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

Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs

Knowledge remains limited on genetic variation and genetic correlations for traits in sows and piglets that are reared in an organic or outdoor setting. Here, we estimated genetic variance components for individual piglet weight, litter weight, litter size traits, and number of functional teats in a pig population raised under outdoor organic conditions. Data were collected from the largest organic multiplier farm in Denmark. Individual piglet weight was recorded at birth and on day 10. Number of live and dead piglets were recorded at birth, day 4, and day 11. Mean and total litter weight were calculated based on the individual weight of living piglets at birth and on day 10. The estimated heritability was highest for the number of functional teats (0.49), mean weight of a litter at birth (0.33) and on day 10 (0.25). In contrast, heritability was lowest for litter size traits (0.04-0.08) and piglet weight (0.06-0.07). Maternal heritability was much higher for individual piglet weight than direct heritability. The results showed that selection for higher mean weight results in smaller litters. Also, selection for individual birth weight of piglets results in heavier piglets at 10 days. In conclusion, this study confirmed that there is genetic variation in individual piglet weight, litter traits, and number of functional teats in organically and outdoor-reared pigs.

Direct-Maternal Genetic Parameters for Litter Size and Body Weight of Piglets of a New Black Breed for the Taiwan Black Hog Market

The objective of this study was to estimate the genetic parameters of litter size and piglet weight from farrowing to weaning in KHAPS Black sows. The genetic parameters investigated were the direct (h²_d), maternal (h²_m), realized (h²_r), and total (h²_T) heritability, as well as correlations (r_d, r_m, and r_dm) within and between traits. The analyses were performed using single- and three-trait animal models with and without maternal genetic effects. In the three-trait model with maternal genetic effect, all estimates of h²_d and h²_m were significantly different from zero except the h²_d of mean birth weight. Positive values of r_d and r_m between traits were observed as expected in the range of 0.322-1.000. Negative values of r_dm were found within and between traits and were less associated with mean piglet weight traits than litter size traits. Estimates of h²_T were consistently larger than those of h²_r in both the single- and three-trait model analyses. In addition, the three-trait model can take into account the association between the traits, so the estimates are more accurate with smaller SEs. In conclusion, maternal genetic effects were not negligible in this study, and thus, a multiple-trait animal model with maternal genetic effects and full pedigree is recommended to assist future pig breeding decisions in this new breed.

Genetic variation in piglet mortality in outdoor organic production systems

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0-3 days of age, 4-11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0-3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0-11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.

Piglet Viability: A Review of Identification and Pre-Weaning Management Strategies

Simple Summary

Neonatal piglet viability is decreasing in concert with the selection for ever-greater numbers of piglets born per sow per year. Their survival depends on the early intervention and management strategies used by production staff. This paper will review current and novel methods used to identify these piglets, some of the factors affecting their viability, and management strategies commonly used within production systems to improve their survival.

Abstract

Increased attention on the effects of the global push for a larger litter size has focused on the increased occurrence of piglets with decreased viability, which have lighter birthweights and a reduced ability to thrive in early life. To improve their odds of survival, interventions must be timely and targeted. This requires the early identification of low-viability pigs and appropriate strategies to manage them. Using novel measures such as abdominal circumference and crown to the rump length in conjunction with birth weight may provide an improved protocol for the identification of those at most risk of preweaning mortality. Further, identifying these at-risk piglets allows interventions to increase their colostrum intake and heat provisions shortly following birth. The appropriate management of the pre- and post-partum sows will improve the chances of decreasing the number of piglets born with lower viability. However, this outcome is constrained by limitations in resources such as technology and staffing. If these challenges can be overcome, it will allow for greater control and increased effectiveness in the implementation of current and new management strategies.

Investigating pig survival in different production phases using genomic models

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.

Impact of including the cause of missing records on genetic evaluations for growth in commercial pigs

