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1.
The performance of the two‐trait animal model that regards the first parity and later parities as two different traits in estimating genetic parameters for number of born alive (NBA) was examined using real and simulated data. Genetic parameters for NBA were estimated in purebred Landrace and Large White pigs using a single‐trait repeatability model (Model 1) that regards all parities as the same trait and a two‐trait animal model (Model 2) that regards the first and the later parities as different traits. For Model 2, the permanent environmental effect was fitted to only the records of the later parities. Heritability for NBA estimated using Model 1 was 0.12 for Landrace and 0.11 for Large White. Estimated heritability for NBA of the first parity and the later parities was 0.21 and 0.16, respectively, for Landrace; 0.18 and 0.16, respectively, for Large White obtained using Model 2, and higher than those in both breeds obtained using Model 1. Further results based on data simulated using the Monte Carlo method suggest that estimated additive genetic variance could be more biased using Model 2 than Model 1.  相似文献   

2.
Genetic parameters were estimated for six reproductive traits related to farrowing events in Landrace and Large White pigs; total number born (TNB), number born alive (NBA), number stillborn (NSB), total litter weight at birth (LWB), mean litter weight at birth (MWB), and gestation length (GL). We analyzed 62,534 farrowing records for 10,637 Landrace dams and 49,817 farrowing records for 8,649 Large White dams. Estimated heritabilities of TNB, NBA, NSB, LWB, MWB, and GL by single‐trait repeatability model analyses were 0.12, 0.12, 0.08, 0.18, 0.19, and 0.29, respectively, in Landrace, and 0.12, 0.10, 0.08, 0.18, 0.16, and 0.34, respectively, in Large White. Genetic correlation between NBA and NSB was unfavorable: 0.20 in Landrace and 0.33 in Large White. Genetic correlations of GL with the other five traits were weak: from ?0.18 with NSB to ?0.03 with NBA in Landrace, and from ?0.22 with NSB to ?0.07 with NBA in Large White. LWB had a highly favorable genetic correlation with NBA (0.74 in both breeds), indicating the possibility of using LWB for the genetic improvement of NBA.  相似文献   

3.
Comparison of the multi‐trait animal model and the traditional repeatability model was carried out using data obtained from 6,424 Landrace and 20,835 Yorkshire sows farrowed from January 2000 to April 2018 in order to estimate genetic parameters for litter traits at different parities. Specifically, records of the total number born (TNB), number born alive (NBA), total number of mortality (MORT), number of stillborn (NSB) and number of mummified pigs (MUM) were used. Although results showed the heterogeneity of heritability for litter traits at different parities, the mean heritability estimates from the multi‐trait model were found to be higher than those of the repeatability model for all traits in both pig breeds. In terms of genetic correlation between parities, a slight difference in genetic control in the first parity was noted for TNB and NBA in Landrace and Yorkshire pigs. The correlation between the first parity and later parities ranged from 0.48 to 0.74 for TNB and NBA in both breeds. Moreover, genetic correlation between parities for MORT and NSB was observed to be high for parities higher than 2 in Yorkshire pigs. For MUM, genetic correlation between the first and other parities was generally low in both breeds, indicating that culling pigs on the basis of MUM at the first parity could probably be unreasonable. Overall, the results of this study suggest that the multi‐trait approach for litter size traits is useful for the accurate estimation of genetic parameters.  相似文献   

4.
We estimated genetic parameters in Landrace and Large White pig populations for litter traits at farrowing (total number born, number born alive, number stillborn, total litter weight at birth (LWB), and mean litter weight at birth) and those at weaning (litter size at weaning (LSW), total litter weight at weaning (LWW), mean litter weight at weaning (MWW), and survival rate from farrowing to weaning). We analyzed 65,579 records at farrowing and 6,306 at weaning for Landrace, and 52,557 and 5,360, respectively, for Large White. Single‐trait and two‐trait repeatability animal models were exploited to estimate heritability and genetic correlation respectively. Heritability estimates of LSW were 0.09 for Landrace and 0.08 for Large White. Genetic correlations of LSW with MWW were –0.43 for Landrace and –0.24 for Large White. Genetic correlations of LSW with LWW and LWB ranged from 0.5 to 0.6. The genetic correlation of MWW with LWW was positive, but that with LWB was negligible. The results indicate that utilizing LWW or LWB could improve LSW efficiently, despite the antagonistic genetic correlation between LSW and MWW.  相似文献   

