模型对奶牛生产性状进行遗传评估。收集河南省内17个牧场2008年1月2017年5月共16 335头奶牛头胎174 634条生产性能记录,建立筛选标准对数据进行质控。遗传评估采用随机回归模型,场-测定日为固定效应,以固定回归拟合产犊月龄效应,随机效应包括加性遗传和永久环境效应。固定和随机回归均采用4阶Legendre多项式。结果表明:中国荷斯坦牛头胎测定日产奶量、乳脂率、乳蛋白率、体细胞评分总遗传力分别为0.144 1、0.289 1、0.373 2和0.089 8。本研究为区域性中国荷斯坦牛的遗传评估平台建设和育种规划制定奠定基础。  相似文献   

10.
Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences. Estimated proportion of TD records originated from cows infected with mastitis was 0.66 in DIM from 5 to 15 and averaged 0.2 in the remaining part of lactation. Data from healthy and mastitic cows exhibited markedly different distributions, with respect to both average value and the variance, across all parts of lactation. Heterogeneity of distributions for infected cows was also apparent in different DIM intervals. Cows with mastitis were characterized by smaller milk yield (down to -5 kg) and larger F:P (up to 0.13) and SCS (up to 1.3) compared with healthy contemporaries. Differences in averages between healthy and infected cows for F:P were the most profound at the beginning of lactation, when a dairy cow suffers the strongest energy deficit and is therefore more prone to mammary infection. Residual variances for data from infected cows were substantially larger than for the other mixture components. Fat-to-protein ratio had a significant genetic component, with estimates of heritability that were larger or comparable with milk yield, and was not strongly correlated with milk and SCS on both genetic and environmental scales. Daily milk, F:P and SCS are easily available from milk-recording data for most breeding schemes in dairy cattle. Fat-to-protein ratio can potentially be a valuable addition to SCS and milk yield as an indicator trait for selection against mastitis.  相似文献   

11.
Multiple‐trait (MT) finite mixture random regression (MIX) model was applied using Bayesian methods to first lactation test‐day (TD) milk yield and somatic cell score (SCS) of Canadian Holsteins, allowing for heterogeneity of distributions with respect to days in milk (DIM) in lactation. The assumption was that the associations between patterns of variation in these traits and mastitis would allow revealing the hidden structure in the data distribution because of unknown health status of cows. The MIX model assumed separate means and residual co‐variance structures for two components in four intervals of lactation, in addition to fitting the fixed effect of herd‐test‐day, and fixed and random regressions with Legendre polynomials. Results indicated that the mixture model was superior to standard MT model, as supported by the Bayes factor. Approximately 20% of TD records were classified as originated from cows with a putative, sub‐clinical form of mastitis. The proportion of records from mastitic cows was the largest at the beginning of lactation. The MIX model exhibited different distributions of data from healthy and infected cows in different parts of lactation. Records from sick cows were characterized by larger (smaller) means for SCS (milk) and larger variances. Residual, and daily genetic and environmental correlations between milk and SCS were smaller from the MIX model when compared with MT estimates. Heritabilities of both traits differed significantly among records from healthy, sick and MT model estimates. Both models fitted milk records from healthy cows relatively well. The ability of the MT model in handling SCS records, measured by model residuals, was low, but improved substantially, however, where the data were allowed to be separated into two components in the MIX parameterization. Correlations between estimated breeding values (EBV) for sires from both models were very high for cumulative milk yield (>0.99) and slightly lower (0.95 in the interval from 5 to 45 DIM) for daily SCS. EBV for SCS from MT and MIX models were weakly correlated with posterior probability of sub‐clinical mastitis on the phenotypic scale.  相似文献   

