Genetic correlations between gestation length, piglet survival and early growth

This study is based on 12708 first-parity and 7062 second-parity Yorkshire litters from Swedish nucleus herds; and on 1037 first-parity Yorkshire litters from an experimental herd. Gestation length was analysed together with litter size, piglet mortality and average piglet growth rate. A sire–dam model was used to estimate direct (litter) and maternal (sow) genetic effects. Direct heritability for gestation length was 0.3. Maternal heritability was estimated at 0.2 in nucleus data and 0.3 in experimental data. The maternal genetic correlation between gestation length and litter size was negative. The genetic correlations between gestation length and number stillborn were not consistent between the two data sets. Genetic correlations between gestation length and number dead after birth were negative. Genetic correlations between gestation length and average birth weight and piglet growth rate were positive. We conclude that gestation length is influenced by the genotype of the piglets and the genotype of the sow. Selection for prolonged gestation would probably improve piglet survival after birth and piglet growth; it might, however, result in more stillbirths.     

Genetic parameters for within-litter variation in piglet birth weight and change in within-litter variation during suckling

The objective of this study was to ascertain whether maternal additive genetic variance exists for within-litter variation in birth weight and for change in within-litter variation in piglet weight during suckling. A further objective was to estimate maternal genetic correlations of these two traits with mortality, birth weight, growth, and number of piglets born alive. Data were obtained from L?vsta research station, Swedish University of Agricultural Sciences, and included 22,521 piglets born in 2,003 litters by 1,074 Swedish Yorkshire sows. No cross fostering was used in the herd. The following seven traits were analysed in a multivariate animal (sow) model: number of piglets born alive, within-litter SD in birth weight, within-litter SD in piglet weight at 3 wk of age, mean weight at birth, mean weight at 3 wk of age, proportion of stillborn piglets, and proportion of dead piglets during suckling. Maternal genetic variance for the change in within-litter SD in piglet weight during suckling was assessed from the estimated additive genetic covariance components by conditioning on within-litter SD in birth weight. Similarly, mean growth of piglets during suckling was assessed from the additive genetic covariance components by conditioning on mean weight at birth. The heritability for within-litter SD in birth weight was 0.08 and 0.06 for within-litter SD in piglet weight at 3 wk. The genetic correlation between these two traits was 0.71. Little maternal genetic variance was found for the change in within-litter SD in piglet weight during suckling, and opportunity for genetic improvement of this trait by selective breeding seems limited. The genetic correlation of within-litter SD in birth weight with proportion of dead piglets during suckling was 0.25 and of within-litter SD in birth weight with mean growth of piglets was -0.31. The maternal genetic variance and heritability found for within-litter SD in birth weight indicates that genetic improvement of this trait by selective breeding is possible. In addition, selection for sows' capacity to give birth to homogeneous litters may be advantageous for piglet survival, piglet growth, and litter homogeneity at weaning.     

Genetic study of individual preweaning mortality and birth weight in Large White piglets using threshold-linear models

Individual records from 49,788 Large White piglets were used to evaluate preweaning mortality and its relationship with birth weight (BW). Preweaning mortality included farrowing mortality (TM) was also divided into stillbirth (SB), early (EM), late (LM) and total (ELM) preweaning mortality. Farrowing mortality was also studied as a sow's trait as number of piglets born dead (NBD). Threshold-linear models were used via MCMC. Traits included (1) TM-BW, (2) SB-ELM-BW, (3) SB-EM-LM and (4) NBD-ELM-BW. Model for BW included parity number, litter size, sex, contemporary group (farm-farrowing year-month), litter, and direct and maternal additive genetic effects. For mortality traits, litter effect was of the nursing litter for cross-fostered piglets (4.9%). Models for SB (2, 3) and NBD (4) excluded the effect of sex. In Model 3, BW was fitted as covariable for EM and LM. Estimates of direct and maternal heritability for BW were 0.03–0.06 and 0.14–0.19; and for mortality traits 0.03–0.12 and 0.08–0.12. Direct-maternal correlations were negative for all traits. Genetic correlations between all mortality traits were positive. Results confirmed the importance of BW for the genetic evaluation of piglet mortality. Early mortality is a good candidate for improvement of TM because of larger heritability and high genetic correlations with other mortality traits. It is most efficient to treat SB at sow level and preweaning mortality at the piglet level.     