5.
Genetic parameters for sow stayability were estimated from farrowing records of 10,295 Landrace sows and 8192 Large White sows. The record for sow stayability from parity k to parity k + 1 (k = 1, …, 6) was 0 when a sow had a farrowing record at parity k but not at parity k + 1, and 1 when a sow had both records. Heritability was estimated by using single-trait linear and threshold animal models. Genetic correlations among parities were estimated by using two-trait linear–linear and single-trait random regression linear animal models. Genetic correlations with litter traits at birth were estimated by using a two-trait linear–linear animal model. Heritability estimates by linear model analysis were low (0.065–0.119 in Landrace & 0.061–0.157 in Large White); those by threshold model analysis were higher (0.136–0.200 & 0.110–0.283). Genetic correlations among parities differed between breeds and models. Genetic correlation between sow stayability and number born alive was positive in many cases, implying that selection for number born alive does not reduce sow stayability. The results seem to be affected by decisions on culling made by farmers.  相似文献   

6.
A total of 66,620 records from the first six parities for number of piglets born alive (NBA) from 20,120 Landrace sows and 24,426 records for weight (WT) and backfat thickness (BT) at 175 d of age were analyzed to estimate genetic parameters. The pedigree consisted of 47,186 individuals, including 392 sires and 5,394 dams. Estimates were based on marginal posterior distribution of the genetic parameters obtained using Bayesian inference implemented via the Gibbs sampling procedure with a Data Augmentation step. The posterior means and posterior standard deviation (PSD) for heritability of NBA ranged from 0.064 (PSD 0.005) in the first parity to 0.146 (PSD 0.019) in the sixth parity, always increasing with the order of the parity. The posterior means for genetic correlations of litter size between adjacent parities were, in most cases, greater than 0.80. However, genetic correlation were much lower between nonadjacent parities. For example, the genetic correlation was 0.534 (PSD 0.061) between the fourth and the sixth parity for NBA. The posterior means of heritability for WT and BT were 0.229 (PSD 0.018) and 0.350 (PSD 0.019), respectively. Posterior mean for genetic correlation between WT and BT was 0.339 (PSD 0.044). The posterior means for genetic correlation between production (WT and BT) and reproduction traits (NBA in different parities) were close to zero in most cases. Results from this study suggest that different parities should be considered as different traits. Moreover, selection for growth and backfat should result in no or very little correlated response in litter size.  相似文献   

7.
Heritabilities and genetic correlations for different prolificacy traits were estimated to assess possibilities of selection for high number of piglets weaned. Three litter-size traits: total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets weaned (NW); four piglet survival traits: number of stillborn piglets (NSB), percent of stillborn piglets (NSB%), piglet mortality between birth and weaning (PM), percent of dead piglets during suckling (PM%); and three traits measuring time intervals: age at first farrowing (AFF), first farrowing interval (FFI), and gestation length (GL) were analysed. The Finnish national litter recording scheme provided data on the first parity litters of 11 329 Landrace and 8 362 Large White pigs born between 1986 and 2000. The heritabilitiy estimates were moderate for AFF and GL (0.24–0.37), and low for all the other traits (0.03–0.11). The genetic correlations between TNB and PM (0.68 in Landrace and 0.43 in Large White) and between NBA and PM (0.64 in Landrace and 0.31 in Large White) suggest that selection only for high TNB or NBA will lead to increased PM. The results showed further that GL will increase indirectly if the selection pressure is for low PM (r g =?0.050 in Landrace and ?0.43 in Large White.  相似文献   

