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.     

Impact of dominance effects on sow longevity

The purpose of the current study was to estimate variance components, especially dominance genetic variation, for overall leg action, length of productive life and sow stayability until third and fifth parity in the Finnish pig populations. The variance components were estimated in two purebred [Landrace (LR), n = 23 602 and Large White (LW), n =22 984] and crossbred (LR × LW, n = 17 440) data sets. Five different analyses were carried out for all the traits to compare the effect of sows’ inbreeding, common litter environment and parental dominance in the statistical model when determining the genetic correlations of the traits for the two purebred and crossbred populations. Estimated heritabilities for the traits ranged from 0.04 to 0.06. The estimates for the proportion of dominance variance of phenotypic variance (d²) varied between 0.01 and 0.17, and was highest in the crossbred dataset. The genetic correlations of the same traits in purebred and crossbred were all high (>0.75). Based on current results, the effect of dominance should be accounted for in the breeding value estimation of sow longevity, especially when data from crossbred animals are included in the analyses. Because dominance genetic variation for sow longevity exists that variation should be utilized through planned matings in producing sows for commercial production.     

Relationships between longevity,lifetime productivity,carcass traits and conformation in Polish maternal pig breeds

The objective of this study was to obtain heritability estimates for longevity (length of life, length of productive life, number of litters) and lifetime productivity traits (lifetime pig production, lifetime pig efficiency, lifetime litter efficiency) and genetic correlation between them and litter size at first farrowing, growth (ADG), backfat thickness (BF), loin depth, lean meat percentage (LMP), phenotypic selection index (PSI), and exterior in 19423 Polish Landrace (L) and 16049 Polish Large White (LW) sows. Heritabilities for longevity and lifetime productivity traits were 0.10–0.13 for L sows and 0.09–0.11 for LW sows depending on the trait definition. The genetic correlations among these traits were all high and positive, ranging from 0.76 to 0.99. Antagonistic genetic correlations (?0.21 to ?0.26) were found between longevity traits and PSI and LMP in LW sows, while in L sows the respective parameters were lower and not significant for length of productive life. The number of live‐born piglets in the first litter was positively correlated with lifetime pig production and lifetime pig efficiency in both breeds. The genetic correlations of longevity and lifetime pig production with ADG, BF, loin depth and exterior were small, and in most cases, not significant.     

Selection potential of different prolificacy traits in the finnish landrace and large white populations

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.     

Genetic analysis for sow stayability at different parities in purebred Landrace and Large White pigs

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.     

Genetic associations of sow longevity with age at first farrowing, number of piglets weaned, and wean to insemination interval in the Finnish Landrace swine population

The objective of the study was to estimate genetic parameters for length of productive life (LPL), and determine its genetic correlation with age at first farrowing (AFF), number of piglets weaned at first farrowing (NW), and first wean-to-insemination interval (W2I) in the Finnish Landrace swine population. Data from the Finnish national litter recording scheme were utilized to estimate the genetics of LPL, and genetic associations between LPL, AFF, NW, and W2I. Data from the Finnish Landrace sow records were utilized from farms that farrowed more than 20 gilts annually from 2000 through 2005. The data set included information from 11,222 sows, all of which had AFF and NW information available. The sows producing the records evaluated were daughters of 1,267 sires, and there were 3,684 animals in the pedigree when all of the sires were traced back to founder animals. All data were obtained from FABA Breeding (Vantaa, Finland). Multivariate Bayesian analysis of Gaussian, right censored Gaussian, and categorical traits was utilized to estimate (co)variance parameters of LPL, AFF, NW, and W2I of the sow. From these traits, AFF and NW were treated as Gaussian, LPL as right-censored Gaussian, and W2I as categorical traits. Estimated posterior means of heritabilities were 0.22, 0.16, 0.09, and 0.08 for LPL, AFF, NW, and W2I, respectively. A relatively large proportion of variance due to farm-year interaction was observed (posterior means of f(2) ranged between 0.03 and 0.26). The LPL was moderately genetically correlated with NW and AFF (posterior means were -0.20 and 0.36, respectively), whereas no clear association was found between W2I and LPL. Favorable genetic correlations between AFF and W2I and between NW and W2I were also observed. Additionally, an unfavorable genetic correlation between AFF and NW was observed in the present data set. Because LPL is genetically associated with other economically important prolificacy traits, it should be included in a multiple trait swine breeding value estimation system.     