It is of interest to evaluate crossbred pigs for hot carcass weight (HCW) and birth weight (BW); however, obtaining a HCW record is dependent on livability (LIV) and retained tag (RT). The purpose of this study is to analyze how HCW evaluations are affected when herd removal and missing identification are included in the model and examine if accounting for the reasons for missing traits improves the accuracy of predicting breeding values. Pedigree information was available for 1,965,077 purebred and crossbred animals. Records for 503,716 commercial three-way crossbred terminal animals from 2014 to 2019 were provided by Smithfield Premium Genetics. Two pedigree-based models were compared; model 1 (M1) was a threshold-linear model with all four traits (BW, HCW, RT, and LIV), and model 2 (M2) was a linear model including only BW and HCW. The fixed effects used in the model were contemporary group, sex, age at harvest (for HCW only), and dam parity. The random effects included direct additive genetic and random litter effects. Accuracy, dispersion, bias, and Pearson correlations were estimated using the linear regression method. The heritabilities were 0.11, 0.07, 0.02, and 0.04 for BW, HCW, RT, and LIV, respectively, with standard errors less than 0.01. No difference was observed in heritabilities or accuracies for BW and HCW between M1 and M2. Accuracies were 0.33, 0.37, 0.19, and 0.23 for BW, HCW, RT, and LIV, respectively. The genetic correlation between BW and RT was 0.34 ± 0.03, and between BW and LIV was 0.56 ± 0.03. Similarly, the genetic correlation between HCW and RT was 0.26 ± 0.04, and between HCW and LIV was 0.09 ± 0.05, respectively. The positive and moderate genetic correlations between BW and other traits imply a heavier BW resulted in a higher probability of surviving to harvest. Genetic correlations between HCW and other traits were lower due to the large quantity of missing records. Despite the heritable and correlated aspects of RT and LIV, results imply no major differences between M1 and M2; hence, it is unnecessary to include these traits in classical models for BW and HCW.

Maternal and direct genetic parameters for tail length, tail lesions, and growth traits in pigs

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

The Role of Offspring Genotype-By-Sex Interactions, Independently of Environmental Cues, on the Phenotype Traits of an Obese Swine Model

Simple Summary

The present study, comparing the postnatal development of purebred Iberian and crossbreds Iberian × Large White littermates born from purebred Iberian sows, allows us to discern phenotype traits driven by the genotype from features imposed by pre- and postnatal environment. The results obtained in this study support the well-known relevance of genotype but also evidence a paramount role of the interaction sex-by-genotype, with differential effects depending on the offspring genotype and sex.

Abstract

The present study aimed to assess the importance of offspring genotype on postnatal development, independently of confounding factors related to prenatal environment and postnatal lifestyle, using a translational model of obesity and metabolic syndrome (the Iberian pig). Hence, we compared two genotypes (purebred Iberian and crossbreds Iberian × Large White), produced in one single maternal environment (pure Iberian mothers) through artificial insemination of Iberian sows with Iberian and Large White heterospermic semen and maintained in the same conditions during postnatal development. The results indicate that, under same pre- and postnatal environments, the interaction genotype-by-sex has a determinant role on offspring phenotype (i.e., growth and development, metabolic and antioxidant status and fatty acid composition of different tissues). These results may set the basis for future preclinical and clinical research on the differences in the metabolic phenotype among genotypes.

Relationship between litter size at birth and within-litter birth weight characteristics in laboratory mice as pilot animal for pig

We investigated the relationship between litter size at birth and within-litter birth weight (BW) characteristics of laboratory mice as a pilot mammal for pig. We obtained records of number born alive (NBA) and total and mean litter BW (LWB, MWB), and maximum and minimum values of within-litter BW (MaxIWB, MinIWB), range and standard deviation (Range, SDIWB), skewness (Skew), and kurtosis (Kurt) of within-litter BW for 656 litters at first parity. Pearson's correlations of NBA were highly positive with LWB (0.92), weakly negative with MWB (-0.31), MaxIWB (-0.19), and MinIBW (-0.33), and those of MWB were negligible with Range, SDIWB, Skew, and Kurt (-0.10 to 0.06). Estimated heritabilities, treated as dam traits, were 0.32 for NBA, 0.39 for LWB, 0.24 for MWB, 0.28 for MaxIWB, 0.05 for MinIWB, 0.16 for Range, 0.17 for SDIWB, and 0.00 for Skew and Kurt. Estimated genetic correlation between NBA and LWB was high (0.95). Therefore, LWB could be promising for efficiently improving NBA. The estimated genetic correlation of NBA was negligible with MWB (0.00), positive with MaxIWB (0.10), Range (0.48), and SDIWB (0.36), and negative with MinIWB (-0.36), suggesting that selection for increased NBA brings larger SDIWB and lighter MinIWB.

