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1.
This study investigated genetic trends of some productive and reproductive traits in a herd of Murrah buffalo raised in São Paulo, Brazil. Variance components for milk production (MP), length of lactation (LL), calving interval (CI) and age of first calving (AFC) were estimated by the restricted maximum likelihood method, using an animal model. Estimated heritability values were 0.38; 0.01; 0.10 and 0.20 for MP, LL, CI and AFC, respectively. Estimated repeatability values were 0.50, 0.13 and 0.20 for MP, LL and CI, respectively. Means of predicted breeding values for cows, dams and sires according to calving year and the genetic correlations were presented.  相似文献   

2.
Calving records from the Animal Breeding Center of Iran collected from January 1990 to December 2007 and comprising 207,106 first calving events of Holsteins from 2,506 herds were analysed using univariate and bivariate linear sire models to estimate heritabilities and genetic correlations between age at first calving (AFC) and productive performance. Average AFC was 26.48 months in this study. The peak in the frequency distribution of AFC clearly exists coinciding with cows calving for the first time at approximately 25 months of age. Heritability estimate for AFC was 0.34 which was greater than the corresponding values for productive traits. The heritability estimates were low to medium for productive traits which ranged from 0.17 to 0.26 for cows in their first calvings. Except for fat and protein percentages of milk, phenotypic and genetic correlations between AFC and productive performance traits were low to moderately negative. Range of genetic correlations between productive traits was −0.53 to 0.99. Reduction of age at first calving appeared to have a negative effect on first lactation protein and fat percentages; however, it had positive effects on milk yield, fat yield, protein yield and their mature equivalents. It seems that reducing age at first calving to 24–25 months is probably more profitable than reducing age at first calving to an earlier time in Iranian conditions.  相似文献   

3.

The main objective of this study was to estimate genetic correlations between fertility and production traits in first, second and third lactations as well as between fertility traits measured in the same way at different ages. The fertility traits studied were: number of inseminations per service period, number of treatments for reproductive disturbances, interval between first and last inseminations, interval between calving and first insemination, and interval between calving and last insemination. Early milk production was measured as the average of the energy-corrected milk yield at the second and third monthly testdays in a lactation. The number of records was approximately 450 000, 350 000, 180 000 and 75 000 in the heifer period, first, second, and third lactations, respectively. A linear, trivariate model that included the effects of herd-year, year, month, age and sire of the cow was applied. To reduce the effect of ongoing selection, 305-days kg protein production in first lactation was included as a variate in all of the analyses. Correlations between the herd-year effects indicated that factors of herd-year level conducive to increased production had a tendency to increase the number of inseminations as well as the number of reproductive treatments, although there was an earlier start and termination of the insemination period. Genetic correlations between fertility traits and production were in the range of 0.2-0.4, all of them unfavourable and higher at later parities. The genetic correlations between fertility traits in the heifer period and the same traits in first lactation were 0.7. Genetic correlations between the first and second lactation varied between 0.7 and 0.9, and between the second and third lactation they were all 0.9 or higher. In conclusion, fertility and production traits need to be selected for simultaneously if fertility is going to be maintained along further genetic improvement on production, and such selection should include fertility results from lactating cows.  相似文献   

4.
The aim of this study was to estimate genetic and phenotypic parameters for growth and survival traits of Sahiwal cattle in Kenya and determine their relationship to milk production and fertility. Performance records of 5,681 animals were obtained from the National Sahiwal Stud and the traits considered were: birth weight (kilogrammes), weaning weight (kilogrammes), pre-weaning average daily gain (grammes per day), post-weaning average daily gain (grammes per day), yearling weight (kilogrammes), mature weight at 36 months (kilogrammes), pre-weaning survival rate (SR), post-weaning survival rate (PSR), lactation milk yield (kilogrammes), age at first calving (days), and calving interval (days). The data was analysed using univariate and bivariate animal model based on restricted maximum likelihood methods, incorporating all known pedigree relationship among animals. The additive direct effects were more pronounced than maternal genetic effects in early and in post-yearling growth performance. The additive genetic variance and heritabilities were low for SR and PSR. The correlation between direct additive genetic and maternal genetic effect were negative for pre-yearling traits. Genetic and phenotypic correlations among growth traits and between growth and milk yield were positive, whilst those between growth and fertility were weak and negative. Correlations between survival and growth were generally low and positive. The estimates obtained in this study provide the necessary technical parameters for evaluating alternative breeding programmes and selection schemes for sustainable improvement of Sahiwal cattle.  相似文献   

