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1.
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   

2.
Using a large‐scale data set that included first lactation test day records from 1975 to 2000 for Japanese Holsteins, genetic parameters for milk yield were estimated by using random regression (RR) test‐day models (TDM) with heterogeneous and homogeneous residual variances. It is necessary for the RR‐TDM to include a function that explains the shape of the lactation curve. The RR‐TDM with the LW curve, which combined Wilmink's curve and a Legendre polynomial, was used for fitting the model for milk yield. In recent years, increases in residual variance have been noted for Japanese dairy cattle. Thus, three kinds of heterogeneous residual variance over the calving year were considered: H1, H2 and HG. Linear and quadratic exponential functions for the calving year were used in H1 and H2, respectively. Residual variance of HG was divided into five groups according to calving year. Homogeneous residual variance was HO. All heterogeneous residual variances increased with calving year in an almost linear fashion. Residual variance increased over the study period. However, there is no need to consider heterogeneous residual variances in genetic evaluations, because the heterogeneity of residual variance over the years did not affect the ranking of top sires and cows.  相似文献   

3.
To obtain a sport horse that excels in the highest levels of competition, breeders must take into account certain genetic and environmental factors that could influence the sport horse's performance, such as the rider–horse interaction (RHI). The main aim of this study was to describe this interaction in a genetic model by modelling it in relation to the horse's age. A total of 31,129 sport results from Spanish Sport Horses were used from a total of 1,101 animals evaluated, and these were grouped in three age levels and had been ridden by 606 different riders. Only riders who had ridden more than one horse (and vice‐versa) were considered for the analyses. Five linear models with different random effects were analysed according to the covariates, the homogeneity/heterogeneity of the RHI and the relevant residual random effects. The model of best fit was then selected for the genetic evaluation of the animal. In general, models including the RHI effect (M2, M4 and M5) fitted better than the other models, and the best fit was obtained for M4 (with heterogeneous residual variance). The genetic variance increased constantly with age, whereas heritability showed a response on three intervals. This study revealed the varied evolution of the RHI with age, showing the different “plastic abilities” of this relationship.  相似文献   

4.
Two heterogeneous variance adjustment methods and two variance models were compared in a simulation study. The method used for heterogeneous variance adjustment in the Nordic test‐day model, which is a multiplicative method based on Meuwissen (J. Dairy Sci., 79, 1996, 310), was compared with a restricted multiplicative method where the fixed effects were not scaled. Both methods were tested with two different variance models, one with a herd‐year and the other with a herd‐year‐month random effect. The simulation study was built on two field data sets from Swedish Red dairy cattle herds. For both data sets, 200 herds with test‐day observations over a 12‐year period were sampled. For one data set, herds were sampled randomly, while for the other, each herd was required to have at least 10 first‐calving cows per year. The simulations supported the applicability of both methods and models, but the multiplicative mixed model was more sensitive in the case of small strata sizes. Estimation of variance components for the variance models resulted in different parameter estimates, depending on the applied heterogeneous variance adjustment method and variance model combination. Our analyses showed that the assumption of a first‐order autoregressive correlation structure between random‐effect levels is reasonable when within‐herd heterogeneity is modelled by year classes, but less appropriate for within‐herd heterogeneity by month classes. Of the studied alternatives, the multiplicative method and a variance model with a random herd‐year effect were found most suitable for the Nordic test‐day model for dairy cattle evaluation.  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.
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7.
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   

8.
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   

9.
The objectives of this study were to compare covariance functions (CF) and estimate the heritability of milk yield from test‐day records among exotic (Saanen, Anglo‐Nubian, Toggenburg and Alpine) and crossbred goats (Thai native and exotic breed), using a random regression model. A total of 1472 records of test‐day milk yield were used, collected from 112 does between 2003 and 2006. CF of the study were Wilmink function, second‐ and third‐order Legendre polynomials, and linear splines 4 knots located at 5, 25, 90 and 155 days in milk (SP25–90) and 5, 35, 95 and 155 of days in milk (SP35–95). Variance components were estimated by restricted maximum likelihood method (REML). Goodness of fit, Akaike information criterion (AIC), percentage of squared bias (PSB), mean square error (MSE), and empirical correlation (RHO) between the observed and predicted values were used to compare models. The results showed that CF had an impact on (co)variance estimation in random regression models (RRM). The RRM with splines 4 knots located at 5, 25, 90 and 155 of days in milk had the lowest AIC, PSB and MSE, and the highest RHO. The heritability estimated throughout lactation obtained with this model ranged from 0.13 to 0.23.  相似文献   

