首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 52 毫秒
1.
The genetic parameters for Brahman cattle under the tropical conditions of Mexico are scarce. Therefore, heritabilities, additive direct and maternal correlations, and genetic correlations for birth weight (BW) and 205 days adjusted weaning weight (WW205) were estimated in four Brahman cattle herds in Yucatan, Mexico. Parameters were estimated fitting a bivariate animal model, with 4,531 animals in the relationship matrix, of which 2,905 had BW and 2,264 had WW205. The number of sires and dams identified for both traits were 122 and 962, respectively. Direct heritability estimates for BW and WW205 were 0.41?±?0.09 and 0.43?±?0.09, and maternal heritabilities were 0.15?±?0.07 and 0.38?±?0.08, respectively. Genetic correlations between direct additive and maternal genetic effects for BW and WW205 were ?0.41?±?0.22 and ?0.50?±?0.15, respectively. The direct genetic, maternal, and phenotypic correlations between BW and WW205 were 0.77?±?0.09, 0.61?±?0.18, and 0.35, respectively. The moderate to high genetic parameter estimates suggest that genetic improvement by selection is possible for those traits. The maternal effects and their correlation with direct effects should be taken into account to reduce bias in genetic evaluations.  相似文献   

2.
Covariance components were estimated for growth traits (BW, birth weight; WW, weaning weight; YW, yearling weight), visual scores (BQ, breed quality; CS, conformation; MS, muscling; NS, navel; PS, finishing precocity), hip height (HH), and carcass traits (BF, backfat thickness; LMA, longissimus muscle area) measured at yearling. Genetic gains were obtained and validation models on direct and maternal effects for BW and WW were fitted. Genetic correlations of growth traits with CS, PS, MS, and HH ranged from 0.20 ± 0.01 to 0.94 ± 0.01 and were positive and low with NS (0.11 ± 0.01 to 0.20 ± 0.01) and favorable with BQ (0.14 ± 0.02 to 0.37 ± 0.02). Null to moderate genetic correlations were obtained between growth and carcass traits. Genetic gains were positive and significant, except for BW. An increase of 0.76 and 0.72 kg is expected for BW and WW, respectively, per unit increase in estimated breeding value (EBV) for direct effect and an additional 0.74 and 1.43, respectively, kg per unit increase in EBV for the maternal effect. Monitoring genetic gains for HH and NS is relevant to maintain an adequate body size and a navel morphological correction, if necessary. Simultaneous selection for growth, morphological, and carcass traits in line with improve maternal performance is a feasible strategy to increase herd productivity.  相似文献   

3.
The aim of this study was to estimate genetic parameters for BW of Angus cattle up to 5 yr of age and to discuss options for including mature weight (MW) in their genetic evaluation. Data were obtained from the American Angus Association. Only records from herds with at least 500 animals and with >10% of animals with BW at ≥ 2 yr of age were considered. Traits were weaning weight (WW, n = 81,525), yearling weight (YW, n = 62,721), and BW measured from 2 to 5 yr of age (MW2, n = 15,927; MW3, n = 12,404; MW4, n = 9,805; MW5, n = 7,546). Genetic parameters were estimated using an AIREML algorithm with a multiple-trait animal model. Fixed effects were contemporary group and departure of the actual age from standard age (205, 365, 730, 1,095, 1,460, and 1,825 d of age for WW, YW, MW2, MW3, MW4, and MW5, respectively). Random effects were animal direct additive genetic, maternal additive genetic, maternal permanent environment, and residual. Estimates of direct genetic variances (kg(2)) were 298 ± 71.8, 563 ± 15.1, 925 ± 52.1, 1,221 ± 65.8, 1,406 ± 80.4, and 1,402 ± 66.9; maternal genetic variances were 167 ± 4.8, 153 ± 6.1, 123 ± 9.1, 136 ± 12.25, 167 ± 18.0, and 110 ± 14.0; maternal permanent environment variances were 124 ± 2.9, 120 ± 4.3, 61 ± 7.5, 69 ± 11.9, 103 ± 15.9, and 134 ± 35.2; and residual variances were 258 ± 3.8, 608 ± 8.6, 829 ± 34.2, 1,016 ± 38.8, 1,017 ± 52.1, and 1,202 ± 63.22 for WW, YW, MW2, MW3, MW4, and MW5, respectively. The direct genetic correlation between WW and YW was 0.84 ± 0.14 and between WW and MW ranged from 0.66 ± 0.06 (WW and MW4) to 0.72 ± 0.11 (WW and MW2). Direct genetic correlations ranged from 0.77 ± 0.08 (YW and MW5) to 0.85 ± 0.07 (YW and MW2) between YW and MW, and they were ≥ 0.95 among MW2, MW3, MW4, and MW5. Maternal genetic correlations between WW and YW and MW ranged from 0.52 ± 0.05 (WW and MW4) to 0.95 ± 0.07 (WW and YW), and among MW they ranged from 0.54 ± 0.14 (MW4 and MW5) to 0.94 ± 0.07 (MW2 and MW3). Genetic correlations suggest that a genetic evaluation for MW may be MW2-based and that including BW from older ages could be accomplished by adjusting records to the scale of MW2.  相似文献   