8.
Reproduction is a complex trait, controlled by genetic and environmental factors. Genetic improvement of this trait is important for animal breeders to improve the animal's production efficiency. Apart from genetic factors, animal production can be affected by environmental factors, i.e. the nursing ability of the sow, which is in turn affected directly by effective teat number (teats producing milk normally, TN) and number of piglets born alive (NBA). The objective of this study was to find new mutations, such as single nucleotide polymorphisms (SNPs) from the Zona Pellucida glycoprotein gene (ZP3) using Single Strand Chain Polymorphism (SSCP) and nucleotide sequencing and to investigate association between genetic variations and sow reproductive traits. We identified 13 new SNPs from exon 1, two new SNPs from intron 2, one SNP from intron 6 and a 18 bp (GCACGTGGTCCTCCTGG)‐deletion/insertion from intron 2 of the ZP3 gene. Five out of these mutations were selected to genotype in five different breeds (Small Meishan, Qingping, Duroc, Landrace and Large White) and association with reproductive traits in European breeds (Duroc, Landrace and Large White). The sows with genotype AA had more 1.11 piglets NBA than of the sows with genotype AB (p < 0.05) in the 18 bp deletion/insertion of intron 2, while non‐significant associations between the other mutations and reproductive traits (NBA and TN) were found.  相似文献   

9.
Direct selection for litter size or weight at weaning in pigs is often hindered by external interventions such as cross‐fostering. The objective of this study was to infer the causal structure among phenotypes of reproductive traits in pigs to enable subsequent direct selection for these traits. Examined traits included: number born alive (NBA), litter size on day 21 (LS21), and litter weight on day 21 (LW21). The study included 6,240 litters from 1,673 Landrace dams and 5,393 litters from 1,484 Large White dams. The inductive causation (IC) algorithm was used to infer the causal structure, which was then fitted to a structural equation model (SEM) to estimate causal coefficients and genetic parameters. Based on the IC algorithm and temporal and biological information, the causal structure among traits was identified as: NBA → LS21 → LW21 and NBA → LW21. Owing to the causal effect of NBA on LS21 and LW21, the genetic, permanent environmental, and residual variances of LS21 and LW21were much lower in the SEM than in the multiple‐trait model for both breeds. Given the strong effect of NBA on LS21 and LW21, the SEM and causal information might assist with selective breeding for LS21 and LW21 when cross‐fostering occurs.  相似文献   

10.
Up to 109,447 records of 49,656 Large White sows were used to evaluate the genetic relationship between number of pigs born dead (BD) and number born alive (BA) in first and later parities. Performance data (n = 30,832) for ultrasound backfat (BF) at the end of the test and days to reach 113.5 kg (AD) were used to estimate their relationships with BD and BA at first parity in a four-trait threshold-linear analysis (TL). Effects were year-farm, contemporary group (CG: farm-farrowing year-farrowing month) and animal additive genetic. At first parity, estimates of heritability were 0.09, 0.09, 0.37, and 0.31 for BA, BD, AD, and BF, respectively. The estimate of genetic correlation between BD and litter size was -0.04 (BD-BA). Corresponding values with test traits were both -0.14 (BD-AD, BD-BF). Estimates of genetic correlation between BA and performance traits were 0.08 (BA-AD) and 0.05 (BA-BF). The two test traits were moderately negatively correlated (-0.22). For later parities, a six-trait (BD, BA in three parities) TL model was implemented. The estimates of additive genetic variances and heritability increased with parity for BD and BA. Estimates of heritabilities were: 0.09, 0.10, and 0.11 for BD, and 0.09, 0.12, and 0.12 for BA in parities one to three, respectively. Estimates of genetic correlations between different parities were high (0.91 to 0.96) for BD, and slightly lower (0.74 to 0.95) for BA. Genetic correlations between BD and BA were low and positive (0.02 to 0.17) for BA in Parities 1 and 2, but negative (-0.04 to -0.10) for BA in Parity 3. Selection for increased litter size should have little effect on farrowing piglet mortality. Intense selection for faster growth and increased leanness should increase farrowing piglet mortality of first-parity sows. A repeatability model with a simple correction for the heterogeneity of variances over parities could be implemented to select against farrowing mortality. The genetic components of perinatal piglet mortality are independent of the ones for litter size in the first parity, and they show an undesirable, but not strong, genetic association in second parity.  相似文献   

