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1.
Genetic parameters for the efficiency of gain traits on 380 boars and the genetic relationships with component traits were estimated in 1,642 pigs (380 boars, 868 gilts, and 394 barrows) in 7 generations of a Duroc population. The efficiency of gain traits included the feed conversion ratio (FCR) and residual feed intake (RFI) and their component traits, ADG, metabolic BW (MWT), and daily feed intake (FI). The RFI was calculated as the difference between the actual and expected FI. The expected FI was predicted by the nutritional requirement and by the residual of phenotypic (RFI(phe)) and genetic (RFI(gen)) regressions from the multivariate analysis for FI on MWT and ADG. The means for RFI(phe) and RFI(gen) were close to zero, and the mean for nutritional RFI was negative (-0.11 kg/d). The traits studied were moderately heritable (ranging from 0.27 to 0.53). The genetic and phenotypic correlations between ADG and FI were moderate to high, whereas the genetic correlation between MWT and FI was moderate, and the phenotypic correlation between them was low. The corresponding correlations between RFI(phe) and RFI(gen) were > 0.95, implying that they can be regarded as the same trait. The genetic and phenotypic correlations of FCR with measures of RFI were high but lower than unity. The RFI(phe) was phenotypically independent of its component traits, MWT (r(p) = 0.01) and ADG (r(p) = 0.03). The RFI(gen) was genetically independent of MWT (r(g) = -0.04), whereas there was a weak genetic relationship (r(g) = 0.15) between RFI(gen) and ADG. Residual FI was more heritable than FCR, and the genetic and phenotypic correlations of RFI(phe) and RFI(gen) with FI were positive and stronger than that of FCR with FI. These results provide evidence that RFI(phe) or RFI(gen) should be included in breeding programs for Duroc pigs to make genetic improvement in the efficiency of gain.  相似文献   

2.
Genetic parameters of average daily gain (ADG), metabolic body weight (MWT), body weight at finish (BWF), daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI) were estimated in 740 Japanese Black bulls. RFI was calculated as the difference between actual and expected feed intake predicted by the residual of multiple regression (RFIphe) and genetic regression (RFIgen) from the multivariate analysis for DFI, MWT, and ADG. The estimations were made for the test periods of 140 days (77 bulls) and 112 days (663 bulls). The mean for RFIphe was close to zero and RFIgen was negative. Most of the traits studied were moderately heritable (ranging from 0.24 to 0.49), except for ADG and FCR (0.20 and 0.15, respectively). The genetic correlations among growth traits (ADG, MWT and BWF) and between DFI and growth traits were high, while the phenotypic correlations between them were moderate to high. The genetic and phenotypic correlations between RFIphe and RFIgen were > 0.95 implying that they are regarded as the same trait and the genetic correlations of RFI (RFIphe and RFIgen) with FCR and DFI were favorably high. RFIphe was phenotypically independent of its component traits, MWT (rp = − 0.01) and ADG (rp = 0.01). RFIgen was genetically independent of MWT (rg = − 0.07), while there was a weak genetic relationship (rg = 0.18) between RFIgen and ADG. These results provide evidence that RFIgen should be included for genetic improvement of feed efficiency in Japanese Black breeding program.  相似文献   

3.
A data set based on 50 studies including feed intake and utilization traits was used to perform a meta‐analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta‐analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta‐analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 ± 0.04, 0.39 ± 0.03, 0.31 ± 0.02, 0.31 ± 0.03 and 0.26 ± 0.03, respectively. Pooled genetic correlation estimates ranged from ?0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.  相似文献   