Selection for litter size at day five to improve litter size at weaning and piglet survival rate

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.     

Direct,maternal and nurse sow genetic effects on farrowing-, pre-weaning- and total piglet survival

Peri- and postnatal survival data, including birth weights and cross-foster information from two line/farm combinations with 33 717 and 29 200 piglets, respectively, were analyzed to find the best genetic model to describe piglet survival. This was done in terms of direct (piglet), maternal and nurse sow genetic effects, maternal to cover uterine quality and nurse sow to cover mothering ability. The two component traits, farrowing and pre-weaning survival and — birth weight, the most important factor for survival — were similarly analyzed. As fixed effects, Year/Season, cross, parity, birth weight in classes of 100 g, litter size as such, and sex were included in the analyses. Models combining the different genetic effects were compared on the basis of the log-likelihood. A maternal/nurse sow model fitted the data best for pre-weaning survival, a direct/maternal model for birth weight, a direct model for farrowing survival in the dam line and a direct/maternal model for farrowing survival in the sire line. Including nurse sow effect in a model for piglet survival as a whole gave erratic results, making it difficult to define an optimal model. Estimated heritabilities for pre-weaning survival, measured on the binary scale, in the dam line were 0.02±0.005 for both maternal and nurse sow effects. Heritabilities for birth weight were, on average for the two lines, 0.04±0.01 for the direct effect and 0.20±0.03 for the maternal effect. In conclusion, selection for increased component traits of piglet survival is possible.     

Heritability and genetic correlation estimates of semen production traits with litter traits and pork production traits in purebred Duroc pigs

We estimated heritabilities of semen production traits and their genetic correlations with litter traits and pork production traits in purebred Duroc pigs. Semen production traits were semen volume, sperm concentration, proportion of morphologically normal sperms, total number of sperm, and total number of morphologically normal sperm. Litter traits at farrowing were total number born, number born alive, number stillborn, total litter weight at birth, mean litter weight at birth, and piglet survival rate at birth. Litter traits at weaning were litter size at weaning, total litter weight at weaning, mean litter weight at weaning, and piglet survival rate from birth to weaning. Pork production traits were average daily gain, backfat thickness, and loin muscle area. We analyzed 45,913 semen collection records of 896 boars, 6,950 farrowing performance records of 1,400 sows, 2,237 weaning performance records of 586 sows, and individual growth performance records of 9,550 animals measured at approximately 5 mo of age. Heritabilities were estimated using a single-trait animal model. Genetic correlations were estimated using a 2-trait animal model. Estimated heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of estimated genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.     

Genetic Parameters for the Piglet Mortality Traits Crushing,Stillbirth and Total Mortality,and their Relation to Birth Weight

The aim of this study was to estimate genetic and phenotypic parameters for the three mortality traits crushing, stillbirth and total mortality in piglets, and their respective correlations with birth weight. Records were available from 11 016 Yorkshire piglets from 1046 first parity litters in a Swedish experimental herd. Each mortality trait was analysed jointly with birth weight, using bivariate models. Both mixed linear models and threshold models were used. The threshold models took environmental and maternal genetic effects into account, whereas the linear models also included a direct genetic effect of the piglet on its birth weight. The estimated heritabilities were low for all mortality traits (0.01-0.15), with the lowest estimate for crushing and the highest for stillbirth. The estimated environmental correlations between the different mortality traits and birth weight were negative. The estimated genetic correlations between crushing and birth weight (both direct and maternal effect) were also negative in both models, indicating that sows with low-weight piglets are more likely to crush piglets. However, the genetic correlations between stillbirth and birth weight (both direct and maternal effect) were positive. These results suggest that stillbirth and crushing are traits with different genetic backgrounds, and that genetically increasing the birth weight of the piglets may result in more stillborn piglets.     

Genetic relationship of litter traits between farrowing and weaning in Landrace and Large White pigs

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.     

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

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.     