5.
Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.  相似文献   

6.
The test‐day milk fat‐to‐protein ratio (TD‐FPR) could serve as a measure of energy balance status and might be used as a criterion to improve metabolic stability and fertility through genetic selection. Therefore, genetic parameters for fertility traits, test‐day milk yield (TD‐MY) and TD‐FPR, as well as, their relationships during different stages of lactation, were estimated on data collected from 25 968 primiparous Thai dairy crossbred cows. Gibbs sampling algorithms were implemented to obtain (co)variance components using both univariate linear and threshold animal models and bivariate linear‐linear and linear‐threshold animal models with random regression. Average TD‐MY and TD‐FPR were 12.60 and 1.15. Heritability estimates for TD‐MY, TD‐FPR and selected fertility traits ranged from 0.31 to 0.58, 0.17 to 0.19 and 0.02 to 0.05, respectively. Genetic correlations among TD‐FPR and TD‐MY, TD‐FPR and fertility traits, and TD‐MY and fertility traits ranged from 0.05 to ‐0.44, from ‐0.98 to 0.98 and ‐0.22 to 0.79, respectively. Selection for lower TD‐FPR would decrease numbers of inseminations per conception and increase conception at first service and pregnancy within 90 days. In addition, cow selection based only on high milk production has strong effects to prolong days to first service, days open and calving interval.  相似文献   

7.
Field records from the American Angus Association were used to study the associations of sire marbling score EPD and sire weaning weight maternal (milk) EPD with age at first calving (AFC) and calving interval (CI). Cows were selected based on the accuracy of their sire's milk (> or =.7) or marbling (> or =.6) EPD. The data were screened using biological constraints, and regression models were used to identify records that were greater than 5 SD from the mean. The AFC was modeled for both milk and marbling data sets to account for effects of year, sire EPD, and their interaction. The CI was subdivided into first, second, and mature calving interval traits and modeled to account for state, year, calf sex, calf birth weight (BW), calf weaning weight (WW), sire EPD, and interactions of EPD with year and state. Derivative-free REML was used to estimate heritability and genetic correlations for AFC and CI. Sire milk EPD and marbling EPD were predictors of AFC (P < .001); however, pooled estimates were unreliable because of state x EPD interactions (P < .001). Increases in sire milk EPD resulted in reductions in AFC; however, there was no consistent pattern to effects of marbling EPD increases. Models accounted for < 8% of variation in AFC. Sire milk EPD was not a predictor of first, second, or mature CI (P > .1). Sire marbling score EPD was not a predictor of second, or mature CI (P > .1); however, it was associated (P = .059) with first CI, although regression estimates varied across states and prevented pooling. The BW, sex, and WW were predictors of CI (P < .001). Increases in BW resulted in longer mature CI, and mature CI decreased as WW increased. The AFC was heritable (.22), and CI traits had heritabilities ranging from .01 to .03. The AFC was genetically correlated with first CI (-.6) and mature CI (-.93). Genetic correlations between CI traits were uninterpretable because of low additive genetic variances. In conclusion, sire marbling score and milk EPD do not seem to be reliable predictors of AFC or CI. The BW and WW have significant but small effects on AFC and CI. Selection for AFC is possible, but earlier calving heifers may have longer calving intervals.  相似文献   