4.
Genetic parameter estimates for growth traits in Horro sheep   总被引:5,自引:0,他引:5  
Variance components and genetic parameters were estimated for growth traits: birth weight (BWT), weaning weight (WWT), 6‐month weight (6MWT) and yearling weight (YWT) in indigenous Ethiopian Horro sheep using the average information REML (AIREML). Four different models: sire model (model 1), direct animal model (model 2), direct and maternal animal model (model 3) and direct–maternal animal model including the covariance between direct and maternal effects (model 4) were used. Bivariate analysis by model 2 was also used to estimate genetic correlation between traits. Estimates of direct heritability obtained from models 1–4, respectively, were for BWT 0.25, 0.27, 0.18 and 0.32; for WWT, 0.16, 0.26, 0.1 and 0.14; for 6MWT 0.18, 0.26, 0.16 and 0.16; and for YWT 0.30, 0.28, 0.23, and 0.31. Maternal heritability estimates of 0.12 and 0.23 for BWT; 0.19 and 0.24 for WWT; 0.09 and 0.09 for 6MWT and 0.08 and 0.14 for YWT were obtained from models 3 and 4, respectively. The correlations between direct and maternal additive genetic effects for BWT, WWT, 6MWT and YWT were –0.64, –0.42, 0.002 and –0.46, respectively. On the other hand, the genetic correlations between BWT and the rest of growth traits (WWT, 6MWT and YWT, respectively) were 0.45, 0.33 and 0.31, whereas correlations between WWT and 6MWT, WWT and YWT and 6MWT and YWT were 0.98, 0.84 and 0.87, respectively. The medium to high direct and maternal heritability estimates obtained for BWT and YWT indicate that in Horro sheep faster genetic improvement through selection is possible for these traits and it should consider both (direct and maternal) h2 estimates. However, since the direct‐maternal genetic covariances were found to be negative, caution should be made in making selection decisions. The high genetic correlation among early growth traits imply that genetic improvement in any one of the traits could be made through indirect selection for correlated traits.  相似文献   

5.
The aim of this experiment was to evaluate the significance of neonatal environment on feed efficiency. For that purpose, rabbits from a line selected for residual feed intake (RFI) during 10 generations (G10 kits) were cross‐fostered with non‐selected control does (i.e., G0 line), and reciprocally. In parallel, sibs were fostered by mothers from their original line. Nine hundred animals were raised in individual (N = 456) or collective (N = 320) cages. Traits analysed in this study were body weight at 32 days and at 63 days, average daily gain (ADG), feed intake between weaning and 63 days (FI), feed conversion ratio (FCR) and RFI. The maternal environment offered by does from the line selected for RFI deteriorated the FCR of the kits, independently of their line of origin, during fattening (+0.08 ± 0.02) compared to FCR of kits nursed by G0 does. The line, the type of housing and the batch were significant effects for all the measured traits: G10 kits were lighter than their G0 counterparts at 32 days (?82.9 ± 9 g, p < 0.0001) and at 63 days (?161 ± 16 g, p < 0.0001). They also had a lower ADG (?2.36 ± 0.36 g/day, p < 0.0001), RFI (?521 ± 24 g/day, p < 0.0001) and a lower FI (?855 ± 31 g, p < 0.0001), resulting in a more desirable feed efficiency (FCR: ?0.35 ± 0.02). There was no significant difference in the contrast of G10 and G0 performances between collective and individual/digestive cages (p > 0.22): ?2.35 g/day versus 2.94 g/day for ADG, ?0.39 versus ?0.40 for FCR, ?577 g versus ?565 g for RFI and ?879 g versus ?859 g for FI, respectively). Thus, no genotype‐by‐environment (housing) interaction is expected at the commercial level, that is, no re‐ranking of the animals due to collective housing.  相似文献   

6.
1. The objectives of the present study were to estimate heritability and genetic correlations for feed efficiency and body weight (BW) in Japanese quail.

2. Recorded traits during different weeks of the growing period were BW from hatch to 35 d, feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI) from hatch to 28 d of age.

3. Genetic parameters were estimated by restricted maximum likelihood method using ASREML software. The results showed that heritability estimates for BW ranged from 0.11 to 0.22, and maternal permanent environmental effect was the highest at hatch (0.45). FCR, RFI and FI showed moderate heritabilities ranging from 0.13 to 0.40.

4.Genetic correlations of BW28 with FI0–28 (0.88) and RFI0–28 (0.1) and genetic correlation of FI0–28 with FCR0–28 (0.13) and RFI0–28 (0.52) were positive. A negative genetic correlation was found between BW28 and FCR0–28 (?0.49). There was a high positive genetic correlation (0.67) between RFI0–28 and FCR0–28.