Within-litter variation of birth weight in hyperprolific Czech Large White sows and its relation to litter size traits, stillborn piglets and losses until weaning

Data from about 2900 litters (approximately 40,000 piglets) originating from 1063 Czech Large White hyperprolific sows were analyzed. The phenotypic and genetic relations between litter size traits, piglet mortality during farrowing and from birth to weaning and several statistics referring to the distribution of the birth weight within litter were analyzed. All genetic parameters were estimated from multi-trait animal models including the following factors: mating type (natural service or insemination), parity, linear and quadratic regression on age at first farrowing (1st litter) or farrowing interval (2nd and subsequent litters), herd-year-season effect and additive-genetic effect of the sow. The phenotypic correlations of the mean birth weight with the total number of piglets born and piglets born alive were − 0.30. Traits describing the variability of the birth weight within litter (range, variance, standard deviation, coefficient of variation) were mostly positively correlated with litter size. A statistically significant phenotypic correlation (− 0.09 to − 0.15) between mean birth weight and losses at birth and from birth to weaning was found. The heritability for the number of piglets born, piglets born alive and piglets weaned was around 0.15. The number of stillborn piglets had only a very low heritability less than 0.05, whereas the heritability for losses from birth to weaning was 0.13. The heritabilities of the mean, minimal and maximal birth weight were 0.16, 0.10 and 0.10, respectively. The heritability for all statistics and measures referring to the variability of the birth weight within litter was very low and did never exceed the value of 0.05. An increase in litter size was shown to be genetically connected with a decrease in the mean piglet birth weight and an increase in the within-litter variability of birth weight. Selection on litter size should be accompanied by selection on mortality traits and/or birth-weight traits. Losses from birth to weaning and the minimal birth weight in the litter were proposed as potential traits for a selection against piglet mortality.     

Correlated responses for litter traits to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Effects of selection for reproductive traits were estimated using data from 3 pig lines derived from the same Large White population base. Two lines were selected for 6 generations on high ovulation rate at puberty (OR line) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS line). The third line was an unselected control line. Genetic parameters for age and BW at puberty (AP and WP); number of piglets born alive, weaned, and nurtured (NBA, NW, and NN, respectively); proportions of stillbirth (PSB) and survival from birth to weaning (PSW); litter and average piglet BW at birth (LWB and AWB), at 21 d (LW21 and AW21), and at weaning (LWW and AWW) were estimated using REML methodology. Heritability estimates were 0.38 +/- 0.03, 0.46 +/- 0.03, 0.16 +/- 0.01, 0.08 +/- 0.01, 0.09 +/- 0.01, 0.04 +/- 0.01, 0.04 +/- 0.02, 0.19 +/- 0.02, 0.10 +/- 0.02, 0.10 +/- 0.02, 0.36 +/- 0.02, 0.27 +/- 0.01, and 0.24 +/- 0.01 for AP, WP, NBA, PSB, NW, NN, PSW, LWB, LW21, LWW, AWB, AW21, and AWW, respectively. The measures of litter size showed strong genetic correlations (r(a) >/= 0.95) and had antagonistic relations with PSB (r(a) = -0.59 to -0.75) and average piglet BW (r(a) = -0.19 to -0.46). They also had strong positive genetic correlations with prenatal survival (r(a) = 0.67 to 0.78) and moderate ones with ovulation rate (r(a) = 0.36 to 0.42). Correlations of litter size with PSW were negative at birth but positive at weaning. The OR and PS lines were negatively related to PSW and average piglet BW. Puberty traits had positive genetic correlations with OR and negative ones with PS. Genetic trends were estimated by computing differences between OR or PS and control lines at each generation using least squares and mixed model methodologies. Average genetic trends were computed by regressing line differences on generation number. Significant (P < 0.05) average genetic trends were obtained in OR and PS lines for AP (respectively, 2.1 +/- 0.9 and 3.2 +/- 1.0 d/generation) and WP (respectively, 2.0 +/- 0.5 and 1.8 +/- 0.5 d/generation) and in the PS line for NBA (0.22 +/- 0.10 piglet/generation). Tendencies (P < 0.10) were also observed for LWB (0.21 +/- 0.12 kg/generation) and AWW (-0.25 +/- 0.14 kg/generation) in the PS line. Selection on components of litter size can be used to improve litter size at birth, but result in undesirable trends for preweaning survival.     