11.
The objective of this study was to estimate genetic parameters and breeding values for the twinning rate of the first three parities (T1, T2 and T3) and 305‐day milk yield in first lactation (MY), using a four‐trait threshold‐linear animal model in Japanese Holsteins. Data contained 1 323 946 cows calving between 1990 and 2007. Twinning was treated as a binary character: ‘single’ or ‘twin or more’. Reported T1, T2 and T3 were 0.70%, 2.87%, and 3.73%, respectively. Individual 305‐day milk yield was computed using a multiple trait prediction for cows with at least eight test‐day records. (Co)variance components were estimated via Gibbs sampling for randomly sampled subsets. Posterior means of heritabilities for T1, T2 and T3 were 0.11, 0.16 and 0.14, respectively. Genetic correlations between parities were 0.92 or greater. Genetic correlations of MY with twinning rate were not ‘significant’ (i.e. their 95% highest probability density intervals contained zeros). Multiple births at different parities were considered as the same genetic trait. The average evaluations of T1 (T2) for sires born before 1991 was 0.48% (2.25%) compared with a mean of 0.76% (3.37%) for sires born after 1992. A recent increase in the reported twinning rate reflects the positive genetic trend for sires in Japanese Holsteins.  相似文献   

12.
FSHβ基因的多态性分布及其对大白猪产活仔数的影响   总被引：2，自引：2，他引：0  
为了研究猪繁殖性状候选主效基因FSHβ在大白猪不同胎次中的遗传效应,并应用于大白猪繁殖性状的遗传改良,采用PCR方法检测了该基因在2个大白猪育种群共802头母猪中的多态性分布,并分析了其对产活仔数的影响,其中湖北天种公司大白猪群体样本数为472头,分析统计胎次1774胎,等位基因A的频率为0.447、等位基因B的频率为0.553;宜昌正大公司大白猪群为330头,分析统计胎次1644胎,等位基因A、B的频率分别为0.312、0.688。分析该位点的多态性与产活仔数的关系,结果发现,头胎不同基因型对产活仔数的影响为ABBBAA,二胎为AAABBB,经产胎次和所有胎次均为ABAABB,但差异均不显著。综合分析结果表明,A等位基因对大白猪产活仔数的影响要优于B等位基因,AB基因型母猪的产活仔数要优于其他2种基因型,提高生产猪群该基因的杂合子个体数比例有望取得更大的经济效益。  相似文献   

13.
The objective of this study was to estimate genetic associations of prolificacy traits with other traits under selection in the Finnish Landrace and Large White populations. The prolificacy traits evaluated were total number of piglets born, number of stillborn piglets, piglet mortality during suckling, age at first farrowing, and first farrowing interval. Genetic correlations were estimated with two performance traits (ADG and feed:gain ratio), with two carcass traits (lean percent and fat percent), with four meat quality traits (pH and L* values in longissimus dorsi and semimembranosus muscles), and with two leg conformation traits (overall leg action and buck-kneed forelegs). The data contained prolificacy information on 12,525 and 10,511 sows in the Finnish litter recording scheme and station testing records on 10,372 and 9,838 pigs in Landrace and Large White breeds, respectively. The genetic correlations were estimated by the restricted maximum likelihood method. The most substantial correlations were found between age at first farrowing and lean percent (0.19 in Landrace and 0.27 in Large White), and fat percent (-0.26 in Landrace and -0.18 in Large White), and between number of stillborn piglets and ADG (-0.38 in Landrace and -0.25 in Large White) and feed:gain (0.27 in Landrace and 0.12 in Large White). The correlations are indicative of the benefits of superior growth for piglets already at birth. Similarly, the correlations indicate that age at first farrowing is increasing owing to selection for carcass lean content. There was also clear favorable correlation between performance traits and piglet mortality from birth to weaning in Large White (r(g) was -0.43 between piglet mortality and ADG, and 0.42 between piglet mortality and feed:gain), but not in Landrace (corresponding correlations were 0.26 and -0.22). There was a general tendency that prolificacy traits were favorably correlated with performance traits, and unfavorably with carcass lean and fat percents, whereas there were no clear associations between prolificacy and meat quality or leg conformation. In conclusion, accuracy of estimated breeding values may be improved by accounting for genetic associations between prolificacy, carcass, and performance traits in a multitrait analysis.  相似文献   