8.
The study was undertaken to estimate the genetic divergence among FG, IFG, FJG, IFJG, and R crosses of Gir cow on the basis of age at first conception, age at first calving, and lactation milk yield per day of lactation length using Mahalanobis D2 statistics. The genetic groups’ influence was significant (P?<?0.01) for all traits separately and simultaneously (V test) based on three traits. The differences in the D2 values among all the genetic groups’ combinations were significant except IFG with R genetic group combination. The total D2 values for age at first conception (AFCon), age at first calving (AFC), and lactation milk yield per day of lactation length (LMY/LL) were 18.85, 0.06, and 9.01 respectively. The percent contribution of AFCon to the total D2 value was maximum as 67.51 followed by LMY/LL as 32.27 and lowest of AFC as 0.22. Among the clusters formed on the basis of D2 values, IFG, IFJG, and R formed one cluster, whereas, FG and FJG formed second cluster. The magnitude of inter-cluster distance was greater than intra-cluster distance.  相似文献   

9.
Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305-day milk yield using the K-means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype-by-environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305-day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305-day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.  相似文献   

10.
This study estimated genetic and phenotypic parameters and annual trends for growth and fertility traits of Charolais and Hereford cattle in Kenya. Traits considered were birth weight (BW, kg), pre-weaning average daily gain (ADG, kg/day) and weaning weight (WW, kg); calving interval (CI, days) and age at first calving (AFC, days). Direct heritability estimates for growth traits were 0.36 and 0.21; 0.25 and 0.10; 0.23 and 0.13 for BW, ADG and WW in Charolais and Hereford, respectively. Maternal heritability estimates were 0.11 and 0.01; 0.18 and 0.00; 0.17 and 0.17 for BW, ADG and WW in Charolais and Hereford, respectively. Direct-maternal genetic correlations ranged between −0.46 and 1.00; −0.51 and −1.00; −0.47 and −0.39 for BW, ADG and WW in Charolais and Hereford, respectively. Genetic correlations ranged from −0.99 to unity and −1.00 to unity for growth and fertility traits respectively. Prospects for improvement of growth and fertility traits exist.  相似文献   

11.
Purebred Holstein-Friesian cows are the main exotic breed used for milk production on large, medium, and small farms in Kenya. A study was undertaken on seven large-scale farms to investigate the genetic trends for milk production and fertility traits between 1986 and 1997 and the genetic relationships between the traits. This involved 3,185 records from 1,614 cows, the daughters of 253 sires. There was a positive trend in breeding value for 305-d milk yield of 12.9 kg/ yr and a drop in calving interval of 0.9 d/yr over the 11-yr period. Bulls from the United States (U.S.) had an average total milk yield breeding value 230 kg higher than the mean of all bulls used; Canada (+121 kg), Holland (+15 kg), the United Kingdom (U.K., 0 kg), and Kenya (-71 kg) were the other major suppliers of bulls. Average breeding values of bulls for calving interval by country of origin were -1.31 (Canada), -1.27 (Holland), -0.83 (U.S.), -0.63 (Kenya), and 0.68 d (U.K.). The genetic parameters for 305-d milk yield were 0.29 (heritability), 0.05 (permanent environment effect as proportion of phenotypic variance) resulting in an estimated repeatability of 0.34. Using complete lactation data rather than 305-d milk yield resulted in similar estimates of the genetic parameters. However, when lactation length was used as a covariate heritability was reduced to 0.25 and the permanent environment effect proportion increased to 0.09. There was little genetic control of either lactation length (heritability, 0.09) or calving interval (heritability, 0.05); however, there were strong genetic correlations between first lactation milk yield, calving interval, and age at first calving.  相似文献   