Genetic evaluation including maternal effects in Large White Yorkshire × desi crossbred pigs under hot and humid conditions of India

A study was conducted to evaluate the individual and sow performance traits of Large White Yorkshire × desi crossbred pigs at All India Co-ordinated Research Project on Pigs (AICRP), Kattupakkam. The genetic groups studied were 50% LWY (100% LWY × 100% desi), 50% LWY inter se (50% LWY 50% desi × 50% LWY 50% desi), 75% LWY (100% LWY × 50% LWY 50% desi) and 75% LWY inter se (75% LWY 25% desi × 75% LWY 25% desi). The (co)variance components for different traits were estimated by restricted maximum likelihood method (REML). The average inbreeding in the whole population was 5.4%. Maternal genetic and common litter effects were important random sources of variation in individual traits. The least-squares mean for birth weight (BW), weaning weight (WW), average daily gain up to weaning (ADG), market weight (MW), pre-weaning mortality (PWM), age at first farrowing (AFF), litter size at birth (LSAB), litter weight at birth (LWAB), litter size at weaning (LSAW), litter weight at weaning (LWAW) and farrowing interval (FI) were 1.079 kg, 7.906 kg, 142.238 g, 8.4%, 62.208 kg, 456.829 days, 197.994 days, 6.792, 8.174 kg, 6.347 and 60.649 kg, respectively, and the direct heritability obtained through the best model were 0.069, 0.015, 0.012, 0.031, 0.291, 0.019, 0.173, 0.257, 0.076 and 0.157, respectively. The repeatability estimates for LWAB, LSAW, LWAW and FI were 0.265, 0.258, 0.263 and 0.762, respectively. The 75% LWY were better in terms of production and reproduction traits and the high heritability for litter traits provided good scope for improvement.

Invited review: Piglet survival: benefits of the immunocompetence

Piglet mortality has a negative impact on animal welfare and public acceptance. Moreover, the number of weaned piglets per sow mainly determines the profitability of piglet production. Increased litter sizes are associated with lower birth weights and piglet survival. Decreased survival rates and performance of piglets make the control of diseases and infections within pig production even more crucial. Consequently, selection for immunocompetence becomes an important key aspect within modern breeding programmes. However, the phenotypic recording of immune traits is difficult and expensive to realize within farm routines. Even though immune traits show genetic variability, only few examples exist on their respective suitability within a breeding programme and their relationships to economically important production traits. The analysis of immune traits for an evaluation of immunocompetence to gain a generally improved immune response is promising. Generally, in-depth knowledge of the genetic background of the immune system is needed to gain helpful insights about its possible incorporation into breeding programmes. Possible physiological drawbacks for enhanced immunocompetence must be considered with regards to the allocation theory and possible trade-offs between the immune system and performance. This review aims to discuss the relationships between the immunocompetence of the pig, piglet survival as well as the potential of these traits to be included into a breeding strategy for improved robustness.

Genetic and phenotypic parameters for litter size, survival rate, gestation length, and litter weight traits in American mink

The economic efficiency of mink production is greatly influenced by reproductive performance. Therefore, the objective of this study was to estimate phenotypic and genetic parameters for reproduction traits including total number of kits born (TB), number of live kits at birth (LB), number of live kits at weaning (LW), survival rate at birth (SB), survival rate at weaning (SW), gestation length (GL), average kit weight per litter at birth (AWB), average kit weight per litter at week 3 (AW3), and average kit weight per litter at weaning (AWW) in American mink. Data included records of 3,046 litters collected by the Canadian Centre for Fur Animal Research at Dalhousie Faculty of Agriculture between 2002 and 2016. Significance (P < 0.05) of fixed effects (year, number of matings, color type, age of dam, origin of dam, sex ratio, and number of live kits) and random effects of permanent environment were determined using univariate repeatability models. A significant effect of permanent environment was only found for survival rate traits (P < 0.05). Subsequently, genetic and phenotypic parameters for all traits were estimated by fitting a set of bivariate models using ASREML 4.0. Heritabilities (± SE) were estimated to be 0.07 ± 0.03 for TB, 0.07 ± 0.02 for LB, 0.09 ± 0.04 for LW, 0.13 ± 0.03 for SB, 0.10 ± 0.02 for SW, 0.29 ± 0.03 for GL, 0.28 ± 0.05 for AWB, 0.19 ± 0.04 for AW3, and 0.10 ± 0.04 for AWW. Moderate positive genetic correlation was observed between AWB with SB (0.66 ± 0.10) and SW (0.61 ± 0.13). Furthermore, genetic correlations of LB with SW and AWB were 0.55 ± 0.16 and 0.53 ± 0.18, respectively. On the other hand, negative and moderate genetic correlations were observed between GL and survival rates at birth (-0.43 ± 0.14) and at weaning (-0.37 ± 0.15). These results indicated that selection for higher litter weights at birth can effectively improve survival rate and number of live kits in mink farms. It was suggested to incorporate litter weight traits as a selection criterion to increase maternal ability in mink breeding programs. Unfavorable genetic trends were observed for the studied traits indicating that phenotypic selection with low selection intensity had not been an efficient method to improve them over the last 10 yr. It was recommended to use genetic or genomic evaluation methods for mink selection.