4.
In the present study, (co)variance components and genetic parameters in Nellore sheep were obtained by restricted maximum likelihood (REML) method using six different animal models with various combinations of direct and maternal genetic effects for birth weight (BW), weaning weight (WW), 6-month weight (6MW), 9-month weight (9MW) and 12-month weight (YW). Evaluated records of 2075 lambs descended from 69 sires and 478 dams over a period of 8 years (2007–2014) were collected from the Livestock Research Station, Palamaner, India. Lambing year, sex of lamb, season of lambing and parity of dam were the fixed effects in the model, and ewe weight was used as a covariate. Best model for each trait was determined by log-likelihood ratio test. Direct heritability for BW, WW, 6MW, 9MW and YW were 0.08, 0.03, 0.12, 0.16 and 0.10, respectively, and their corresponding maternal heritabilities were 0.07, 0.10, 0.09, 0.08 and 0.11. The proportions of maternal permanent environment variance to phenotypic variance (Pe2) were 0.07, 0.10, 0.07, 0.06 and 0.10 for BW, WW, 6MW, 9MW and YW, respectively. The estimates of direct genetic correlations among the growth traits were positive and ranged from 0.44(BW-WW) to 0.96(YW-9MW), and the estimates of phenotypic and environmental correlations were found to be lower than those of genetic correlations. Exclusion of maternal effects in the model resulted in biased estimates of genetic parameters in Nellore sheep. Hence, to implement optimum breeding strategies for improvement of traits in Nellore sheep, maternal effects should be considered.  相似文献   

5.
The aim of this study was to estimate genetic parameters for growth traits in Mexican Nellore cattle. A univariate animal model was used to estimate (co)variance components and genetic parameters. The traits evaluated were birth weight (BW), weaning weight (WW), and yearling weight (YW). Models used included the fixed effects of contemporary groups (herd, sex, year, and season of birth) and age of dam (linear and quadratic) as a covariate. They also included the animal, dam, and residual as random effects. Phenotypic means (SD) for BW, WW, and YW were 31.4 (1.6), 175 (32), and 333 (70) kg, respectively. Direct heritability, maternal heritability, and the genetic correlation between additive direct and maternal effects were 0.59, 0.17, and −0.90 for BW; 0.29, 0.17, and −0.90 for WW; and 0.24, 0.15, and −0.86 for YW, respectively. The results showed moderate direct and maternal heritabilities for the studied traits. The genetic correlations between direct and maternal effects were negative and high for all the traits indicating important tradeoffs between direct and maternal effects. There are significant possibilities for genetic progress for the growth traits studied if they are included in a breeding program considering these associations.  相似文献   