Genetic relationships between length of productive life and lifetime production efficiency in a commercial swine herd in Northern Thailand

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.     

Between-breed variability of stillbirth and its relationship with sow and piglet characteristics

Litter characteristics at birth were recorded in 4 genetic types of sows with differing maternal abilities. Eighty-two litters from F(1) Duroc x Large White sows, 651 litters from Large White sows, 63 litters from Meishan sows, and 173 litters from Laconie sows were considered. Statistical models included random effects of sow, litter, or both; fixed effects of sow genetic type, parity, birth assistance, and piglet sex, as well as gestation length, farrowing duration, piglet birth weight, and litter size as linear covariates. The quadratic components of the last 2 factors were also considered. For statistical analyses, GLM were first considered, assuming a binomial distribution of stillbirth. Hierarchical models were also fitted to the data to take into account correlations among piglets from the same litter. Model selection was performed based on deviance and deviance information criterion. Finally, standard and robust generalized estimating equations (GEE) procedures were applied to quantify the importance of each effect on a piglet's probability of stillbirth. The 5 most important factors involved were, in decreasing order (contribution of each effect to variance reduction): difference between piglet birth weight and the litter mean (2.36%), individual birth weight (2.25%), piglet sex (1.01%), farrowing duration (0.99%), and sow genetic type (0.94%). Probability of stillbirth was greater for lighter piglets, for male piglets, and for piglets from small or very large litters. Probability of stillbirth increased with sow parity number and with farrowing duration. Piglets born from Meishan sows had a lower risk of stillbirth (P < 0.0001) and were little affected by the sources of variation mentioned above compared with the 3 other sow genetic types. Standard and robust GEE approaches gave similar results despite some disequilibrium in the data set structure highlighted with the robust GEE approach.     

Analysis of birth weight variability in pigs with respect to liveborn and total born offspring

Reduction in the variability of piglet birth weight within litter and increased piglet survival are key objective in schemes aiming to improve sow prolificacy. In previous studies, variation in birth weight was described by the sample standard deviation of birth weights within one litter, and the genetic impact has been proved. In this study, we additionally considered the sex effect on piglet's birth weight and on its variability. The sample variance of birth weights per litter separated by sex was assigned as a trait of the sow. Different transformations of the trait were fitted by linear and generalized linear mixed models. Based on 1111 litters from Landrace sows, the estimates of heritability for the different measures ranged from 11 to 12%. We analysed the influence of including birth weight of stillborn piglets on the variability of birth weight within litter. With omitted stillborns, the heritability was estimated approximately 2% higher than that in investigations of all born piglets, and the impact of sex on birth weight variability was increased. Because the proportion of intrapartum deaths is rather high, it is recommended to consider the total number of piglets born per litter when analysing birth weight variation.     

Neonatal piglet traits of importance for survival in crates and indoor pens

The primary aim of the present study was to investigate whether the same piglet traits contributed to the same causes of neonatal piglet mortality in crates (CT) and pens (PN). Gilts originating from 2 distinct genetic groups that differed in breeding value for piglet survival rate at d 5 (SR5) were used. These were distributed to farrow in either PN or CT as follows: high-SR5 and CT (n = 30); low-SR5 and CT (n = 27); high-SR5 and PN (n = 22); and low-SR5 and PN (n = 24). Data on individual piglets were collected at birth, including interbirth interval; birth order; birth weight; rectal temperature at birth, 2 h after birth, and 24 h after birth; cordal plasma lactate; and latency to first suckle. Based on autopsy, causes of mortality were divided into stillborn, bitten to death, starvation, crushed, disease, and other causes. Potential risk factors of dying were estimated using a GLM with a logit link function. No significant effect (NS) of housing was observed on the odds of a piglet being stillborn (F(1,73) = 0.1, NS), being crushed (F(1,53) = 1.4, NS), or dying of starvation (F(1,53) = 0.3, NS). No significant differences were observed between the 2 genetic groups for any category of mortality. Piglet traits for pre- and postnatal survival were the same for CT and PN. The odds of being stillborn were increased in piglets born late in the birth order (F(1,1061) = 33.5, P < 0.0001), after a long interbirth interval (F(1,1061) = 19.2, P < 0.0001), and with a lighter birth weight (F(1,1061) = 9.2, P = 0.003). The lighter the birth weight of the piglets, the greater were the odds of being crushed (F(1,1050) = 18, P < 0.0001) and dying of starvation (F(1,1050) = 19, P < 0.0001). The lower the rectal temperature 2 h after birth, the greater were the odds of being crushed (F(1,1050) = 4.6, P = 0.03), starving (F(1,1050) = 16.6, P < 0.0001), or dying of diseases (F(1,1050) = 4.9, P = 0.03). Increased cordal plasma lactate increased the odds of dying from starvation (F(1,1050) = 18, P < 0.0001). In both CT and PN, the birth weight, body temperature 2 h after birth, and birth process were important traits related to crushing, starvation, and disease. Neither housing nor breeding value influenced mortality or traits of importance for the inborn viability of piglets. The results emphasize that the microclimate in the PN for newborn piglets and its heat-preserving properties are more important for survival than whether the sow is crated or penned.     