Estimation of direct and maternal genetic parameters for individual birth weight, weaning weight, and probe weight in Yorkshire and Landrace pigs

As a result of selecting for increased litter size, newborn piglets are being born lighter and have a lower chance of survival. Raising fewer pigs to market weight would have a negative impact on the industry and farmer profitability; thus, understanding the genetics of individual growth performance traits will determine whether these traits will play an important role in pig breeding schemes. This study aimed to estimate genetic parameters for individual birth weight (BW), weaning weight (WW), and probe weight (PW) in Canadian-purebred Yorkshire and Landrace pigs. PW is a live weight taken at the time of the ultrasound measurements, when pigs weigh about 100 kg. Data were collected from 2 large and related breeding herds from 2003 to 2015. Four linear animal models were used, which included the following: Model 1-direct additive genetic effect; Model 2-direct additive genetic and maternal genetic effect; Model 3-direct additive genetic and common litter effect; and Model 4-direct additive genetic, maternal genetic, and common litter effect. The model which included all 3 random effects (Model 4) was determined to be the best fit to the data. Low to moderate direct heritability estimates were observed as follows: 0.15 ± 0.03 for BW, 0.04 ± 0.01 for WW, and 0.33 ± 0.03 for PW for the Yorkshire breed; and 0.05 ± 0.01 for BW, 0.01 ± 0.01 for WW, and 0.27 ± 0.03 for PW in the Landrace breed. As expected, the direct heritability estimates increased with age as a result of decreased maternal influence on the trait. Bivariate animal models were also used to estimate genetic and environmental correlations between traits. Strong direct genetic correlations were observed between BW and WW in both breeds. Based on the estimates of genetic parameters, individual BW could be evaluated and considered in breeding programs aiming to increase BW and improve subsequent performance. Different selection emphasis could also be applied on direct and maternal additive genetic effects on BW to optimize the breeding programs and improve selection efficiency.

Estimation of direct and maternal genetic parameters for individual birth weight and probe weight using cross-fostering information

A total of 246 357 measurements of birth (BW) and probe (PW) weights of purebred Yorkshire and Landrace pigs were used to compare the fitting of two alternate models including either common-litter effect or cross-fostering group effect to account for common environmental variation. PW, is a live ultrasonic weight measurement taken when the pigs are 100 ± 30 kg, following national standards. The common-litter effect was defined as piglets born into the same litter, and the group effect was used to account for cross-fostering, and defined as the effect common to piglets raised by the same nurse-sow, regardless of whether that piglet was born into that litter or not. It was found that the cross-fostering group explained 5% more environmental variation in BW when compared with the common-litter effect, indication that BW is a criterion in cross-fostering. Cross-fostering also explained 1% more environmental variation in PW in both the Yorkshire and Landrace. When the cross-fostering group effect was included in place of the common-litter effect, the direct and maternal genetic heritability estimates were similar, but residual variances were reduced. This study advanced the understanding of the effects of cross-fostering on PW, its association with BW and its implications in modern pig breeding programs.

Direct and maternal additive effects are not the main determinants of Iberian piglet perinatal mortality

Data of 127,800 Iberian piglets were used to study genetic parameters of mortality at birth at the piglet level. These records proceed from three data sets: 4,987 litter of 2,156 sows of a dam line, 2,768 litter of 817 sows of a complete diallel cross between four Iberian strains and 7,153 litter of 2,113 sows of the Torbiscal composite line. Perinatal mortality was considered as a binary trait, and Bayesian threshold animal models were fitted to separately analyse the three data sets. The posterior means of direct heritability were 0.010, 0.004 and 0.003, and those of maternal heritability were 0.034, 0.011 and 0.014 for dam line, diallel cross and Torbiscal line, respectively. Important effects of litter size and parity order were inferred in the three data sets, of within-breed cross-breeding parameters in the diallel cross and of sex and sow handling in the Torbiscal line Therefore, the inclusion of perinatal mortality in the objective of selection is questionable in this breed and strategies for reducing piglet mortality successful in other breeds should be considered.