5. In conclusion, selection for increased BW and reduced FI in a selection index could be recommended to improve feed efficiency traits including FCR and RFI in Japanese quail.  相似文献   

7.
Data on 380 Duroc boars from seven generations, and 1026 Landrace pigs (341 boars and 685 gilts) from six generations were used to estimate genetic parameters for daily gain (DG), backfat thickness (BF), metabolic weight (MWT), daily feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI). Two measures of RFI were estimated as the difference between actual feed intake and that predicted from models that included initial test age and weight and DG (RFI1); and initial test age and weight, DG and BF (RFI2). Heritability estimates for DG, MWT and FI were moderate for both breeds. BF estimates were high for both the breeds. The measures of feed efficiency (FCR and RFI) were moderately heritable. Genetic correlations of BF with measures of RFI were stronger when BF was not included in the estimation of RFI (0.40 and 0.46 for Duroc and Landrace, respectively (for RFI1), compared with 0.05 and 0.06 for Duroc and Landrace, respectively (for RFI2)). Genetic correlations of MWT with measures of RFI were all negative and low. Genetic and phenotypic correlations between DG and measures of RFI were close to zero, which indicated that selection for reduced RFI could be made without adversely affecting DG. BF should also decrease, and MWT should increase under selection for reduced RFI. The reduction in BF would depend on the measure of RFI used.  相似文献   

8.
Residual feed intake (RFI) has been proposed as an index for determining beef cattle energetic efficiency. Although the relationship of RFI with feed conversion ratio (FCR) is well established, little is known about how RFI compares to other measures of efficiency. This study examined the phenotypic relationships among different measures of energetic efficiency with growth, feed intake, and ultrasound and carcass merit of hybrid cattle (n = 150). Dry matter intake, ME intake (MEI), ADG, metabolic weight (MWT), and FCR during the test averaged 10.29 kg/d (SD = 1.62), 1,185.45 kJ/(kg0.75 x d) (SD = 114.69), 1.42 kg/d (SD = 0.25), 86.67 kg0.75 (SD = 10.21), and 7.27 kg of DM/kg of gain (SD = 1.00), respectively. Residual feed intake averaged 0.00 kg/d and ranged from -2.25 kg/d (most efficient) to 2.61 kg/d (least efficient). Dry matter intake (r = 0.75), MEI (r = 0.83), and FCR (r = 0.62) were correlated with RFI (P < 0.001) and were higher for animals with high (>0.5 SD) RFI vs. those with medium (+/-0.5 SD) or low (<0.5 SD) RFI (P < 0.001). Partial efficiency of growth (PEG; energetic efficiency for ADG) was correlated with RFI (r = -0.89, P < 0.001) and was lower (P < 0.001) for high- vs. medium- or low-RFI animals. However, RFI was not related to ADG (r = -0.03), MWT (r = -0.02), relative growth rate (RGR; growth relative to instantaneous body size; r = -0.04), or Kleiber ratio (KR; ADG per unit of MWT; r = -0.004). Also, DMI was correlated (P < 0.01) with ADG (r = 0.66), MWT (r = 0.49), FCR (r = 0.49), PEG (r = -0.52), RGR (r = 0.18), and KR (r = 0.36). Additionally, FCR was correlated (P < 0.001) with ADG (r = -0.63), PEG (r = -0.83), RGR (r = -0.75), and KR (r = -0.73), but not with MWT (r = 0.07). Correlations of measures of efficiency with ultrasound or carcass traits generally were not different from zero except for correlations of RFI, FCR, and PEG, respectively, with backfat gain (r = 0.30, 0.20, and -0.30), ultrasound backfat (r = 0.19, 0.21, and -0.25), grade fat (r = 0.25, 0.19, and -0.27), lean meat yield (r = -0.22, -0.18, and 0.24), and yield grade (r = 0.28, 0.24, and -0.25). These phenotypic relationships indicate that, compared with other measures of energetic efficiency, RFI should have a greater potential to improve overall production efficiency and PEG above maintenance, and lead to minimal correlated changes in carcass merit without altering the growth and body size of different animals.  相似文献   