14.
The aim of this study was to estimate genetic parameters of seven traits related to sow reproductive performance. Data on all Norwegian Landrace pigs (NL) born in nucleus herds and raised in nucleus or multiplying herds from 1990 to 2000 were extracted from the Norwegian national recording scheme. Reproductive traits investigated were age at first service (AFS), return rate in gilts (RRg), age at first farrowing (AFF), live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), return rate after first litter (RR1), live-born piglets in the second litter (NBA2), and interval from weaning to first service after second litter (WTS2). After editing, the data set comprised 12,583 to 56,042 records, depending on the trait. A mixed linear and a joint linear threshold animal model were used to estimate (co)variance components. A full Bayesian approach via Gibbs sampling was adopted. The statistical model used for analysis included contemporary groups of herd-year (-season), purebred or crossbred litter, single or double insemination, mating type, parity in which the animal was born, a regression on lactation length, and an additive genetic effect. Neither the estimated heritabilities nor the genetic correlations differed much between the two approaches, but there was a tendency for higher genetic correlations using the joint linear threshold model approach. Average heritabilities were as follows: AFS = 0.31; RRg = 0.03; RR1 = 0.02; NBA1 = 0.12; NBA2 = 0.14; WTS1 = 0.08; and WTS2 = 0.03. The highest genetic correlations were estimated between NBA1 and NBA2 (r(g) = 0.95), RR1 and WTS1 (r(g) = 0.93), and between WTS1 and WTS2 (r(g) = 0.78). The estimated genetic correlation between NBA and WTS were close to zero. Selection for increased NBA will slightly increase AFS and reduce the probability of a return. Selection for decreased AFS will have a favorable effect on WTS intervals; however, selection for decreased AFS seems to have an unfavorable effect on return rate both on gilts and sows. Conversely, selection for decreased WTS intervals will reduce the probability of a return. Potential selection candidates to include in a multivariate fertility index are AFS, NBA, and WTS1. Due to the low heritability and low, but favorable, genetic correlations to NBA and WTS, RR is not recommended as a selection candidate.  相似文献   

15.
Genetic parameters and trends in the average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP), and age at 90 kg (D90) were estimated for populations of Landrace and Yorkshire pigs. Additionally, the correlations between these production traits and litter traits were estimated. Litter traits included total born (TB) and number born alive (NBA). The data used for this study were obtained from eight farms during 1999 to 2016. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while bivariate analyses were performed to estimate the correlations between production and litter traits. The heritability estimates were 0.52 and 0.43 for ADG; 0.54 and 0.45 for BF; 0.25 and 0.26 for LMA; 0.54 and 0.48 for LP; and 0.56 and 0.46 for D90 in the Landrace and Yorkshire breeds, respectively. The ADG and D90 showed low genetic correlation with BF and LP. The LMA had ?0.40, ?0.32, 0.49, and 0.39 genetic correlations with ADG, BF, LP, and D90, respectively. Genetic correlations between production and litter traits were generally low, except for the correlations between LMA and TB (?0.23) in Landrace and ADG and TB (?0.16), ADG and NBA (?0.18), D90 and TB (0.19), and D90 and NBA (0.20) in Yorkshire. Genetic trends in production traits were all favorable except for LMA.  相似文献   