Variance component estimates for alternative litter size traits in swine

Litter size at d 5 (LS5) has been shown to be an effective trait to increase total number born (TNB) while simultaneously decreasing preweaning mortality. The objective of this study was to determine the optimal litter size day for selection (i.e., other than d 5). Traits included TNB, number born alive (NBA), litter size at d 2, 5, 10, 30 (LS2, LS5, LS10, LS30, respectively), litter size at weaning (LSW), number weaned (NW), piglet mortality at d 30 (MortD30), and average piglet birth weight (BirthWt). Litter size traits were assigned to biological litters and treated as a trait of the sow. In contrast, NW was the number of piglets weaned by the nurse dam. Bivariate animal models included farm, year-season, and parity as fixed effects. Number born alive was fit as a covariate for BirthWt. Random effects included additive genetics and the permanent environment of the sow. Variance components were plotted for TNB, NBA, and LS2 to LS30 using univariate animal models to determine how variances changed over time. Additive genetic variance was minimized at d 7 in Large White and at d 14 in Landrace pigs. Total phenotypic variance for litter size traits decreased over the first 10 d and then stabilized. Heritability estimates increased between TNB and LS30. Genetic correlations between TNB, NBA, and LS2 to LS29 with LS30 plateaued within the first 10 d. A genetic correlation with LS30 of 0.95 was reached at d 4 for Large White and at d 8 for Landrace pigs. Heritability estimates ranged from 0.07 to 0.13 for litter size traits and MortD30. Birth weight had an h of 0.24 and 0.26 for Large White and Landrace pigs, respectively. Genetic correlations among LS30, LSW, and NW ranged from 0.97 to 1.00. In the Large White breed, genetic correlations between MortD30 with TNB and LS30 were 0.23 and -0.64, respectively. These correlations were 0.10 and -0.61 in the Landrace breed. A high genetic correlation of 0.98 and 0.97 was observed between LS10 and NW for Large White and Landrace breeds, respectively. This would indicate that NW could possibly be used as an effective maternal trait, given a low level of cross-fostering, to avoid back calculating litter size traits from piglet records. Litter size at d 10 would be a compromise between gain in litter size at weaning and minimizing the potentially negative effects of the nurse dam and direct additive genetics of the piglets, as they are expected to increase throughout lactation.

Genetic trends in maternal and neonatal behaviors and their association with perinatal survival in French Large White swine

Genetic trends in maternal abilities were studied in French Large White sows. Two lines representing old-type and modern-type pigs were obtained by inseminating modern sows with semen from boars born in 1977 or 1998. Successive generations were produced by inter-se mating. The maternal performance of sows from the second generation was compared in farrowing crates. Video analysis was performed for the 1st h after the onset of 43 and 36 farrowing events, and for the 6 first hours for 23 and 21 events, in old-type and modern-type sows, respectively. Genetic trends were estimated as twice the difference in estimates between the 2 lines. The contribution of behavior to the probability of stillbirth and piglet death in the first 2 days was estimated as the percentage of deviance reduction (DR) due to the addition of behavior traits as factors in the mortality model. Sow activity decreased strongly from the 1st to the 2nd h in both lines (P < 0.001). In the first 6 h, old-type sows sat (1st parity), stood (2nd parity) and rooted (both parities) for longer than modern-type sows, which were less active, especially in 2nd parity. In modern-type sows, stillbirth was associated positively with lying laterally in the first 6 h (4.6% DR) and negatively in the 1st h (9.1% DR). First-parity old-type sows were more attentive to piglets (P = 0.003) than modern-type sows which responded more to nose contacts at 2nd parity (P = 0.01). Maternal reactivity of modern-type sows was associated with a higher risk of piglet death (4.6% DR). Respiratory distress at birth tended to be higher in modern-type piglets than in old-type piglets (P < 0.10) and was associated with a higher risk of piglet death in both lines (2.7–3.1% DR). Mobility at birth was lower in modern-type than old-type piglets (P < 0.0001). Genetic trends show that sow and piglet behaviors at farrowing have changed. Our results indicate reduced welfare in parturient modern-type sows and their newborn piglets.