9.
Data were collected over a period of 21 years (1988–2008) to estimate (co)variance components for birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), weaning to 6WT (ADG2), and from 6WT to 12WT (ADG3) in Sirohi goats maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India. Analyses were carried out by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. The best model was chosen after testing the improvement of the log-likelihood values. Heritability estimates for BWT, WWT, 6WT, 9WT, 12WT, ADG1, ADG2, and ADG3 were 0.39 ± 0.05, 0.09 ± 0.03, 0.06 ± 0.02, 0.09 ± 0.03, 0.11 ± 0.03, 0.10 ± 0.3, 0.04 ± 0.02, and 0.01 ± 0.01, respectively. For BWT and ADG1, only direct effects were significant. Estimate of maternal permanent environmental effect were important for body weights from weaning to 12WT and also for ADG2 and ADG3. However, direct maternal effects were not significant throughout. Estimate of c 2 were 0.06 ± 0.02, 0.03 ± 0.02, 0.06 ± 0.02, 0.05 ± 0.02, 0.02 ± 0.02, and 0.02 ± 0.02 for 3WT, 6WT, 9WT, 12WT, ADG2, and ADG3, respectively. The estimated repeatabilities across years of ewe effects on kid body weights were 0.10, 0.08, 0.05, 0.08, and 0.08 at birth, weaning, 6, 9, and 12 months of age, respectively. Results suggest possibility of modest rate of genetic progress for body weight traits and ADG1 through selection, whereas only slow progress will be possible for post-weaning gain. Genetic and phenotypic correlations between body weight traits were high and positive. High genetic correlation between 6WT and 9WT suggests that selection of animals at 6 months can be carried out instead of present practice of selection at 9 months.  相似文献   

10.
提高猪饲料效率的测定与选择   总被引:1,自引:0,他引:1  
为提高猪饲料效率的选择,本试验测定一些与猪饲料效率相关的生产性状并进行遗传评估。方法:测定60头军牧1号白猪后备公猪的采食量、体增重、背膘厚等生产性状,用猪剩余采食量(RFI)和饲料转化率(FCR)作为评价饲料效率的两个指标,并对其遗传参数进行评估。结果:测定期内军牧1号公猪群体FCR均值为2.61,RFI的标准差为77.52。RFI与FCR的遗传力分别是0.35、0.33,RFI与ADFI(日采食量)、ADG(日增重)、BF(背膘厚)的遗传相关分别是0.89、0.12、-0.05,FCR与ADFI、ADG、BF的遗传相关分别是0.55、-0.65、-0.11。结论:军牧1号白猪品种内饲料效率存在较大的遗传差异,由于RFI与ADG遗传相关很低,因此用RFI作为选择性状可有效提高猪的饲料效率。  相似文献   

11.
Breeding strategies based on feed efficiency are now implemented in most animal species using residual feed intake (RFI) criteria. Although relevant, the correlated responses of feeding behaviour traits resulting from such selection on RFI are poorly documented. We report the estimated feeding behaviour at three time levels (visit, meal and day) and genetic parameters between the feeding behaviour traits and their links with RFI and its components. Feed intake, feeding duration at three time levels (per visit, meal and day), feeding rate, number of visits and time‐between‐visits were estimated for 951 Romane lambs fed via automatic concentrate feeders. Heritability estimates of feeding behaviour traits ranged from 0.19 to 0.54 with higher estimates for the day level than the visit level. Daily feed intake was not genetically linked to feed intake at the visit level, whereas feeding duration between visit and day levels was moderately correlated (Rg = +0.41 ± 0.12). RFI was not significantly correlated with feeding rate, but was positively linked to feed intake and feeding duration at the day level (+0.73 ± 0.09 and +0.41 ± 0.13, respectively) and negatively at the visit level (?0.33 ± 0.14 and ?0.22 ± 0.17, respectively). Selecting animals with lower RFI values might modify their feeding behaviour by increasing feed intake and feeding duration at the visit level but decrease the number of visits per day (+0.51 ± 0.14).  相似文献   