10.
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   

11.
We compared the goodness of fit of three mathematical functions (including: Legendre polynomials, Lidauer‐Mäntysaari function and Wilmink function) for describing the lactation curve of primiparous Iranian Holstein cows by using multiple‐trait random regression models (MT‐RRM). Lactational submodels provided the largest daily additive genetic (AG) and permanent environmental (PE) variance estimates at the end and at the onset of lactation, respectively, as well as low genetic correlations between peripheral test‐day records. For all models, heritability estimates were highest at the end of lactation (245 to 305 days) and ranged from 0.05 to 0.26, 0.03 to 0.12 and 0.04 to 0.24 for milk, fat and protein yields, respectively. Generally, the genetic correlations between traits depend on how far apart they are or whether they are on the same day in any two traits. On average, genetic correlations between milk and fat were the lowest and those between fat and protein were intermediate, while those between milk and protein were the highest. Results from all criteria (Akaike's and Schwarz's Bayesian information criterion, and ?2*logarithm of the likelihood function) suggested that a model with 2 and 5 coefficients of Legendre polynomials for AG and PE effects, respectively, was the most adequate for fitting the data.  相似文献   

12.
This study was designed to: (i) estimate genetic parameters and breeding values for conception rates (CR) using the repeatability threshold model (RP‐THM) and random regression threshold models (RR‐THM); and (ii) compare covariance functions for modeling the additive genetic (AG) and permanent environmental (PE) effects in the RR‐THM. The CR was defined as the outcome of an insemination. A data set of 130 592 first‐lactation insemination records of 55 789 Thai dairy cows, calving between 1996 and 2011, was used in the analyses. All models included fixed effects of year × month of insemination, breed × day in milk to insemination class and age at calving. The random effects consisted of herd × year interaction, service sire, PE, AG and residual. Variance components were estimated using a Bayesian method via Gibbs sampling. Heritability estimates of CR ranged from 0.032 to 0.067, 0.037 to 0.165 and 0.045 to 0.218 for RR‐THM with the second, third and fourth‐order of Legendre polynomials, respectively. The heritability estimated from RP‐THM was 0.056. Model comparisons based on goodness of fit, predictive abilities, predicted service results of animal, and pattern of genetic parameter estimates, indicated that the model which fit the desired outcome of insemination was the RR‐THM with two regression coefficients.  相似文献   

13.
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   

14.
Our objective was to evaluate changes in breeding values for carcass traits of two meat‐type quail (Coturnix coturnix) strains (LF1 and LF2) to changes in the dietary (methionine + cystine):lysine ([Met + Cys]:Lys) ratio due to genotype by environment (G × E) interaction via reaction norm. A total of 7000 records of carcass weight and yield were used for analyses. During the initial phase (from hatching to day 21), five diets with increasing (Met + Cys):Lys ratios (0.61, 0.66, 0.71, 0.76 and 0.81), containing 26.1% crude protein and 2900 kcal ME/kg, were evaluated. Analyses were performed using random regression models that included linear functions of sex (fixed effect) and breeding value (random effect) for carcass weight and yield, without and with heterogeneous residual variance adjustment. Both fixed and random effects were modelled using Legendre polynomials of second order. Genetic variance and heritability estimates were affected by both (Met + Cys):Lys ratio and strain. We observed that a G × E interaction was present, with changes in the breeding value ranking. Therefore, genetic evaluation for carcass traits should be performed under the same (Met + Cys):Lys ratio in which quails are raised.  相似文献   

15.
The objectives of the present study were (i) to find the best fitted model for repeatedly measured daily dry matter intake (DMI) data obtained from different herds and experiments across lactations and (ii) to get better estimates of the genetic parameters and better genetic evaluations. After editing, there were 572,512 daily DMI records of 3,495 animals (Holstein cows) from 11 different herds across 13 lactations and the animals were under 110 different nutritional experiments. The fitted model for this data set was a univariate repeated‐measure animal model (called model 1) in which additive genetic and permanent environmental (within and across lactations) effects were fitted as random. Model 1 was fitted as two distinct models (called models 2 and 3) based on alternative fixed effect corrections. For unscaled data, each model (models 2 and 3) was fitted as a homoscedastic (HOM) model first and then as a heteroscedastic (HET) model. Then, data were scaled by multiplying with particular herd‐scaling factors, which were calculated by accounting for heterogeneity of phenotypic within‐herd variances. Models were selected based on cross‐validation and prediction accuracy results. Scaling factors were re‐estimated to determine the effectiveness of accounting for herd heterogeneity. Variance components and respective heritability and repeatability were estimated based on a pedigree‐based relationship matrix. Results indicated that the model fitted for scaled data showed better fit than the models (HOM or HET) fitted for unscaled data. The heritability estimates of the models 2 and 3 fitted for scaled data were 0.30 and 0.08, respectively. The repeatability estimates of the model fitted for scaled data ranged from 0.51 to 0.63. The re‐estimated scaling factor after accounting for heterogeneity of residual variances was close to 1.0, indicating the stabilization of residual variances and herd accounted for most of the heterogeneity. The rank correlation of EBVs between scaled and unscaled data ranged from 0.96 to 0.97.  相似文献   