Genetic and phenotypic correlations between performance traits with meat quality and carcass characteristics in commercial crossbred pigs

Genetic correlations between performance traits with meat quality and carcass traits were estimated on 6,408 commercial crossbred pigs with performance traits recorded in production systems with 2,100 of them having meat quality and carcass measurements. Significant fixed effects (company, sex and batch), covariates (birth weight, cold carcass weight, and age), random effects (additive, litter and maternal) were fitted in the statistical models. A series of pairwise bivariate analyses were implemented in ASREML to estimate heritability, phenotypic, and genetic correlations between performance traits (n = 9) with meat quality (n = 25) and carcass (n = 19) traits. The animals had a pedigree compromised of 9,439 animals over 15 generations. Performance traits had low-to-moderate heritabilities (±SE), ranged from 0.07±0.13 to 0.45±0.07 for weaning weight, and ultrasound backfat depth, respectively. Genetic correlations between performance and carcass traits were moderate to high. The results indicate that: (a) selection for birth weight may increase drip loss, lightness of longissimus dorsi, and gluteus medius muscles but may reduce fat depth; (b) selection for nursery weight can be valuable for increasing both quantity and quality traits; (c) selection for increased daily gain may increase the carcass weight and most of the primal cuts. These findings suggest that deterioration of pork quality may have occurred over many generations through the selection for less backfat thickness, and feed efficiency, but selection for growth had no adverse effects on pork quality. Low-to-moderate heritabilities for performance traits indicate that they could be improved using traditional selection or genomic selection. The estimated genetic parameters for performance, carcass and meat quality traits may be incorporated into the breeding programs that emphasize product quality in these Canadian swine populations.

Joint analysis of binomial and continuous traits with a recursive model: a case study using mortality and litter size of pigs

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshire. Available evidence suggests that mortality of piglets increased partly as a result of successful selection for total number of piglets born. In recent years there has been a need to decrease the incidence of mortality in pig-breeding programs. We report estimates of genetic variation at the level of the logit of the probability of mortality and quantify how it is affected by the size of the litter. Several models for mortality are considered and the best fits are obtained by postulating linear and cubic relationships between the logit of the probability of mortality and litter size, for Landrace and Yorkshire, respectively. An interpretation of how the presence of genetic variation affects the probability of mortality in the population is provided and we discuss and quantify the prospects of selecting for reduced mortality, without affecting litter size.

Estimation of genetic parameters for birth weight, preweaning mortality, and hot carcass weight of crossbred pigs

Genetic parameters for birth weight (BWT), preweaning mortality (PWM), and HCW were estimated for a crossbred pig population to determine if BWT could be used as an early predictor for later performances. Sire genetic effects for those traits were estimated to determine if early selection of purebred sires used in crossbreeding could be improved. Data were recorded from 1 commercial farm between 2008 and 2010. Data were from 24,376 crossbred pigs from Duroc sires and crossbred Large White × Landrace dams and included 24,376 BWT and PWM records and 13,029 HCW records. For the analysis, PWM was considered as a binary trait (0 for live or 1 for dead piglet at weaning). A multitrait threshold-linear animal model was used, with animal effect divided into sire genetic and dam effects; the dam effects included both genetic and environmental variation due to the absence of pedigree information for crossbred dams. Fixed effects were sex and parity for all traits, contemporary groups for BWT and HCW, and age at slaughter as a linear covariable for HCW. Random effects were sire additive genetic, dam, litter, and residual effects for all traits and contemporary group for PWM. Heritability estimates were 0.04 for BWT, 0.02 for PWM, and 0.12 for HCW. The ratio between sire genetic and total estimated variances was 0.01 for BWT and PWM and 0.03 for HCW. Dam and litter variances explained, respectively, 14% and 15% of total variance for BWT, 2% and 10% for PWM, and 3% and 8% for HCW. Genetic correlations were -0.52 between BWT and PWM, 0.55 between BWT and HCW, and -0.13 between PWM and HCW. Selection of purebred sires for higher BWT of crossbreds may slightly improve survival until weaning and final market weight at the commercial level.

Variance and covariance components for liability of piglet survival during different periods

Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual piglet level, the estimates of direct heritability in Landrace were 0.035, 0.057 and 0.027, and in Yorkshire the estimates were 0.012, 0.030 and 0.025 for liability of survival at farrowing (SVB), from birth to day 5 (SV5) and from day 6 to weaning (SVW), respectively. The estimates of maternal heritability for SVB, SV5 and SVW were, respectively, 0.057, 0.040 and 0.030 in Landrace, and 0.050, 0.038 and 0.019 in Yorkshire. Both direct and maternal genetic correlations between the three survival traits were low and not significantly different from zero, except for a moderate direct genetic correlation between SVB and SV5 and between SV5 and SVW in Landrace. Direct and maternal genetic correlations between piglet birth weight (BW) and SV5 were moderately high, but the correlations between BW and SVB and between BW and SVW were low and most of them were not significantly different from zero. These results suggest that effective genetic improvement in piglet survival before weaning by selection should be based on both direct and maternal additive genetic effects and treat survival in different periods as different traits.