Genetic association between leg conformation in young pigs and sow longevity

Longevity is important in pig production with respect to both economic and ethical aspects. Direct selection for longevity might be ineffective because ‘true’ longevity can only be recorded when a sow has been culled or died. Thus, indirect selection for longevity using information from other traits that can be recorded early in life and are genetically correlated with longevity might be an alternative. Leg conformation has been included in many breeding schemes for a number of years. However, proving that leg conformation traits are good early indicators for longevity still remains. Our aim was to study genetic associations between leg conformation traits of young (5 months; 100 kg) Swedish Yorkshire pigs in nucleus herds and longevity traits of sows in nucleus and multiplier herds. Data included 97 533 animals with information on conformation (Movement and Overall score) recorded at performance testing and 26 962 sows with information on longevity. The longevity traits were as follows: stayability from 1st to 2nd parity, lifetime number of litters and lifetime number of born alive piglets. Genetic analyses were performed with both linear models using REML and linear‐threshold models using Bayesian methods. Heritabilities estimated using the Bayesian method were higher than those estimated using REML, ranging from 0.10 to 0.24 and 0.07 to 0.20, respectively. All estimated genetic correlations between conformation and longevity traits were significant and favourable. Heritabilities and genetic correlations between conformation and longevity indicate that selection on leg conformation should improve sow longevity.     

Estimation of genetic parameters for farrowing traits in purebred Landrace and Large White pigs

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.     

Genetic relationship between purebred and crossbred sow longevity

Background: The overall breeding objective for a nucleus swine selection program is to improve crossbred commercial performance. Most genetic improvement programs are based on an assumed high degree of positive relationship between purebred performance in a nucleus herd and their relatives' crossbred performance in a commercial herd. The objective of this study was to examine the relationship between purebred and crossbred sow longevity performance. Sow longevity was defined as a binary trait with a success occurring if a sow remained in the herd for a certain number of parities and including the cumulative number born alive as a measure of reproductive success. Heritabilities, genetic correlations, and phenotypic correlations were estimated using THRGIBBS1F90.Results: Results indicated little to no genetic correlations between crossbred and purebred reproductive traits.This indicates that selection for longevity or lifetime performance at the nucleus level may not result in improved longevity and lifetime performance at the crossbred level. Early parity performance was highly correlated with lifetime performance indicating that an indicator trait at an early parity could be used to predict lifetime performance. This would allow a sow to have her own record for the selection trait before she has been removed from the herd.Conclusions: Results from this study aid in quantifying the relationship between purebred and crossbred performance and provide information for genetic companies to consider when developing a selection program where the objective is to improve crossbred sow performance. Utilizing crossbred records in a selection program would be the best way to improve crossbred sow productivity.     

Analysis of longevity and exterior traits on Large White sows in Switzerland

Records of length of productive life, from first farrowing to culling, of 16,464 Large White purebred sows from SUISAG were studied using survival analysis. The major aims of the study were to model the risk of culling within parity and to assess the influence of exterior traits, such as the number of teats or feet and leg scores, on culling. Culling was concentrated at the first day after each farrowing or at the first day after weaning. Weaning itself was mostly between 21 and 49 d after farrowing, with an average weaning age of 35 d. Because of the definition of culling date used, there was practically no risk of culling from these periods. The culling rates at different periods suggested a modeling of the baseline hazard function within parity instead of over the entire productive life of the animals. A piecewise Weibull function and a simple graphical method to validate its adequacy were proposed for sow longevity analysis. The risk of culling increased with older parities (P < 0.001) and with decreasing litter size at weaning (P < 0.001). The exterior traits analyzed (number of teats, and feet and leg scores, on a scale from 1 to 7) had a moderate effect on the risk of culling compared with other factors but were still influential on survival, productive life expectancy, and annual replacement rate. Sows with less than 13 good teats had 1.35 times greater risk of being culled than sows with more good teats (P < 0.05). Sows with an X-O rear leg score of 2 had 1.4 times greater risk of being culled than sows with an intermediate score of 4 (P < 0.05). Sows at the optimum score of 4 for the size of inner claws of the rear leg had 0.83 times less risk of being culled (P < 0.01) than sows with scores of 2 and 3. Furthermore, when a phenotypic index for feet and legs was used to group these variables, the effect was highly significant (P < 0.001). Therefore, a means to improve longevity is through phenotypic selection of replacement gilts based on exterior traits: gilts with 13 or less good teats or with extreme feet and leg scores should be culled. From a genetic point of view, sows with the best value in the current index for exterior traits had a lower risk of culling (P < 0.01), and therefore, it is possible to obtain a response for sow longevity via indirect selection for exterior traits. From 1999 to 2003, the trend has been to eliminate extreme animals on exterior traits. This may partly explain the improvement of sow length of productive life longevity from 560 d in 2000 to nearly 710 d in 2003 observed in the data set.     