6.
The objectives of the current study were to investigate the additive genetic associations between heifer pregnancy at 16 months of age (HP16) and age at first calving (AFC) with weight gain from birth to weaning (WG), yearling weight (YW) and mature weight (MW), in order to verify the possibility of using the traits measured directly in females as selection criteria for the genetic improvement of sexual precocity in Nelore cattle. (Co)variance components were estimated by Bayesian inference using a linear animal model for AFC, WG, YW and MW and a nonlinear (threshold) animal model for HP16. The posterior means of direct heritability estimates were: 0.45 ± 0.02; 0.10 ± 0.01; 0.23 ± 0.02; 0.36 ± 0.01 and 0.39 ± 0.04, for HP16, AFC, WG, YW and MW, respectively. Maternal heritability estimate for WG was 0.07 ± 0.01. Genetic correlations estimated between HP16 and WG, YW and MW were 0.19 ± 0.04; 0.25 ± 0.06 and 0.14 ± 0.05, respectively. The genetic correlations of AFC with WG, YW and MW were low to moderate and negative, with values of − 0.18 ± 0.06; − 0.22 ± 0.05 and − 0.12 ± 0.05, respectively. The high heritability estimated for HP16 suggests that this trait seem to be a better selection criterion for females sexual precocity than AFC. Long-term selection for animals that are heavier at young ages tends to improve the heifers sexual precocity evaluated by HP16 or AFC. Predicted breeding values for HP16 can be used to select bulls and it can lead to an improvement in sexual precocity. The inclusion of HP16 in a selection index will result in small or no response for females mature weight.  相似文献   

7.
Estimates of genetic parameters for growth traits in Kermani sheep   总被引：3，自引：0，他引：3  
Birth weight (BW), weaning weight (WW), 6-month weight (W6), 9-month weight (W9) and yearling weight (YW) of Kermani lambs were used to estimate genetic parameters. The data were collected from Shahrbabak Sheep Breeding Research Station in Iran during the period of 1993-1998. The fixed effects in the model were lambing year, sex, type of birth and age of dam. Number of days between birth date and the date of obtaining measurement of each record was used as a covariate. Estimates of (co)variance components and genetic parameters were obtained by restricted maximum likelihood, using single and two-trait animal models. Based on the most appropriate fitted model, direct and maternal heritabilities of BW, WW, W6, W9 and YW were estimated to be 0.10 +/- 0.06 and 0.27 +/- 0.04, 0.22 +/- 0.09 and 0.19 +/- 0.05, 0.09 +/- 0.06 and 0.25 +/- 0.04, 0.13 +/- 0.08 and 0.18 +/- 0.05, and 0.14 +/- 0.08 and 0.14 +/- 0.06 respectively. Direct and maternal genetic correlations between the lamb weights varied between 0.66 and 0.99, and 0.11 and 0.99. The results showed that the maternal influence on lamb weights decreased with age at measurement. Ignoring maternal effects in the model caused overestimation of direct heritability. Maternal effects are significant sources of variation for growth traits and ignoring maternal effects in the model would cause inaccurate genetic evaluation of lambs.  相似文献   

8.
Genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive per year (LBAY), lifetime number of piglets weaned per year (LPWY), lifetime litter birth weight per year (LBWY) and lifetime litter weaning weight per year (LWWY) were estimated using phenotypic records of 3085 sows collected from 1989 to 2013 in a commercial swine farm in Northern Thailand. The five‐trait animal model included the fixed effects of first farrowing year‐season, breed group and age at first farrowing. Random effects were animal and residual. Heritability estimates ranged from 0.04 ± 0.02 for LBWY to 0.17 ± 0.04 for LPL. Genetic correlations ranged from 0.66 ± 0.14 between LPL and LBAY to 0.95 ± 0.02 between LPWY and LWWY. Spearman rank correlations among estimated breeding values for LPL and lifetime production efficiency traits tended to be higher for boars than for sows. Sire genetic trends were negative and significant for all traits, except for LPWY. Dam genetic trends were positive and significant for all traits. Sow genetic trends were mostly positive and significant only for LPWY and LBWY. Improvement of LPL and lifetime production efficiency traits will require these traits to be included in the selection indexes used to choose replacement boars and gilts in this population.  相似文献   