Animal-related factors associated with piglet mortality in a bedded, group-farrowing system

Li, Y. Z., Anderson, J. E. and Johnston, L. J. 2012. Animal-related factors associated with piglet mortality in a bedded, group-farrowing system. Can. J. Anim. Sci. 92: 11–20. To understand pre-weaning mortality of piglets in a bedded, group-farrowing system, associations with sow parity, mortality of piglets during the first 24 h after birth, farrowing behavior, cross-fostering, birth weight and gender of piglets were investigated. Sows (n=169, parity 1 to 10) from eight contemporary groups were evaluated. Litter size at birth, dead piglets from birth to weaning, and individual weight of piglets at birth and weaning (27±2.6 d) were recorded. Behavior of 46 focal sows during farrowing was video-recorded. Piglet mortality within litter increased (P<0.001) with increasing parity. Piglets that died before weaning were lighter (P<0.001) at birth than weaned piglets. Mortality of pigs during the first 24 h postpartum was correlated positively with pre-weaning mortality within litter (R2=0.34; P<0.001). Farrowing behaviors were not associated with piglet mortality, and were not different among sows of different parities, or between sows with and without 24 h piglet mortality. Gender of piglets and cross-fostering did not affect piglet mortality. Results indicate that parity, 24 h mortality, and birth weight of piglets were the major animal-related factors associated with piglet mortality in the loose farrowing system studied.

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.

Genetic analyses of stillbirth in relation to litter size using random regression models

Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-year-season) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B-splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth.

An application of change-point recursive models to the relationship between litter size and number of stillborns in pigs

We developed and implemented change-point recursive models and compared them with a linear recursive model and a standard mixed model (SMM), in the scope of the relationship between litter size (LS) and number of stillborns (NSB) in pigs. The proposed approach allows us to estimate the point of change in multiple-segment modeling of a nonlinear relationship between phenotypes. We applied the procedure to a data set provided by a commercial Large White selection nucleus. The data file consisted of LS and NSB records of 4,462 parities. The results of the analysis clearly identified the location of the change points between different structural regression coefficients. The magnitude of these coefficients increased with LS, indicating an increasing incidence of LS on the NSB ratio. However, posterior distributions of correlations were similar across subpopulations (defined by the change points on LS), except for those between residuals. The heritability estimates of NSB did not present differences between recursive models. Nevertheless, these heritabilities were greater than those obtained for SMM (0.05) with a posterior probability of 85%. These results suggest a nonlinear relationship between LS and NSB, which supports the adequacy of a change-point recursive model for its analysis. Furthermore, the results from model comparisons support the use of recursive models. However, the adequacy of the different recursive models depended on the criteria used: the linear recursive model was preferred on account of its smallest deviance value, whereas nonlinear recursive models provided a better fit and predictive ability based on the cross-validation approach.

Genetics of growth in piglets and the association with homogeneity of body weight within litters

The objective of this study was to examine the genetic basis of homogeneity in piglets and the genetic correlations with litter size and growth during lactation. Genetic parameters for variation in piglet BW within litters at birth and at 3 wk of age, and in the BW of individual piglets at 3 wk (BW3) were estimated from the Norwegian Landrace nucleus population. Data on BW3 were collected from 146,572 piglets from 14,045 litters in 58 herds. Body weight at birth and at 3 wk of age was recorded for 13,318 piglets from 5 nucleus herds. Litter data were evaluated using multivariate trait models. The heritability estimates for the SD of BW at birth and at 3 wk (SDBW3) were in agreement with the literature (0.10 and 0.08, respectively). The genetic correlation for the number of piglets born alive and the mean BW at 3 wk was negative (-0.40 +/- 0.07), and the correlation of number of piglets born alive with SDBW3 was close to zero (-0.03 +/- 0.11). The genetic correlation between the SD of BW at birth and SDBW3 was moderate (0.51 +/- 0.31). The mean BW at birth was genetically correlated with mean BW at 3 wk (0.59 +/- 0.16) but was independent of SDBW3 (0.08 +/- 0.27). The estimates of direct and maternal heritability for BW3 were 0.03 and 0.07, respectively, and the genetic correlation between the 2 components was negative (-0.43 +/- 0.10). The genetic correlation of SDBW3 with the maternal effect on BW3 was positive and strong (0.66 +/- 0.08), whereas a negative correlation was found with the direct effect on BW3 (-0.18 +/- 0.14). These results suggest that it is possible to select for mean BW at birth without an increase in within-litter heterogeneity at 3 wk of age. A more efficient strategy would be to consider both the direct and the maternal effects on BW3 in the genetic evaluation, together with SDBW3. Thus, it is possible to avoid the increase in within-litter heterogeneity that would occur as a result of selection performed at 3 wk on a litter trait such as mean BW.