Survival analysis of preweaning piglet survival in a dry-cured ham-producing crossbred line

The aim of this study was to investigate piglet preweaning survival and its relationship with a total merit index (TMI) used for selection of Large White terminal boars for dry-cured ham production. Data on 13,924 crossbred piglets (1,347 litters), originated by 189 Large White boars and 328 Large White-derived crossbred sows, were analyzed under a frailty proportional hazards model, assuming different baseline hazard functions and including sire and nursed litter as random effects. Estimated hazard ratios (HR) indicated that sex, cross-fostering, year-month of birth, parity of the nurse sow, size of the nursed litter, and class of TMI were significant effects for piglet preweaning survival. Female piglets had less risk of dying than males (HR = 0.81), as well as cross-fostered piglets (HR = 0.60). Survival increased when piglets were nursed by sows of third (HR = 0.85), fourth (HR = 0.76), and fifth (HR = 0.79) parity in comparison with first and second parity sows. Piglets of small (HR = 3.90) or very large litters (HR >1.60) had less chance of surviving in comparison with litters of intermediate size. Class of TMI exhibited an unfavorable relationship with survival (HR = 1.20 for the TMI top class). The modal estimates of sire variance under different baseline hazard functions were 0.06, whereas the variance for the nursed litter was close to 0.7. The estimate of the nursed litter effect variance was greater than that of the sire, which shows the importance of the common environment generated by the nurse sow. Relationships between sire rankings obtained from different survival models were high. The heritability estimate in equivalent scale was low and reached a value of 0.03. Nevertheless, the exploitable genetic variation for this trait justifies the inclusion of piglet preweaning survival in the current breeding program for selection of Large White terminal boars for dry-cured ham production.     

Phenotypic and genetic parameter estimates for reproductive traits in Zandi sheep

This study reports on the phenotypic and genetic (co)variance components for reproductive traits in Zandi sheep, using between 1,859 and 2,588 records obtained from 577 ewes. The data were collected from the Khojir Breeding Station of Zandi sheep in Tehran, Iran from 1994 to 2008. The basic traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), and litter mean weight per lamb weaned (LMWLW), and the composite traits were total litter weight at birth (TLWB) and total litter weight at weaning (TLWW). Genetic analyses were carried out using the restricted maximum likelihood method that was explored by fitting the additive direct genetic effects and permanent environmental effects of the ewes as random effects and the ewe age at lambing and lambing year as fixed effects for all of the investigated traits. Akaike’s information criterion was used to choose the most appropriate model. LSB, LSW, LMWLB, LMWLW, TLWB, and TLWW direct heritability estimates were 0.07, 0.05, 0.12, 0.10, 0.08, and 0.14, respectively. The estimated fractions of variance due to the permanent environmental effects of the ewe ranged from 0.03 for LMWLB to 0.08 for LMWLW and TLWW. Corresponding repeatability estimates ranged from 0.10 for LSW to 0.22 for TLWW. Direct genetic correlations varied from ?0.61 for LSB–LMWLB to 0.88 for LSB–LSW and LSB–TLWB. Results indicate that genetic change depends not only on the heritability of traits, but also on the observed phenotypic variation; therefore, improvement of non-genetic factors should be included in the breeding programs.     