12.
Calving records from the Animal Breeding Center of Iran collected from January 1987 to December 2007 and comprising 292,875 calving events of Holsteins from 1,413 dairy herds were analyzed using univariate and bivariate linear animal models to estimate heritabilities and genetic correlations for calving intervals in the first three lactations of Holstein cows. Genetic trends were obtained by regressing yearly mean estimates of breeding values on calving year. Average calving intervals were from 406 to 414 days and decreased over the parities. Heritability estimates for calving intervals varied from 0.03 to 0.04 across the parities. Also, estimates of genetic correlations between calving intervals in different parities were high and ranged from 0.67 to 0.89. The average annual phenotypic trends obtained from fitting linear regression of annual mean calving intervals at parity 1 and 2 were significant (P < 0.01), but the phenotypic trend of calving interval at parity 3 was not significant over the years. On the other hand, there was an increasing genetic trend for calving interval at parity 1, and there were decreasing genetic trends for calving intervals at parity 2 and 3 over the years (P < 0.01). The low estimates of heritability obtained in this study imply that much of the improvement in calving interval traits could be attained by improvement of production environment rather than genetic selection.  相似文献   

13.

In a breeding programme where young potential breeding bulls are reared on performance test stations, selection based on own results can be carried out before test inseminations. Both beef and milk production traits are included in the total merit index used for selection, and estimates of genetic and phenotypic parameters of these traits are therefore of interest for an optimal construction of such indices. Data on first lactation milk records from the field and beef records of potential dairy breeding bulls from the Danish performance test stations were analysed in bivariate animal-sire models using the AI-REML algorithm. Genetic correlations of 0.16, 0.25 and 0.43 between feed intake capacity and protein yield were obtained for Red Danish (RD), Danish Black and White (DBW) and Danish Jersey (DJ), respectively. These correlations were significantly different from zero for the two populations (DBW and DJ). Genetic correlations around zero between feed efficiency and protein yield were obtained for all three populations. Genetic correlations of 0.44, 0.19 and 0.47 between average daily gain and protein yield were obtained for RD, DBW and DJ, respectively. The genetic correlations between protein yield and muscle area was close to zero for DBW, while it was -0.31 for RD. Selection index calculations indicate that indices composed of different beef performance traits can be used as early predictors for milk yield. Selection on such an index could increase the breeding value of the young bulls for milk production traits by 0.8-2.0% of the population mean.  相似文献   

14.
Multivariate procedures are used for the extraction of variables from the correlation matrix of phenotypes in order to identify those traits that explain the largest proportion of phenotypic variation and to evaluate the relationship structure between these traits. The reproductive traits (days from calving to first estrus [CFE], days from calving to last service [CLS], calving interval [CI] and gestation length [GL]) and milk production traits (milk yield at 305 days of lactation [MY305], peak yield [PY] and milk yield per day of calving interval [MYCI]) of 5,217 Holstein females (primiparous and multiparous) were measured. Principal component analysis (PCA) and factor analysis of the correlation matrix were used to estimate the correlation between traits. Analysis grouped the seven traits into three principal components and four latent factors that retained approximately 81.5% and 88.9% of the total variation of the data, respectively. The production variables exhibited positive phenotypic correlation coefficients of high magnitude (>.67). The phenotypic correlation estimates between the productive and reproductive traits were low, ranging from .13 to .22. A strong association (.99) was observed between CLS and CI. Our results indicate that multivariate analysis was effective in generating correlations between the traits studied, grouping the seven traits in a smaller number of variables that retained approximately 81% of the total variation of the data.  相似文献   

15.

Genetic and environmental correlations were estimated both between the ability to show oestrus and milk production, and among different fertility traits (heat-intensity score, number of days between consecutive inseminations, number of inseminations per service period, interval between calving and first or last insemination, and interval between first and last insemination). Milk production was measured as the average of the energy-corrected milk yield on second and third monthly test days. The number of records were approximately 450000, 350000, 180000 and 75000 in the heifer period, first, second and third lactations, respectively. A linear, trivariate model that included the effects of herd-year, year, month, age and cow's sire was applied. The results indicated that further selection for increased milk production is not expected to deteriorate heat intensity. The number of days between calving and first insemination, the number of inseminations and the heat intensity were complementary, and can be recommended for a selection index for fertility.  相似文献   