9.
Genetic and phenotypic parameters were estimated for lamb growth traits for the Dorper sheep in semi-arid Kenya using an animal model. Data on lamb growth performance were extracted from available performance records at the Sheep and Goats Station in Naivasha, Kenya. Growth traits considered were body weights at birth (BW0, kg), at 1 month (BW1, kg), at 2 months (BW2, kg), at weaning (WW, kg), at 6 months (BW6, kg), at 9 months (BW9, kg) and at yearling (YW, kg), average daily gain from birth to 6 months (ADG0–6, gm) and from 6 months to 1 year (ADG6–12, gm). Direct heritability estimates were, correspondingly, 0.18, 0.36, 0.32, 0.28, 0.21, 0.14, 0.29, 0.12 and 0.30 for BW0, BW1, BW2, WW, BW6, BW9, YW, ADG0–6 and ADG6–12. The corresponding maternal genetic heritability estimates for body weights up to 9 months were 0.16, 0.10, 0.10, 0.19, 0.21 and 0.18. Direct-maternal genetic correlations were negative and high ranging between −0.47 to −0.94. Negative genetic correlations were observed for ADG0–6–ADG6–12, BW2–ADG6–12, WW–ADG6–12 and BW6–ADG6–12. Phenotypic correlations ranged from 0.15 to 0.96. Maternal effects are important in the growth performance of the Dorper sheep though a negative correlation exists between direct and maternal genetic effects. The current study has provided important information on the extent of additive genetic variation in the existing flocks that could now be used in determining the merit of breeding rams and ewes for sale to the commercial flocks. The estimates provided would form the basis of designing breeding schemes for the Dorper sheep in Kenya. Implications of the study to future Dorper sheep breeding programmes are also discussed.  相似文献   

10.
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   

11.
Tail length and tail lesions are the major triggers for tail biting in pigs. Against this background, 2 datasets were analyzed to estimate genetic parameters for tail characteristics and growth traits. Dataset 1 considered measurements for trait tail length (T-LEN) and for the growth traits birth weight (BW), weaning weight (WW), postweaning weight (PWW), and average daily gain (ADG) from 9,348 piglets. Piglets were born in the period from 2015 to 2018 and kept on the university Gießen research station. Dataset 2 included 4,943 binary observations from 1,648 pigs from the birth years 2016 to 2019 for tail lesions (T-LES) as indicators for nail necrosis, tail abnormalities, or tail biting. T-LES were recorded at 30 ± 7 d after entry for rearing (T-Les-1), at 50 ± 7 d after entry for rearing (end of the rearing period, T-LES-2), and 130 ± 20 d after entry for rearing (end of fattening period, T-LES-3). Genetic statistical model evaluation for dataset 1 based on Akaike’s information criterion and likelihood ration tests suggested multiple-trait animal models considering covariances between direct and maternal genetic effects. The direct heritability for T-LEN was 0.42 (±0.03), indicating the potential for genetic selection on short tails. The maternal genetic heritability for T-LEN was 0.05 (±0.04), indicating the influence of uterine characteristics on morphological traits. The negative correlation between direct and maternal effects for T-LEN of –0.35 (±0.13), as well as the antagonistic relationships (i.e., positive direct genetic correlations in the range from 0.03 to 0.40) between T-LEN with the growth traits BW, WW, PWW, and ADG, complicate selection strategies and breeding goal definitions. The correlations between direct effects for T-LEN and maternal effects for breeding goal traits, and vice versa, were positive but associated with a quite large SE. The heritability for T-LES when considering the 3 repeated measurements was 0.23 (±0.04) from the linear (repeatability of 0.30) and 0.21 (±0.06; repeatability of 0.29) from the threshold model. The breeding value correlations between T-LES-3 with breeding values from the repeatability models were quite large (0.74 to 0.90), suggesting trait lesion recording at the end of the rearing period. To understand all genetic mechanisms in detail, ongoing studies are focusing on association analyses between T-LEN and T-LES, and the identification of tail biting from an actor’s perspective.  相似文献   

12.
The objective of the present study was to estimate genetic changes of body weight at different ages in Moghani sheep. Traits included were birth weight (BW, n = 4,208), 3-month weight (3MW, n = 4,175), 6-month weight (6MW, n = 3,138), 9-month weight (9MW, n = 2,244), and yearling weight (YW, n = 1,342). Data and pedigree information used in this study were collected at the Breeding Station of Moghani sheep during 1989–2005. The analysis was carried out for five traits, using the MTGSAM program. Breeding values of individual animals were obtained from a multivariate animal model analysis and genetic trends were obtained by regressing the means of predicted breeding values on year of birth for each trait. Direct genetic trends were positive and significant (P < 0.05) for BW, 3MW, 6MW, 9MW, and YW and were 1.63, 69.20, 79.38, 66.83, and 110.22 g/year, respectively. Also, maternal genetic trends for BW, 3MW, 6MW, 9MW, and YW were positive and significant (P < 0.05) and were 2.36, 49.18, 37.33, 17.73, and 9.67 g/year, respectively. The results showed that improvement of body weights of Moghani sheep seems feasible in selection programs.  相似文献   