12.
To analyze how infection with Mycobacterium avium subsp. paratuberculosis (MAP) affects the shape of lactation curves, a three-level hierarchical test-day model was set up with fat-corrected test-day milk yield (FCTM) as response. Milk samples from 6955 cows in 108 Danish dairy herds were tested with ELISA to detect antibodies against MAP. Optical densities (ODs) recorded on a continuous scale were standardized according to parity and stage of lactation. In addition to standardized ODs (stOD), seven fixed covariates, quadratic terms and first-order interactions were included in the model. Cow and cow nested in herd were included as random effects. Cows of first, second and higher parities were analyzed separately. The lactation curves after peak yield were significantly less persistent in young infected cows, where an increase of one stOD unit was associated with a depression of the milk yield per day through day 305 of 3.7 kg FCTM in first parity and 2.7 kg FCTM in second parity. In second-parity cows, the lactation curve also was both depressed through the entire lactation and more steep after 60 days in milk (DIM). In third and older parities, a significant effect of the quadratic term of stOD indicated exponentially increased losses with increased ODs.  相似文献   

13.
本研究通过对规模化牧场测定日数据进行分析,旨在估计不同地区305 d校正产奶量对应泌乳天数(DIM)的校正系数与胎次校正系数。利用Wood(不完全伽玛)模型对来自不同温度带9个参考群11 749头荷斯坦奶牛2010－2020年间的683 160条测定日产奶量拟合泌乳曲线,估计泌乳曲线参数,计算头胎牛和经产牛1~305 d泌乳天数对应的校正系数,分别分析参考群和验证群305 d校正产奶量和305 d实际累积奶量的差异;利用SAS 9.2中混合线性模型对1~6胎至少有前5个胎记录的牛估计305 d奶量的胎次效应值,并计算1~6胎各胎次的乘法校正系数;比较传统系数和新系数校正结果的差异。结果表明:①参考群头胎牛和经产牛中,泌乳曲线方程的拟合度R2范围分别为0.4593~0.4913和0.5796~0.6341,泌乳高峰日分别为79~85和53 d,泌乳高峰奶量分别为33.1~34.4和46.0~48.6 kg;②对于参考群,头胎牛和经产牛校正系数分别在泌乳≥90 d和泌乳≥30 d基本趋于一致,头胎牛和经产牛泌乳≥60 d的305 d校正产奶量均趋近于305 d实际累积奶量,奶量差值分别在100和200 kg以内;③对于验证群的305 d校正产奶量,头胎牛泌乳≥150 d和经产牛泌乳≥180 d的泌乳天数校正系数适用性更佳,305 d校正产奶量与305 d实际累积奶量比值高于79%;④1~6胎的胎次校正系数分别为1.2121、1.0380、1.0063、1.0000、1.0220和1.0290;⑤与传统系数相比,新泌乳天数校正系数校正效果更好,头胎牛和经产牛新系数校正的305 d奶量较305 d实际累积奶量相差分别在900和700 kg以内;利用新胎次校正系数,2~4胎产奶量可较为准确地校正到5胎成年当量。本研究结果表明,定期更新305 d校正产奶量的泌乳天数与胎次校正系数,便于准确地将不同泌乳天数、不同胎次状态下泌乳牛的产奶量调整到同一基准上,从而更好地比较奶牛个体泌乳性能的高低,为牧场管理提供参考依据。  相似文献   

14.
The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo’s test‐day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test‐day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from ?0.07 (second with eighth week) to ?0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes.  相似文献   

15.
The aim of the study was to assess crossbreeding effects for 305‐day milk, fat, and protein yield and calving interval (CI) in Irish dairy cows (parities 1 to 5) calving in the spring from 2002 to 2006. Data included 188 927 records for production traits and 157 117 records for CI. The proportion of genes from North American Holstein Friesian (HO), Friesian (FR), Jersey (JE) and Montbéliarde (MO) breeds, and coefficients of expected heterosis for HO×FR, HO×JE and HO×MO crosses were calculated from the breed composition of cows’ parents. The model used to assess crossbreeding effects accounted for contemporary group, age at calving within parity, linear regression on gene proportions for FR, JE and MO, and linear regression on coefficients of expected heterosis for HO×FR, HO×JE and HO×MO, as fixed effects, and additive genetic, permanent environmental and residual as random. Breed effects for production traits were in favour of HO, while for CI were in favour of breeds other than HO. The highest heterosis estimates for production were for HO×JE, with first‐generation crosses yielding 477 kg more milk, 25.3 kg more fat, and 17.4 kg more protein than the average of the parental breeds. The highest estimate for CI was for HO×MO, with first‐generation crosses showing 10.2 days less CI than the average of the parental breeds. Results from this study indicate breed differences and specific heterosis effects for milk yield traits and fertility exist in Irish dairy population.  相似文献   