16.
The performance of indigenous Begait cattle (498 cows, 284 calves, and 48 heifers) in northern Ethiopia was studied. System of herd management significantly (P?<?0.01) influenced all production traits. Calves in medium-input herds (MIHM) grew faster than those in low-input herds (LIHM), by 232 g/d from birth to 9 months (Gain1) and by 385 g/d from 9 to 12 months (Gain2). Cow’s dry period, calving interval (CI), and age at first calving (AFC) were 234, 222, and 343 days shorter for MIHM than for LIHM. Compared with LIHM, cows from MIHM had 74% higher daily milk yield (DMY) and 91% higher lactation milk yield (LMY). Calves born at wet season grew faster by 14 and 10% than those calves born in the dry season at Gain1 and Gain2. The subsequent CI of cows calved in the wet season had 77 days shorter, 0.45 kg DMY, and 93 kg LMY increment. The differences between production systems can be attributed to differences in management skills and access to better quality feeds. Technical intervention is needed to ensure provision of balanced rations to exploit the potential productivity of Begait cattle.  相似文献   

17.
Breed additive and non‐additive effects plus heritabilities and repeatabilities for milk yield per lactation (LMY), milk yield per day (DMY), lactation length (LL), annual milk yield (AMY), annual milk yield per metabolic body weight (AMYBW) and cow weight at calving (BW) were estimated for 5464 lactation records collected from purebred Boran (B), Friesian (F), and crosses of Friesian and Jersey (J) breeds with the Boran breed raised in the tropical highlands of Ethiopia. Single trait analysis was carried out by using two equivalent repeatability animal models. In the first model the genotype was fitted as a fixed group effect, while in the second model the genotype was substituted by breed additive, heterotic and recombination effects fitted as fixed covariates. Both the F and J breed additive effects, measured as a deviation from the B breed were significant (p < 0.01) for all traits, except for BW of the J. The F and J additive contributions were 2774 ± 81 and 1473 ± 362 kg for LMY, 7.1 ± 0.2 and 4.8 ± 0.8 kg for DMY, 152 ± 7 and 146 ± 31 days for LL, 2345 ± 71 and 1238 ± 319 kg for AMY, 20.6 ± 0.9 and 18.9 ± 4.3 kg for AMYBW, and 140 ± 4 and ?21 ± 22 kg (p > 0.05) for BW. The heterotic contributions to the crossbred performance were also positive and significant (p < 0.01) for all traits. The F1 heterosis expressed as a deviation from the mid‐parent values were 22 and 66% for LMY, 11 and 20% for DMY, 29 and 29% for LL, 21 and 64% for AMY, 42 and 42% for AMYBW, and 2% (p < 0.05) and 11% for BW for the F × B and J × B crosses, respectively. The recombination effect estimated for the F × B crosses was negative and significant for LMY (?526 ± 192 kg, p < 0.01), DMY (?3.0 ± 0.4 kg, p < 0.001), AMY (?349 ± 174 kg, p < 0.05) and BW (?68 ± 11 kg, p < 0.001). For the J × B crosses the recombination loss was significant and negative only for DMY (?2.2 ± 0.7 kg, p < 0.05) and BW (?33 ± 17 kg, p < 0.05). The direct heritabilities (h2) estimated for LMY, DMY, LL, AMY and AMYBW were 0.24 ± 0.04, 0.19 ± 0.03, 0.13 ± 0.03, 0.23 ± 0.04 and 0.17 ± 0.05, respectively. Based on the genetic parameters estimated, the best breeding strategy to increased milk production under highland Ethiopian conditions is to apply selection on purebred base populations (Boran and Friesian) and then crossing them to produce F1 dairy cows. However, for breeding decision based on total dairy merit, further investigations are needed for traits such as milk quality, reproduction, longevity and survival.  相似文献   