12.
The purpose of the present study was to obtain estimates of variance components and genetic parameters for direct and maternal effects on various growth traits in Beetal goat by fitting four animal models, attempting to separate direct genetic, maternal genetic and maternal permanent environmental effects under restricted maximum likelihood procedure. The data of 3,308 growth trait records of Beetal kids born during the period from 2004 to 2019 were used in the present study. Based on best fitted models, the direct additive h2 estimates were 0.06, 0.27, 0.37, 0.17 and 0.10 for birth weight (BWT), weight at 3 (WT3), 6 (WT6), 9 (WT9) and 12 (WT12) months of age, respectively. Maternal permanent environmental effects significantly contributed for 10% and 7% of total variance for BWT and WWT, respectively, which reduced direct heritability by 40 and 10% for respective traits from the models without these effects. For average daily gain (ADG1) and Kleiber ratios (KR1) up to weaning period (3 months) traits, maternal permanent environmental effects accounted for 7% and 8% of phenotypic variance, respectively, and resulted in a reduction of 6.6% and 5.4% in direct h2 of respective traits. For post-weaning traits, the maternal effects were non-significant (p > .05) which indicates diminishing influence of mothering ability for these traits. High and positive genetic correlations were obtained among WT3-WT6, WT6-WT9 and WT9-WT12 with correlations of 0.96 ± 0.25, 0.84 ± 0.23 and 0.90 ± 0.13, respectively. Thus, early selection at weaning age can be practised taking into consideration maternal variation for effective response to selection in Beetal goat.  相似文献   

13.
This study was conducted to evaluate the importance of maternal effect on body measurement traits at an early stage of growth, and to estimate the genetic relationships between direct and maternal effects and among body measurement traits at 0 month (0‐mo) and 4 months (4‐mo) of age in a population of Japanese Black calves. Body measurements and body weight of 889 Japanese Black calves were estimated with the use of an animal model by the Residual Maximum Likelihood procedure. Direct heritabilities were low to moderate, ranging between 0.17 ± 0.09 and 0.48 ± 0.13 at 0‐mo, and slightly lower, ranging between 0.15 ± 0.07 and 0.33 ± 0.13 at 4‐mo. Estimated maternal heritabilities were low to moderate, ranging between 0.08 ± 0.07 and 0.33 ± 0.07 at 0‐mo and 0.13 ± 0.06 to 0.33 ± 0.06 at 4‐mo. The direct genetic correlations between 0‐mo and 4‐mo were moderate to highly positive, ranging from 0.53 ± 0.23 to 0.96 ± 0.09. The estimated direct genetic correlation of chest width with other width traits was low and positive at both ages, whereas with hip width it was high and positive (0.80 ± 0.09) at 0‐mo, suggesting that simultaneous improvement of body width of the front and back parts is possible. Maternal genetic effects were relatively independent of direct genetic effects for body measurement traits and can be considered in genetic evaluation.  相似文献   

14.
Direct and maternal genetic parameters for measures of feed consumption and feed efficiency were estimated using data recorded on 514 performance tested young male Japanese Black cattle during the period from 1978–2004. Measures of feed consumption were daily feed intake, concentrate intake, ratio of roughage intake to feed intake, total digestible nutrient intake, digestible crude protein intake (DCPI) and metabolizable energy intake. Feed efficiency traits included feed conversion ratio (FCR), total digestible nutrient conversion ratio (TCR), digestible crude protein conversion ratio (DCR) and residual feed intake. Data were analyzed using three alternative animal models (including direct and direct plus maternal genetic effects (including or excluding covariance between direct and maternal genetic effects)). The direct heritability estimates for all the measures of feed consumption and feed efficiency were moderate to high, suggesting that sufficient genetic variation exists in these traits which should respond to selection. All the measures of feed consumption were genetically more strongly correlated with residual feed intake than with other measures of feed efficiency. Maternal heritability estimates for DCPI, FCR and TCR were not significantly different from zero, while the corresponding estimates for all the studied traits were low (ranged from 0.07 to 0.24). The estimates of direct heritability for measures of feed consumption were reduced up to 34% when maternal genetic effect was considered in the model. An antagonistic relationship existed between direct and maternal genetic effect (ram) for FCR and DCR, which biased the estimates of direct heritability downwards. The results indicate that maternal effects play an important role in measures of feed consumption and most of the feed efficiency traits, which should be accounted for these traits in genetic evaluation system.  相似文献   