Effect of leg conformation on survivability of Duroc, Landrace, and Large White sows

Sow longevity influences farm economy and can be considered an important indicator of animal welfare. Body features such as leg conformation can play a key role in sow longevity, although little is known about its effect on culling decisions. Within this context, longevity data from 587 Duroc, 239 Landrace, and 217 Large White sows were analyzed with special emphasis on the effect of leg conformation. Sow longevity was analyzed twice for each breed, testing the effect of a subjective overall score for leg conformation, or the presence or absence of 6 specific leg conformation defects. Each preliminary model also included a teat conformation score with 3 levels, farm or origin, backfat thickness at 6 mo of age, and 2 continuous sources of variation, namely the age at the first farrowing and the number of piglets born alive at each farrowing. Overall leg conformation score influenced (P < 0.01) sow longevity in Duroc, Landrace, and Large White sows, with a greater hazard ratio (HR) for poorly conformed sows (1.56, 2.16, and 1.79, respectively) than for well-conformed sows (0.32, 0.66, and 0.68, respectively). Abnormal hoof growth reduced survivability in Duroc (HR = 2.78; P < 0.001) and Landrace sows (HR = 1.88; P < 0.01); the presence of splayed feet (P < 0.05) or bumps and injuries (P < 0.001) increased the risk of culling in Duroc sows (HR = 2.08 and 3.57, respectively), whereas the incidence of straight pastern increased the HR in Large White sows (HR = 2.49; P < 0.01). In all 3 breeds, longevity decreased for plantigrade sows, with a greater HR in Duroc (HR = 3.38; P < 0.001) than in Landrace (HR = 1.53; P < 0.10) and Large White sows (HR = 1.73; P < 0.05). Teat conformation did not influence sow longevity (P > 0.10). Estimates of heritability for longevity in Duroc sows ranged from 0.05 to 0.07 depending on the algorithm applied. Leg conformation had a substantial effect on sow longevity, where an accurate removal of poorly leg-conformed candidate gilts before first mating could improve sow survival and reduce culling costs. These moderate estimates of heritability indicated that survivability of Duroc sows could be genetically improved by direct selection for leg conformation.     

Genetic analysis of sow longevity and sow lifetime reproductive traits using censored data

Sow longevity is a key component for efficient and profitable pig farming; however, approximately 50% of sows are removed annually from a breeding herd. There is no consensus in the scientific literature regarding a definition for sow longevity; however, it has been suggested that it can be measured using several methods such as stayability and economic indicators such as lifetime piglets produced. Sow longevity can be improved by genetic selection; however, it is rarely included in genetic evaluations. One reason is elongated time intervals required to collect complete lifetime data. The effect of genetic parameter estimation software in handling incomplete data (censoring) and possible early indicator traits were evaluated analysing a 30% censored data set (12 725 pedigreed Landrace × Large White sows that included approximately 30% censored data) with DMU6, THRGIBBS1F90 and GIBBS2CEN. Heritability estimates were low for all the traits evaluated. The results show that the binary stayability traits benefited from being analysed with a threshold model compared to analysing with a linear model. Sires were ranked very similarly regardless if the program handled censoring when all available data were included. Accumulated born alive and stayability were good indicators for lifetime born alive traits. Number of piglets born alive within each parity could be used as an early indicator trait for sow longevity.     