16.
Performance test records from on-farm tests of young Polish Large White boars and reproductive records of Polish Large White sows from 94 nucleus farms during 1978 to 1987 were used to estimate population parameters for the measured traits. The number of boar performance records after editing was 114,347 from 3,932 sires, 21,543 dams, 44,493 litters and 1,075 herd-year-seasons. Reproductive performance records of sows involved 41,080 litters from 2,348 sires, 18,683 dams and 1,520 herd-year-seasons. Both data sets were analyzed by using restricted maximum-likelihood programs. The model used for the performance records included fixed herd-year-seasons, random sires, dams and error effects, and covariances for the year of birth of sire and year of birth of dam. The model used for the reproduction data set was the same as the performance data with parity as an additional fixed effect. Estimated heritabilities were .27, .29, .26, .07, .06, .06 for average daily gain standardized to 180 d (ADG), backfat thickness standardized to 110 kg BW (BF), days to 110 kg (DAYS), litter size at birth born alive (NBA), litter size at 21 d (N21) and litter weight at 21 d (W21), respectively. Estimated common environmental effects for the same traits were .09, .10, .09, .06, .07 and .08, respectively. Genetic correlations were .25 (ADG and BF), -.99 (ADG and DAYS), -.21 (BF and DAYS), .91 (NBA and N21), .68 (NBA and W21) and .80 (N21 and W21). The respective phenotypic correlations were .23, -.99, -.20, .88, .75, .86. These population parameters for Polish Large White pigs are similar to those for breeds in other countries.  相似文献   

17.
A Bayesian threshold model was fitted to analyze the genetic parameters for farrowing mortality at the piglet level in Large White, Landrace, and Pietrain populations. Field data were collected between 1999 and 2006. They were provided by 3 pig selection nucleus farms of a commercial breeding company registered in the Spanish Pig Data Bank (BDporc). Analyses were performed on 3 data sets of Large White (60,535 piglets born from 4,551 litters), Landrace (57,987 piglets from 5,008 litters), and Pietrain (42,707 piglets from 4,328 litters) populations. In the analysis, farrowing mortality was considered as a binary trait at the piglet level and scored as 1 (alive piglet) or 0 (dead piglet) at farrowing or within the first 12 h of life. Each breed was analyzed separately, and operational models included systematic effects (year-season, sex, litter size, and order of parity), direct and maternal additive genetic effects, and common litter effects. Analyses were performed by Bayesian methods using Gibbs sampling. The posterior means of direct heritability were 0.02, 0.06, and 0.10, and the posterior means of maternal heritability were 0.05, 0.13, and 0.06 for Large White, Landrace, and Pietrain populations, respectively. The posterior means of genetic correlation between the direct and maternal genetic effects for Landrace and Pietrain populations were -0.56 and -0.53, and the highest posterior intervals at 95% did not include zero. In contrast, the posterior mean of the genetic correlation between direct and maternal effects was 0.15 in the Large White population, with the null correlation included in the highest posterior interval at 95%. These results suggest that the genetic model of evaluation for the Landrace and Pietrain populations should include direct and maternal genetic effects, whereas farrowing mortality could be considered as a sow trait in the Large White population.  相似文献   