15.
Background: The feed conversion ratio(FCR) and residual feed intake(RFI) are common indexes in measuring feed efficiency for livestock. RFI is a feed intake adjusted for requirements for maintenance and production so these two traits are related. Similarly, FCR is related to feed intake and weight gain because it is their ratio. Cholecystokinin type A receptor(CCKAR) plays an important role in animal digestive process. We examined the interplay of these three parameters in a local Chinese chicken population.Results: The feed intake(FI) and body weights(BW) of 1,841 individuals were monitored on a daily basis from 56 to 105 d of age. There was a strong correlation between RFI and average daily feed intake(ADFI) and a negative correlation between the FCR and daily gain(r_g=-0.710). Furthermore, we identified 51 single nucleotide polymorphisms(SNPs) in the CCKAR and 4 of these resulted in amino acid mutations. The C334A mutation was specifically associated with FI and the expected feed intake(EFI)(P 0.01) and significantly associated with the average daily gain(ADG)(P 0.05). G1290A was significantly associated with FI and EFI(P 0.05).Conclusion: FCR is apply to weight selecting, and RFI is more appropriate if the breeding focus is feed intake. And C334A and G1290A of the CCKAR gene can be deemed as candidate markers for feed intake and weight gain.  相似文献   

16.
Because feed is the major input in pork production, conversion of feed into lean tissue at minimum costs has been a focus for improvement. Several researchers have proposed using residual feed intake (RFI) rather than feed conversion ratio (FCR) for genetic improvement of feed efficiency. Little is known about the variation in RFI in pigs. As several studies suggest a greater RFI is related to greater animal activity levels, the current study investigated the phenotypic relationship between RFI and feed intake (FI) behavior of 104 group-housed growing Duroc barrows allowed ad libitum access to feed. Feed intake, BW gain, feeding time (TIME), feeding frequency (VISITS), RFI, and FCR were calculated for 5 periods of 14, 23, 28, 21, or 23 d in length (periods 1 through 5, respectively) on animals that were between 73 to 95 d of age at the start of the testing period. Barrows that grew faster consumed more feed (P < 0.001), and barrows that consumed more feed were fatter (P < 0.01). There were no correlations between VISITS and TIME, between VISITS and FI, or between VISITS and RFI. Barrows that spent more time at the feeder, however, consumed more feed (P < 0.05) and had greater RFI in periods 1, 3, and 5 (P < 0.05). As expected, FI and FCR were highly correlated with RFI (P < 0.001). These results suggest that a greater FI rather than greater feed intake activity resulted in greater RFI values.  相似文献   

17.
Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability ( \texth\texta2 ) \left( {{\text{h}}_{\text{a}}^2} \right) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c 2) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.  相似文献   

18.
Our objective was to estimate genetic parameters for feed intake, feeding behavior, and ADG in composite ram lambs ((1/2) Columbia, (1/4) Hampshire, (1/4) Suffolk). Data were collected from 1986 to 1997 on 1,239 ram lambs from approximately 11 to 17 wk of age at the U.S. Meat Animal Research Center near Clay Center, NE. Feeding equipment consisted of an elevated pen with an entrance chute that permitted access to the feeder by only one ram lamb at a time, with disappearance of feed measured by an electronic weighing system. Ram lambs were grouped 11 per pen from 1986 to 1989, and nine per pen from 1990 to 1997. Data were edited to exclude invalid feeding events, and approximately 80% of the data remained after edits were applied. Traits analyzed were daily feed intake (DFI), event feed intake (EFI), residual feed intake (RFI), daily feeding time (DFT), event feeding time (EFT), number of daily feeding events (DFE), and ADG. Feed intake traits of DFI and EFI had estimated heritabilities of 0.25 and 0.33, respectively, whereas estimated heritability of RFI was 0.11. Heritability estimates for feeding behavior traits, including DFT, EFT, and DFE, ranged from 0.29 to 0.36. Average daily gain had an estimated heritability of 0.26. Genetic correlations were positive between all pairs of traits, except for RFI and ADG, and that estimate was essentially zero. Phenotypic correlations were generally similar to genetic correlations. Genetic correlations were large (0.80) between DFI and ADG, intermediate between DFI and RFI (0.61) and between DFT and DFE (0.55), and low (0.17 to 0.31) for the other pairs of traits, with the exception of RFI and ADG (-0.03). Genetic correlations between behavioral traits were greater than correlations between behavioral traits and measures of feed intake or ADG; however, selection for ADG and/or feed intake would be expected to cause some changes in feeding behavior.  相似文献   