Phenotypic and genetic variation in longevity of Polish Landrace sows

The influence of some production traits on the longevity of Polish Landrace sows was evaluated using survival analysis. Estimates of genetic parameters were obtained from the sire and animal components in linear and survival methodologies. Comparison between survival and linear models was based on heritabilities and ranking of estimated breeding values of sires. The same data set, 13 031 sows, was used for both methodologies, even in the presence of censored observations. The effects of herd*year and year*season of the first farrowing had the largest influence on the risk of culling of sows. Sows born in spring season (March–May) had a 24% (p < 0.001) lower hazard for removal than those born in winter (December–February). The age at first farrowing had a small but significant effect on culling: the hazard regression coefficient for this trait was 0.002 per day. Sows that had more piglets born alive and fewer stillborn in the first litter had a decreased risk of being culled. Within a contemporary group, slower growing gilts had decreased removal risk. The relative risk ratios show a marginal decreased rate of culling for sows with backfat thickness between 9.5 and 11 mm compared to the leaner sows. Loin depth had no effect on sow longevity. Heritability estimates ranged from 0.09 to 0.38 depending on the model and type of analysis. In survival analysis, all heritabilities for longevity were higher when analysed with sire models (0.21 and 0.38) compared to animal models (0.09 and 0.16). The use of animal or sire models in the linear analysis gave similar heritability estimates (0.12 and 0.10). Correlations between breeding values for sires were moderate and high, with absolute values from 0.51 to 0.99, depending on the model fitted and methodology. A stronger correlations within methodologies (0.83–0.99) than within models with different methodologies (0.51–0.63) were obtained.     

Genetic correlation between leg conformation in young pigs,sow reproduction and longevity in Danish pig populations

Abstract

Selection for sow longevity using information from traits, which are expressed in early life and genetically highly related to longevity, is expected to be more effective than direct selection as it can overcome the disadvantage of late recording of true longevity. Our aim was to investigate the correlation between leg conformation recorded on young pigs, litter size at first parity and longevity of Danish Landrace and Yorkshire sows. Information on conformation from 116,733 Landrace and 89,963 Yorkshire pigs and information on reproduction and longevity from 27,070 Landrace and 11,895 Yorkshire sows were analyzed. All considered traits were low to moderately heritable, ranging from 0.02 to 0.41. In general, both conformation and reproduction traits were favorably genetically correlated with longevity (0.07–0.39 and 0.00–0.58, respectively). These estimates suggest a potential of improving sow longevity by selection on conformation recorded at young age and litter size at first parity.     

Relationships between Longevity and Linear Type Traits in Holstein Cattle Population of Southern Africa

Relationships between longevity and linear type traits were estimated using data on 34,201 cows with lifetime information and linear type scores. The longevity trait considered was the number of lactations initiated and the linear type traits were rump height, body depth, angularity, rear udder height, fore udder attachment, udder depth, fore teat placement and fore teat length. Fixed effects included in the models were herd year, season of calving and herd-date of classification-classifier and days in milk. Age at first calving and age at classification were included as linear and quadratic covariates. Heritability estimates were low for longevity and moderate for most type traits except rump height and fore teat length. All the phenotypic correlations between longevity and the linear type traits were slightly positive (0.01 to 0.09) except the relationships with rump height and fore teat length which were -0.01 and -0.02, respectively. Genetic correlations between longevity and udder traits as well as angularity were moderate to high and positive (0.22 to 0.48). The only notable negative genetic correlations were longevity with body depth and fore teat length (-0.15 and -0.07, respectively). The genetic correlations suggest that selection for udder traits and angularity should improve longevity in the Holstein cattle population.     

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.     

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.     

Genetic parameter estimation for number born alive at different parities in Landrace and Large White pigs

We estimated genetic parameters for number born alive (NBA) from the first to the seventh parities in Landrace and Large White pigs using three models. Analyzing 55,160 farrowing records for 12,677 Landrace dams and 43,839 for 10,405 Large White dams, we used a single‐trait animal model to estimate the heritability of NBA at each parity and a two‐trait animal model and a single‐trait random regression model to estimate the genetic correlations between parities. Heritability estimates of NBA at each parity ranged from 0.08 to 0.13 for Landrace and from 0.05 to 0.16 for Large White. Estimated genetic correlations between parities in all cases were positive. Genetic correlations between the first and second parities were slightly lower than those between other neighboring parities. Genetic correlations between more distant parities tended to be lower, in some cases <0.8. The results indicate the necessity to investigate the applicability of evaluating NBA at different parities as different traits (e.g., the first and later parities), although a repeatability model might still be reasonable.     

Genetic analysis of age at first service, return rate, litter size, and weaning-to-first service interval of gilts and sows

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.     

Bayesian threshold analysis of direct and maternal genetic parameters for piglet mortality at farrowing in Large White, Landrace, and Pietrain populations

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.