18.
Birth weight and calving difficulty were analyzed with Bayesian methodology using univariate linear models, a bivariate linear model, a threshold model for calving difficulty, and a joint threshold-linear model using a probit approach. Field data included 26,006 records of Gelbvieh cattle. Simulated populations were generated using parameters estimated from the field data. The Gibbs sampler was used to obtain estimates of the marginal posterior mean and standard deviation of the (co)variance components, heritabilities, and correlations. In the univariate analyses, the posterior mean of direct heritability for calving difficulty was .23 with the threshold model and .18 with the linear model. Maternal heritabilities were .10 and .08, respectively. In the bivariate analysis, posterior means of direct heritability for calving difficulty were .21 and .18 for the bivariate linear-threshold and linear-linear model, respectively. Maternal heritabilities were .09 and .06, respectively. Direct heritability for birth weight was .25 for the univariate model and .26 for bivariate models. Maternal heritability was .05 for the linear-threshold model and the univariate model and .06 for the bivariate linear model. Genetic correlation between direct genetic effects in both traits was .81 for the linear-threshold model and .79 for the bivariate linear. Residual correlation was .35 for the bivariate linear model and .50 for the bivariate linear-threshold. A simulation study confirmed that the posterior mean of the marginal distribution was suitable as a point estimate for univariate threshold and bivariate linear-threshold models.  相似文献   

19.
The effect of the environmental level of production (ENV) on the expression of heterosis for 305-day milk, fat, protein, and fat plus protein (FP) yields, lactation average somatic cell score (LSCS), and age at first calving (AFC) was investigated in first lactation Black and White dairy cows in the Netherlands, and officially enrolled in the Dutch herd-book. Holstein Friesian (HF), Dutch Friesian (DF), and first generation (F1) crosses obtained from the mating of HF sires and DF dams (HD) were involved in the study, and data from animals with a calving date between 1990 and 2000 were used. A total of 22,930 cows with production and AFC information distributed in 3549 herds and 11,055 cows with LSCS information distributed in 2071 herds, were available. Adjusted lactation yield of milk for each herd was obtained using a model that accounted for fixed effects of herd, year and month of calving, genotype, and AFC. The overall mean of all adjusted data was computed, and 3 ENV were defined on the basis of the overall mean ± 0.5 standard deviations. Once ENV was defined, traits were analysed with a model that included fixed effects of ENV, herd nested within ENV, AFC (only production traits and LSCS), year and month of calving, genotype, and the interaction between ENV and genotype. Least squares means for the interaction effect were used to estimate heterosis and to evaluate its magnitude across ENV. Holstein Friesian achieved higher productions than DF. First generation crosses showed productions close to HF, especially in the low ENV. Estimates of heterosis for yield traits ranged from 2.4% (milk) in the high to 5.3% (fat) in the low ENV, and reduced with increasing ENV. Estimates for LSCS and AFC were low, with the exception of LSCS in the high ENV. Results suggest that the highest non-additive genetic effects for yield traits and LSCS were expressed in the most stressful ENV, i.e., the low one for production and the high one for LSCS.  相似文献   

20.
Genetic parameters and genetic trends for age at first calving (AFC), interval between first and second calving (CI1), and interval between second and third calving (CI2) were estimated in a Colombian beef cattle population composed of Angus, Blanco Orejinegro, and Zebu straightbred and crossbred animals. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 3-trait model included the fixed effects of contemporary group (year-season of calving-sex of calf; sex of calf for CI1 and CI2 only), age at calving (CI1 and CI2 only), breed genetic effects (as a function of breed fractions of cows), and individual heterosis (as a function of cow heterozygosity). Random effects for AFC, CI1, and CI2 were cow and residual. Program AIREMLF90 was used to perform computations. Estimates of heritabilities for additive genetic effects were 0.15 ± 0.13 for AFC, 0.11 ± 0.06 for CI1, and 0.18 ± 0.11 for CI2. Low heritabilities suggested that nutrition and reproductive management should be improved to allow fuller expressions of these traits. The correlations between additive genetic effects for AFC and CI1 (0.33 ± 0.41) and for AFC and CI2 (0.40 ± 0.36) were moderate and favorable, suggesting that selection of heifers for AFC would also improve calving interval. Trends were negative for predicted cow yearly means for AFC, CI1, and CI2 from 1989 to 2004. The steepest negative trend was for cow AFC means likely due to the introduction of Angus and Blanco Orejinegro cattle into this population.  相似文献   

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