Genetic parameters of piglet survival and birth weight from a two-generation crossbreeding experiment under outdoor conditions designed to disentangle direct and maternal effects

Multivariate Bayesian linear-threshold models were used to estimate genetic parameters of peri- and postnatal piglet survival and individual birth weight of piglets reared under outdoor conditions. Data of 21,835 individual piglet observations were available from a 2-generation crossbreeding experiment selected for direct and maternal genetic effects of postnatal piglet survival on piglet and dam levels, respectively. In the first generation, approximately one-half of the Landrace sires used were selected for large or average breeding values of maternal genetic effects on postnatal piglet survival, whereas in the second generation the Large White sires used were selected for direct genetic effects of the same trait. Estimates of direct and maternal heritability were 0.21 and 0.15, 0.24 and 0.14, and 0.36 and 0.28 for piglet survival at birth and during the nursing period, and individual birth weight, respectively. In particular, direct heritabilities are substantially larger than those from the literature estimated for indoor-reared piglets, suggesting that genetic effects of these traits are substantially greater under outdoor conditions. Direct or maternal genetic correlations between survival traits or with birth weight were small (ranging from 0.06 to 0.17), indicating that peri- and postnatal survival are genetically under rather different control, and survival was only slightly positively influenced by birth weight. There were significant (P < 0.05) negative genetic correlations between direct and maternal genetic effects within each of the analyzed traits ranging from -0.36 to -0.45, which have to be considered when selecting for piglet survival. Adjustment of traits for litter size or inclusion of genetic groups showed insignificant effects on the magnitude of the estimated genetic parameters. The magnitude of genetic parameters suggested that there is substantial potential for genetic improvement of survival traits and birth weight in direct and maternal genetic effects, especially when piglets are kept under outdoor conditions.

A genetic analysis of mortality in pigs

An analysis of mortality is undertaken in two breeds of pigs: Danish Landrace and Yorkshire. Zero-inflated and standard versions of hierarchical Poisson, binomial, and negative binomial Bayesian models were fitted using Markov chain Monte Carlo (MCMC). The objectives of the study were to investigate whether there is support for genetic variation for mortality and to study the quality of fit and predictive properties of the various models. In both breeds, the model that provided the best fit to the data was the standard binomial hierarchical model. The model that performed best in terms of the ability to predict the distribution of stillbirths was the hierarchical zero-inflated negative binomial model. The best fit of the binomial hierarchical model and of the zero-inflated hierarchical negative binomial model was obtained when genetic variation was included as a parameter. For the hierarchical binomial model, the estimate of the posterior mean of the additive genetic variance (posterior standard deviation in brackets) at the level of the logit of the probability of a stillbirth was 0.173(0.039) in Landrace and 0.202(0.048) in Yorkshire. The implications of these results from a breeding perspective are briefly discussed.

Reliable computing in estimation of variance components

The purpose of this study is to present guidelines in selection of statistical and computing algorithms for variance components estimation when computing involves software packages. For this purpose two major methods are to be considered: residual maximal likelihood (REML) and Bayesian via Gibbs sampling. Expectation-Maximization (EM) REML is regarded as a very stable algorithm that is able to converge when covariance matrices are close to singular, however it is slow. However, convergence problems can occur with random regression models, especially if the starting values are much lower than those at convergence. Average Information (AI) REML is much faster for common problems but it relies on heuristics for convergence, and it may be very slow or even diverge for complex models. REML algorithms for general models become unstable with larger number of traits. REML by canonical transformation is stable in such cases but can support only a limited class of models. In general, REML algorithms are difficult to program. Bayesian methods via Gibbs sampling are much easier to program than REML, especially for complex models, and they can support much larger datasets; however, the termination criterion can be hard to determine, and the quality of estimates depends on a number of details. Computing speed varies with computing optimizations, with which some large data sets and complex models can be supported in a reasonable time; however, optimizations increase complexity of programming and restrict the types of models applicable. Several examples from past research are discussed to illustrate the fact that different problems required different methods.

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.

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.