13.
Genetic parameters for birth weight (BW), weaning weight (WW) and pre-weaning daily gain (PWDG) in Iranian Mehraban sheep were estimated using restricted maximum likelihood (REML) procedure. Six different animal models were fitted, differentiated by including or excluding maternal effects, with and without covariance between maternal and direct genetic effects. The estimates for direct heritability ranged from 0.26 to 0.53, 0.18 to 0.32 and 0.15 to 0.33 for BW, WW and PWDG respectively. The estimates were substantially higher when maternal effects, either genetic or environmental, were ignored in the model. The results of this study show that full models with maternal genetic and environmental effects gave the most accurate estimates for early growth traits.  相似文献   

14.
SUMMARY: Field data on weight recordings provided by the Australian Simmental Breeders Association was analysed. From a data set of 64,962 animals, which had either birth (BW), weaning (WW), yearling (YW), or final weight (FW) records a subset of 17 herds comprising 18,083 animals was used to obtain uni- and bivariate estimates of variance components. This subset had to be subdivided into six further subsets, called group herds. The models used allowed for additive genetic, maternal genetic, and permanent environmental effects and for a covariance between additive direct and maternal genetic effects. Estimates were pooled across group herds. The results for BW, WW, YW, FW were .33, .35, .37, and .30, respectively, for heritabilities and .074, .18, and .11 for maternal heritabilities (not estimated for FW). Significant correlations between direct and maternal genetic effects (rAM) existed for WW and YW in the magnitude of -.39 and -.22. However, further research is needed due to the problems associated with the estimation of r(AM) . ZUSAMMENFASSUNG: Sch?tzung direkter und maternaler (Ko)Varianz-Komponenten für Wachstumsmerkmale bei australischem Fleckvieh Gegenstand der Untersuchung waren im Feld erhobene Gewichte, die von der Australischen Simmental Breeders Association bereitgestellt worden waren. Aus einer Datei von 64.962 Tieren, die entweder ein Geburtsgewicht (GG), ein Absetzgewicht (AG), ein J?hrlingsgewicht (JG) oder ein Endgewicht (EG) aufwiesen, wurde ein Teildatensatz von 18.083 Tieren extrahiert und einer uni- und bivariaten Sch?tzung von Varianzkomponenten unterzogen. Diese Datei mu?te weiterhin in sechs verschiedene Dateien aufgeteilt werden; diese wurden Gruppenherden genannt. Die verwendeten Modelle erlaubten additiv-genetische, maternal-genetische und permanente Umwelteffekte sowie das Vorhandensein einer Kovarianz zwischen additiv-genetischem und maternal-genetischem Effekt. Die Sch?tzwerte wurden über die Gruppenherden gepoolt. Die Ergebnisse in der Reihenfolge GG, AG, JG und EG waren 0,33, 0,35, 0,37 und 0,30 für die Heritabilit?ten sowie 0,074, 0,18 und 0,11 für die maternalen Heritabilit?ten (nicht gesch?tzt für EG). Signifikante Korrelationen zwischen direktem und maternal-genetischem Effekt (r(AM) ) existierten für AG und JG in der Gr??enordnung von -0,39 und -0,22. Trotz dieses Ergebnisses sind weitere Untersuchungen n?tig, weil die Sch?tzung von r(AM) problematisch ist.  相似文献   

15.
For the first time, the current study reports the genetic and phenotypic correlations between growth and reproductive traits in Zandi sheep. The data were comprised of 4,309 records of lamb growth traits from 1,378 dams and 273 sires plus 2,588 records of reproductive traits from 577 ewes. These data were extracted from available performance records at Khojir Breeding Station of Zandi sheep in Tehran, Iran, from 1993 to 2008. Correlations were estimated from two animal models in a bivariate analysis using restricted maximum likelihood procedure between lamb growth traits [birth weight (BW), weaning weight at 3 months of age (WW), as well as six-month weight (6 MW)] and ewe reproductive traits [litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB), and total litter weight at weaning (TLWW)]. The genetic correlations between BW and reproductive traits varied from low to high ranges from 0.10 for BW–LSB to 0.86 for BW–TLWB. WW was moderately (0.37) to highly (0.96) correlated with all the reproductive traits. Moreover, the genetic correlations were observed between 6 MW and reproductive traits, varied from 0.19 to 0.95. Relationships between growth and reproductive traits ranged from 0.01 for BW–LSW to 0.28 for BW–TLWB in phenotypic effects. Results indicated that selection to improve WW would have high effect on genetic response in TLWW, and also, these results could be effective for all of the reproductive traits in Zandi sheep.  相似文献   