18.
To study the genetic relationship between three grouped reasons for sow removal (SR) in consecutive parities, accounting for censoring, 13,838 records from Large White sows were analyzed. Data were from seven pure-line farms having, on average, 5.9% unknown SR. Three traits were subjectively defined, each corresponding to a classification of SR (reproductive [RR], nonreproductive [RN], and others [RO]). Records for each trait could take one of five categories, according to parity at removal (0 to 4 or later). A multivariate linear censored model was implemented. The model to estimate (co)variance components and parameters included the effects of year-season, region, contemporary group, and additive genetic effects. The most common SR was related to reproduction (48.5%). Diseases of different origin and cause, old age/parity, and sow death or loss accounted for about 18, 7, and 4% of total culls, respectively. Estimates of variance components showed heterogeneity of additive genetic and residual variances for the three traits. Estimates of heritability were 0.18, 0.13, and 0.15 for RR, RN, and RO, respectively. Genetic correlations between removal codes were high (> or =0.90). Results suggest sizeable additive genetic variances exist for parity at removal and different codes of removal. Different SR reasons seem to operate similarly or as a closely related genetic trait associated with fitness. In particular, RN and RO seem to be genetically indistinguishable. Data structure, definition, and volume are major limitations in studies of sow survival. A multiple-trait censored model is preferred to evaluate reasons of sow disposal. Grouped removal causes seem to be strongly genetically correlated but with heterogeneous variances, suggesting that combining all removal causes and treating the trait as parity at disposal is an alternative approach.  相似文献   

19.
Selection for total number of piglets born (TNB) since 1992 has led to a significant increase in this trait in Danish Landrace and Danish Yorkshire but has also been accompanied by an increase in piglet mortality. The objective of this study was to estimate the genetic and phenotypic parameters for litter size and survival to find alternative selection criteria to improve litter size at weaning. Data from Landrace (9,300 litters) and Yorkshire (6,861 litters) were analyzed using REML based on a linear model including genetic effects of sow and service-sire. The estimates of heritability (based on the sow component) for TNB, number born alive (NBA), and number alive at d 5 after birth (N5D) and at weaning (about 3 wk, N3W) ranged from 0.066 to 0.090 in Landrace and 0.050 to 0.070 in Yorkshire. Genetic correlations between TNB and N3W were 0.289 in Landrace and 0.561 in Yorkshire, but between N5D and N3W the estimated genetic correlation was 0.995 in both populations. The approximate estimates of heritability for survival rate per litter at birth (SVB = NBA/TNB), from birth to d 5 (SV5 = N5D/NBA), and from d 5 to weaning (SVW = N3W/N5D) were 0.130, 0.131, and 0.023, respectively, in Landrace, and 0.095, 0.043, and 0.009, respectively, in Yorkshire. Genetic correlations between TNB and survival rates at different stages were negative. On the other hand, genetic correlations between N5D and survival rates and between N3W and survival rates were strongly or moderately positive, except for the correlations with SVW in Yorkshire. The results suggest that selection for N5D could be an interesting alternative to improve litter size at weaning and piglet survival for Danish Landrace and Danish Yorkshire.  相似文献   

20.
Data from Thai Landrace sows were used to estimate genetic parameters for reproduction and production traits in first and later parities. The reproduction traits investigated were total number of piglets born per litter (TB), number of stillborn piglets (SB), and number of piglets born alive but dead within 24 h (BAD). The reproduction data pertained to 12,603 litters born between 1993 and 2005. The production measures were ADG and backfat thickness (BF); these were recorded in 4,163 boars and 15,171 gilts. Analyses were carried out with a multivariate animal model using average information REML procedures. Heritability estimates of reproduction traits for first parity were 0.03 +/- 0.02 for TB, 0.04 +/- 0.02 for SB, and 0.06 +/- 0.02 for BAD. For later parities, they were 0.07 +/- 0.01 for TB, 0.03 +/- 0.04 for SB, and 0.02 +/- 0.01 for BAD. Heritability estimates for production traits were 0.38 +/- 0.02 for ADG and 0.61 +/- 0.02 for BF. Genetic correlations between ADG and TB tended to be favorable, and genetic correlations between BF and TB tended to be unfavorable in all parities. However, BF was genetically correlated unfavorably with SB in later parities, and the genetic correlations between TB and BAD tended to be unfavorable in all parities. The genetic correlations of TB, SB, and BAD between first and later parities were 0.85 +/- 0.13, 0.79 +/- 0.16, and 0.71 +/- 0.24, respectively. Selection for high growth rate will probably increase TB, and selection for low BF will decrease TB and increase SB. The results obtained also indicated that BAD will increase if there is selection pressure for high TB.  相似文献   

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