Genetic associations of prolificacy with performance, carcass, meat quality, and leg conformation traits in the Finnish Landrace and Large White pig populations

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.     

Estimation of additive and non-additive genetic parameters for reproduction, growth and survival traits in crosses between the Moroccan D'man and Timahdite sheep breeds

Genetic breed differences, heterosis, recombination loss, and heritability for reproduction traits, lamb survival and growth traits to 90 days of age were estimated from crossing D'man and Timahdite Moroccan breeds. The crossbreeding parameters were fitted as covariates in the model of analysis. The REML method was used to estimate (co)variance components using an animal model. The first estimation of crossbreeding effects for Timahdite and D'man breeds shows that breed differences in litter traits are mainly of maternal genetic origin: +1.04 lambs, +1.88 kg, +0.60 lambs, and +2.23 kg in favour of D'man breed for litter size at lambing, litter weight at lambing, litter size at weaning, and litter weight at 90 days, respectively. The breed differences in lamb growth and survival are also of maternal genetic origin for the majority of traits studied, but in favour of the Timahdite breed: +3.48 kg, +45 g day⁻¹ and +0.19 lambs for weight at 90 days, for average daily gain between 30 and 90 days of age, and for lamb survival to 90 days, respectively. The D'man direct genetic effect was low and negative for survival and birth weight of lambs during the first month of life. All traits studied showed positive heterosis effects. Recombination loss effects were not significant. Therefore, crossbreeding of Timahdite with D'man breeds of sheep can result in an improved efficiency of production of saleable lambs. Heritability estimates were medium for litter size but low for the other reproduction traits. Direct heritabilities were low for body weights and lamb survival at 90 days and the corresponding maternal heritabilities showed, however, low to moderate estimates. For litter traits, the estimates of genetic and phenotypic correlations were positive and particularly high for genetic correlations.     

Estimates of genetic parameters and genetic change for reproduction,weight, and wool characteristics of Columbia sheep

Genetic parameters from both single-trait and bivariate analyses for prolificacy, weight and wool traits were estimated using REML with animal models for Columbia sheep from data collected from 1950 to 1998 at the U.S. Sheep Experiment Station (USSES), Dubois, ID. Breeding values from both single-trait and seven-trait analyses calculated using the parameters estimated from the single-trait and bivariate analyses were compared with respect to genetic trends. Number of observations were 31,401 for litter size at birth and litter size at weaning, 24,741 for birth weight, 23,903 for weaning weight, 29,572 for fleece weight and fleece grade, and 2,449 for staple length. Direct heritability estimates from single-trait analyses were 0.09 for litter size at birth, 0.06 for litter size at weaning, 0.27 for birth weight, 0.16 for weaning weight, 0.53 for fleece weight, 0.41 for fleece grade, and 0.55 for staple length. Estimate of direct genetic correlation between littersize at birth and weaning was 0.84 and between birth and weaning weights was 0.56. Estimate of genetic correlation between fleece weight and staple length was positive (0.55) but negative between fleece weight and fleece grade (-0.47) and between staple length and fleece grade (-0.70). Estimates of genetic correlations were positive but small between birth weight and litter size traits and moderate and positive between weaning weight and litter size traits. Fleece weight was lowly and negatively correlated with both litter size traits. Fleece grade was lowly and positively correlated with both litter size traits, while staple length was lowly and negatively correlated with the litter size traits. Estimates of correlations between weight traits and fleece weight were positive and low to moderate. Estimates of correlations between weight traits and fleece grade were negative and small. Estimates of correlations between staple length and birth weight (0.05) and weaning weight were small (-0.04). Estimated breeding values averaged by year of birth from both the single-trait and multiple-trait analyses for the prolificacy and weight traits increased over time, but were unchanged for the wool traits. Estimated changes in breeding values over time did not differ substantially for single-trait and multiple-trait analyses, except for traits highly correlated with another trait that was responding to selection.