16.
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17.
The aims of this study were to estimate, simultaneously, the genetic parameters of test‐day milk fat‐to‐protein ratio (FPR), test‐day milk yield (MY), and days‐open (DO) in the first two lactations of Thai Holsteins. A total of 76 194 test‐day production records collected from 8874 cows with 8674 DO records between 2001 and 2011 from different lactations were treated as separated traits. The estimates of heritability for test‐day FPR in the first lactation showed an increasing trend, whereas the estimates in the second lactation showed a U‐shape trend. Genetic correlations for FPR‐DO and MY‐DO showed a decreasing trend along days in milk (DIM) in both lactations, whereas genetic correlations for FPR‐MY increased along DIM in the first lactation but decreased in the second lactation. Genetic correlations of FPR between consecutive DIM were moderate to high, which showed the effectiveness of simultaneous analyses. Selection of FPR in the early stage has no adverse effect on MY and DO for the first lactation but has a negative effect on MY and positive effect on DO for the second lactation. This study showed that genetic improvement of the energy balance using FPR, MY and DO with multi‐trait test day model could be applied in a Thailand dairy cattle breeding program.  相似文献   

18.
Heritabilities and genetic correlations for milk production traits were estimated from first‐parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Legm) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits.  相似文献   

19.
Repeated records of number of services per conception (NSC) were collected on 607 Japanese Black cows. Data were analysed by random regression (RRM) and multiple trait (MTM) models, considering NSC in each parity as a separate trait. The chosen RRM included additive genetic and permanent environmental effects fitted with a third‐order Legendre polynomials of parity. Heritabilities (h2) estimated by RRM decreased along the NSC trajectory from 0.15 in the first parity to 0.04 in the sixth parity and then increased up to 0.22 in the 10th parity. The corresponding estimates obtained by MTM ranged between 0.04 in parity 9 and 0.13 in parity 1. Permanent environmental proportions (p2) of the total phenotypic variance estimated by RRM showed similar pattern and magnitude to those of h2 estimated by the same method. On the contrary, the p2 estimated by MTM ranged between 0.04 in the first parity and 0.11 in the 10th parity. Additive genetic (rG), permanent environmental (rP) and phenotypic (rPH) correlations were also estimated. The values estimated by RRM between adjacent parities were higher than those of parities far apart. The corresponding values estimated by MTM were lower than those estimated by RRM with no certain trend. The results indicated that NSC in heifers is more heritable than NSC in cows with different parities. Reproductive traits are economically important traits and hence, they should be considered in breeding goals.  相似文献   

20.
Using spline functions (segmented polynomials) in regression models requires the knowledge of the location of the knots. Knots are the points at which independent linear segments are connected. Optimal positions of knots for linear splines of different orders were determined in this study for different scenarios, using existing estimates of covariance functions and an optimization algorithm. The traits considered were test‐day milk, fat and protein yields, and somatic cell score (SCS) in the first three lactations of Canadian Holsteins. Two ranges of days in milk (from 5 to 305 and from 5 to 365) were taken into account. In addition, four different populations of Holstein cows, from Australia, Canada, Italy and New Zealand, were examined with respect to first lactation (305 days) milk only. The estimates of genetic and permanent environmental covariance functions were based on single‐ and multiple‐trait test‐day models, with Legendre polynomials of order 4 as random regressions. A differential evolution algorithm was applied to find the best location of knots for splines of orders 4 to 7 and the criterion for optimization was the goodness‐of‐fit of the spline covariance function. Results indicated that the optimal position of knots for linear splines differed between genetic and permanent environmental effects, as well as between traits and lactations. Different populations also exhibited different patterns of optimal knot locations. With linear splines, different positions of knots should therefore be used for different effects and traits in random regression test‐day models when analysing milk production traits.  相似文献   

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