19.
Records of 9,055 lambs from a composite population originating from crossing Columbia rams to Hampshire x Suffolk ewes at the U.S. Meat Animal Research Center were used to estimate genetic parameters among growth traits. Traits analyzed were weights at birth (BWT), weaning (7 wk, WWT), 19 mo (W19), and 31 mo (W31) and postweaning ADG from 9 to 18 or 19 wk of age. The ADG was also divided into daily gain of males (DGM) and daily gain of females (DGF). These two traits were analyzed with W19 and with W31 in three-trait analyses. (Co)variance components were estimated with REML for an animal model that included fixed effects of sex, age of dam, type of birth or rearing, and contemporary group. Random effects were direct and maternal genetic of animal and dam with genetic covariance, maternal permanent environmental, and random residual. Estimates of direct heritability were .09, .09, .35, .44, .19, .16, and .23 for BWT, WWT, W19, W31, ADG, DGM, and DGF, respectively. Estimates of maternal permanent environmental variance as a proportion of phenotypic variance were .09, .12, .03, .03, .03, .06, and .02, respectively. Estimates of maternal heritability were .17 and .09 for BWT and WWT and .01 to .03 for other traits. Estimates of genetic correlations were large among W19, W31, and ADG (.69 to .97), small between BWT and W31 or ADG, and moderate for other pairs of traits (.32 to .45). The estimate of genetic correlation between DGM and DGF was .94, and the correlation between maternal permanent environmental effects for these traits was .56. For the three-trait analyses, the genetic correlations of DGM and DGF with W19 were .69 and .82 and with W31 were .67 and .67, respectively. Results show that models for genetic evaluation for BWT and WWT should include maternal genetic effects. Estimates of genetic correlations show that selection for ADG in either sex can be from records of either sex (DGM or DGF) and that selection for daily gain will result in increases in mature weight but that BWT is not correlated with weight at 31 mo.  相似文献   

20.
Records on 514 bulls from the sire population born from 1978 to 2004, and on 22,099 of their field progeny born from 1997 to 2003 with available pedigree information (total number = 124,458) were used to estimate genetic parameters for feed intake and energy efficiency traits of bulls and their relationships with carcass traits of field progeny. Feed intake and energetic efficiency traits were daily feed intake, TDN intake, feed conversion ratio (FCR), TDN conversion ratio (TDNCR), residual feed intake (RFI), partial efficiency of growth, relative growth rate, and Kleiber ratio. Progeny carcass traits were carcass weight (CWT), yield estimate, ribeye area, rib thickness, subcutaneous fat thickness (SFT), marbling score (MSR), meat color standard (MCS), fat color standard (FCS), and meat quality grade. All measures of feed intake and energetic efficiency were moderately heritable (ranged from 0.24 to 0.49), except for partial efficiency of growth and relative growth rate, which were high (0.58) and low (0.14), respectively. The phenotypic and genetic correlations between FCR and TDNCR were >or=0.93. Selection for Kleiber ratio will improve all of the energetic efficiency traits with no effect on feed intake measures (daily feed intake and TDN intake). The genetic correlations of FCR, TDNCR, and RFI of bulls with most of the carcass traits of their field progeny were favorable (ranged from -0.24 to -0.72), except with fat color standard (no correlation), MCS, and SFT. Positive (unfavorable) genetic correlations of MCS with FCR, TDNCR, and RFI (0.79, 0.70, and 0.51, respectively) were found. The SFT was negatively genetically correlated with FCR and TDNCR (-0.32 and -0.20, respectively); however, the genetic correlation between RFI and SFT was not significantly different from zero (r(g) = -0.08 +/- 0.12). Favorable correlated responses in CWT, yield estimate, ribeye area, rib thickness, MSR, and meat quality grade would be predicted for selection against any measure of energetic efficiency. The correlated responses in CWT and MSR of progeny were greater for selection against RFI than for selection against any other energetic efficiency trait. Results of this study indicate that RFI should be preferred over other measures of energetic efficiency to include in selection programs.  相似文献   

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