16.
Correlated effects of selection for components of litter size on growth and backfat thickness were estimated using data from 3 pig lines derived from the same base population of Large White. Two lines were selected for 6 generations on either high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (C). Genetic parameters for individual piglet BW at birth (IWB); at 3 wk of age (IW3W); and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to 10 wk of age (ADGPW), and from 25 to 90 kg of BW (ADGT); and age (AGET) and average backfat thickness (ABT) at 90 kg of BW were estimated using REML methodology applied to a multivariate animal model. In addition to fixed effects, the model included the common environment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences between OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) methodology. Average genetic trends for direct and maternal effects were computed by regressing line differences on generation number. Estimates of direct and maternal heritabilities were, respectively, 0.10, 0.12, 0.20, 0.24, and 0.41, and 0.17, 0.33, 0.32, 0.41, and 0.21 (SE = 0.03 to 0.04) for IWB, IW3W, IWW, ADGBW, and ADGPW. Genetic correlations between direct and maternal effects were moderately negative for IWB (-0.21 +/- 0.18), but larger for the 4 other traits (-0.59 to -0.74). Maternal effects were nonsignificant and were removed from the final analyses of ADGT, AGET, and ABT. Direct heritability estimates were 0.34, 0.46, and 0.21 (SE = 0.03 to 0.05) for ADGT, AGET, and ABT, respectively. Direct and maternal genetic correlations of OR with performance traits were nonsignificant, with the exception of maternal correlations with IWB (-0.28 +/- 0.13) and ADGPW (0.23 +/- 0.11) and direct correlation with AGET (-0.23 +/- 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correlations (-0.34 to -0.65) with performance traits. The only significant genetic trends were a negative maternal trend for IBW in the OR line and favorable direct trends for postweaning growth (ADGT and AGET) in both lines. Selection for components of litter size has limited effects on growth and backfat thickness, although it slightly reduces birth weight and improves postweaning growth.  相似文献   

17.
Beef cattle producers in Brazil use body weight traits as breeding program selection criteria due to their great economic importance. The objectives of this study were to evaluate different animal models, estimate genetic parameters, and define the most fitting model for Brahman cattle body weight standardized at 120 (BW120), 210 (BW210), 365 (BW365), 450 (BW450), and 550 (BW550) days of age. To estimate genetic parameters, single-, two-, and multi-trait analyses were performed using the animal model. The likelihood ratio test was verified between all models. For BW120 and BW210, additive direct genetic, maternal genetic, maternal permanent environment, and residual effects were considered, while for BW365 and BW450, additive direct genetic, maternal genetic, and residual effects were considered. Finally, for BW550, additive direct genetic and residual effects were considered. Estimates of direct heritability for BW120 were similar in all analyses; however, for the other traits, multi-trait analysis resulted in higher estimates. The maternal heritability and proportion of maternal permanent environmental variance to total variance were minimal in multi-trait analyses. Genetic, environmental, and phenotypic correlations were of high magnitude between all traits. Multi-trait analyses would aid in the parameter estimation for body weight at older ages because they are usually affected by a lower number of animals with phenotypic information due to culling and mortality.  相似文献   