16.
The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd–year–observation_date–age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%–3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.  相似文献   

17.
A two‐dimensional random regression model with regressions on days in milk (DIM) and parity number was applied to lactational milk yields in Chinese Simmental cattle. Random regressions were fitted for additive genetic and permanent environmental effects using a two‐dimensional polynomial on DIM and parity number. A total of 4340 lactational milk yields from Chinese Simmental cattle which calved between 1980 and early 2000 were used in this study. Variance components were estimated using Bayesian methodology via Gibbs sampling. Variances of random regression coefficients associated with all terms of the polynomials were significant. A covariance function showed that heritabilities of lactational milk yields between 200 and 400 DIM over parities varied between 0.25 and 0.45. Heritabilities of 305‐day milk yields from 1st to 6–8th parities were 0.28, 0.30, 0.32 0.32, 0.32, and 0.31, respectively. Ratios of permanent environment variances to total variances at each DIM were greater than corresponding heritabilities. Generally, genetic correlations were higher between lactational milk yields with similar DIM and parity number.  相似文献   

18.
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   

19.
The objectives of this study were (1) to determine the effect of a treatment with eprinomectin in autumn of pastured dairy herds on the anti-Ostertagia ostertagi bulk-tank milk antibody level, (2) to determine the overall effect of this treatment on three milk-production parameters (milk yield, protein % and fat %) and (3) to investigate the value of the pre-treatment Ostertagia-specific bulk-tank milk antibody level to predict the production response after anthelmintic treatment. One hundred and nineteen herds in Flanders (Belgium) were randomly assigned to a treatment with eprinomectin or a placebo in October 2004. Bulk-tank milk samples were collected monthly from August 2004 until April 2005, and the antibody levels against O. ostertagi were determined as optical density ratios (ODRs) with an ELISA. The treatment effect over the 4 months following treatment on three production parameters (milk yield, milk-protein %, milk-fat %) was estimated by mixed models with herd as a random effect. The treatment effect on milk yield was also investigated within six categories of the pre-treatment ODR. The ODR values were lower in the eprinomectin group than in the control group at each time point after treatment. The overall effect on milk yield was estimated at 1.2 kg/cow/day, whereas no effect on the milk-protein % and milk-fat % was observed. Herds in the highest pre-treatment ODR category (>0.84) had a positive milk-yield response of 4.0 kg/cow/day (95%-confidence interval: 1.0; 7.0), while the 95%-confidence intervals of the milk-yield responses in the other categories all included zero. This study demonstrates that treatment with eprinomectin of pastured dairy cows in autumn will lower the Ostertagia-specific bulk-tank milk antibody level during the stabling period and can result in a consistent increase in milk yield. The results indicate that an O. ostertagi bulk-tank milk ELISA can be used to identify the herds where the greatest milk-yield response after an anthelmintic treatment is expected.  相似文献   

20.
A total of 71 522 records (from 3154 horses) with the times per kilometre (TPK), recorded in Spanish Trotter horses (individual races) from racing performances held from 1991 to 2007, were available for this study. The TPK values for the different age groups (young and adult horses) and different distances (1600–2700 m) were considered as different traits, and a bi character random regression model (RRM) was applied to estimate the (co)variance components throughout the trajectory of age groups and distances. The following effects were considered as fixed: the combination of hippodrome‐date of race (404 levels); sex of the animals (3 levels); type of start (2 levels) and a fixed regression of Legendre polynomials (order 2). Those considered as random effects were the random regression Legendre polynomial (order 1) for animals (9201 animals in the pedigree); the individual environment permanent (3154 animals with data) and the driver (n = 957 levels). The residual variance was considered as heterogeneous with two classes (ages). The heritability estimated by distance ranged from 0.12 to 0.34, with a different trajectory for the two age groups. Within each age group, the genetic correlations between adjacent distances were high (>0.90), but decreased when the differences between them were over 400 metres for both age groups. The genetic correlations for the same distance across the age groups ranged from 0.47 to 0.78. Accordingly, the analysed trait (TPK) can be considered as positive genetic correlated but as different traits along the trajectory of distance and age. Therefore, some re‐ranking should be expected in the breeding value of the horses at different characteristics of the racing. The use of RRM is recommended because it allows us to estimate the breeding value along the whole trajectory of race competition.  相似文献   

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