18.
The aim of this paper was to estimate direct and maternal genetic parameters for calving ease (CE), birth weight (BrW), weaning weight (WW), and calving interval (CI) to assess the possibility of including this information in beef cattle improvement programs. Field data, including a total of 59,813 animals (1,390 sires and 1,147 maternal grand sires) from the Asturiana de los Valles beef cattle breed, were analyzed with a multivariate linear model. Estimates of heritability for direct genetic effects (CED, CID, BrWD, and WWD) were 0.191 +/- 0.019, 0.121 +/- 0.013, 0.390 +/- 0.030, and 0.453 +/- 0.035, respectively, whereas those for maternal genetic effects (CEM, BrWM, and WWM) were 0.140 +/- 0.015, 0.208 +/- 0.020, and 0.138 +/- 0.022, respectively. Genetic correlations between direct or maternal genetic effects across traits were, in general, positive and moderate to low. However, genetic correlation for the pair CED-BrWD was positive and high (0.604 +/- 0.064). Genetic correlations between the direct and maternal genetic effects within a trait were negative and moderate (-0.219 +/- 0.097 for CE, -0.337 +/- 0.080 for BrW, and -0.440 +/- 0.102 for WW). Genetic correlations for CED-BrWM and CED-WWM were -0.121 +/- 0.090 and -0.097 +/- 0.113, respectively. The genetic correlation for CEM-CID was unfavorable (0.485 +/- 0.078), and those for CEM-BrWD (-0.094 +/- 0.079) and CEM-WWD (-0.125 +/- 0.082) were low and negative. The genetic correlation between CID and WWM was favorable (-0.148 +/- 0.106). Overall, the data presented here support the hypothesis that maternal effects for CE and BrW are not the same and that the genetic relationships between CI and maternal effects for WW in beef cattle follow a similar pattern to that reported between CI and milk yield in dairy cattle. Moreover, the need to include direct and maternal breeding values in beef cattle selection programs is suggested.  相似文献   

19.
Birth weights (BW) and weaning weights (WW) of 4,423 non-creep-fed Hereford calves were used to estimate direct and maternal sources of variation and maternal phenotypic effects (fm). Seventeen different (co)variances among relatives were estimated through Henderson's Method III and restricted estimated maximum likelihood procedures. Direct and maternal (co)variances and fm were evaluated by multiple regression procedures. Estimates of h2 for BW and WW were .28 and .28 respectively, by the paternal half-sib procedure and .45 and .88, respectively, based on full-sibs. Repeatability estimates were .21 for BW and .30 for WW. Heritabilities based on regression of offspring on dam and offspring on sire were .45 and .21 for BW and .28 and .06 for WW, respectively. Negative correlations were found between solutions for additive genetic direct and additive maternal effects (rG). Estimates of rG ranged from -.86 to -1.05 for BW and from -.57 to -.79 for WW. Estimates of heritability for direct effects (h2o), for maternal effects (h2m) and for total additive genetic effects (h2T) were .16 to .27, .18 to .63 and -.02 to .05 for BW and .26 to .32, .27 to .67 and .10 to .20 for WW. Dominance affected both direct and maternal effects for BW and WW. Values of -.15 (BW) and -.25 (WW) were found for fm (path coefficient between the maternal phenotypes of dam and daughter). These results indicated that selection response would be decreased due to the negative genetic correlation between direct and maternal effects.  相似文献   

20.
Native chicken breeding station of Mazandaran was established in 1988 with two main objectives: genetic improvement through selection programs and dissemination of indigenous Mazandarani birds. (Co)variance components and genetic parameters for economically important traits were estimated using (bi) univariate animal models with ASREML procedure in Mazandarani native chicken. The data were from 18 generations of selection (1988?C2009). Heritability estimates for body weight at different ages [at hatch (bw1), 8 (bw8), 12 (bw12) weeks of ages and sex maturation (wsm)] ranged from 0.24?±?0.00 to 0.47?±?0.01. Heritability for reproductive traits including age at sex maturation (asm); egg number (en); weight of first egg (ew1); average egg weight at 28 (ew28), 30 (ew30), and 32 (ew32) weeks of age; their averages (av); average egg weight for the first 12?weeks of production (ew12); egg mass (em); and egg intensity (eint) varied from 0.16?±?0.01 to 0.43?±?0.01. Generally, the magnitudes of heritability for the investigated traits were moderate. However, egg production traits showed smaller heritability compared with growth traits. Genetic correlations among egg weight at different ages were mostly higher than 0.8. On the one hand, body weight at different ages showed positive and relatively moderate genetic correlations with egg weight traits (ew1, ew28, ew30, ew32, ew12, and av) and varied from 0.30?±?0.03 to 0.59?±?0.02. On the other hand, low negative genetic correlations were obtained between body weight traits (bw1, bw8, bw12, and wsm) and egg number (en). Also, there is low negative genetic correlation (?24?±?0.04 to ?29?±?0.05) between egg number and egg weight. Therefore, during simultaneous selection process for both growth and egg production traits, probable reduction in egg production due to low reduction in egg number may be compensated by increases in egg weight.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号