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.     

Some Factors Influencing the Losses of Pigs Prior to Weaning

Analyses of the records of 244 litters of purebred Yorkshire, Landrace, the crosses, backcrosses and crisscrosses of these two breeds were carried out to evaluate some of the factors influencing the losses of piglets prior to weaning. There were differences in percentage survival between mating systems, with crossbred Landrace x Yorkshire piglets showing the highest rate of survival.A direct relationship existed between the duration of farrowing and the incidence of stillbirths. The incidence of stillbirths was higher for male piglets than for female piglets.Litter size at birth and weight loss of sow from parturition to weaning were important factors in determining litter size at weaning. Litter size at birth however, exerted a more important influence on litter performance than weight loss. Age of sow had no significant effect on the number of piglets alive at weaning and implied that gilts were apparently as good mothers as sows. From computed least squares estimates, it was implied that in general, piglets of low birthweights had much less chance of survival than those born with heavier weights.     

Genetic aspects regarding piglet losses and the maternal behaviour of sows. Part 2. Genetic relationship between maternal behaviour in sows and piglet mortality

The aim of the study was to analyse the genetic background of different traits to characterise the maternal behaviour of sows and to evaluate the relationship to different causes of piglet losses - increasing piglet survival due to higher maternal abilities of the sow. A total of 1538 purebred litters from 943 German Landrace sows in the year 2004 were available for data analysis. Around 13 971 individually earmarked piglets were included in the analyses. Maternal abilities were characterised through the sow's reaction to the separation from her litter during the first 24 h after farrowing, and on day 21 of lactation, the reaction towards the playback of a piglet's distress call and the reaction towards an unknown noise (music). In 1220 of these litters, the sows were also scored for aggressiveness in the group when regrouped before entering the farrowing crates. To describe fertility, the number of piglets born alive, stillborn piglets, number of piglets born in total and the individual birth weight were utilised. Different causes of piglet losses were evaluated as binary traits of the dam with survival rate, different definitions for crushing by the sow, being underweight and runts. The heritability for being aggressive in the group was h2 = 0.32 and for the behaviour traits during lactation, the heritabilities ranged from h2 = 0.06 to 0.14. The genetic correlations showed that more-reactive sows had fewer piglet losses.     

Genetic aspects regarding piglet losses and the maternal behaviour of sows. Part 1. Genetic analysis of piglet mortality and fertility traits in pigs

In spite of the improvement in management and the breeding goal of increasing the number of piglets born alive, piglet mortality is still a substantial problem in pig breeding. The objective of the first part of the study was to estimate genetic parameters for different causes of piglet losses and to investigate the relationship to litter-size traits. Data were collected on a nucleus herd from January till December 2004. Records from 943 German Landrace sows with 1538 pure-bred litters and 13 971 individually weighted piglets were included. Four different causes of piglet losses (LOSS) were evaluated. Additional analysed traits were underweight and runting. Furthermore, the fertility traits number of piglets born alive, born in total and stillborn piglets as well as the individual birth and weaning weights were analysed. The different LOSS were treated as a binary trait and subsequently the heritabilities were estimated using a threshold model. The most important LOSS was crushing under the sow (12.4%). The survival rate and crushing had a heritability of h2 = 0.03. The fertility traits piglets born alive, born in total and stillborn piglets were analysed with a linear model and heritabilities rank from h2 = 0.05 (stillborn) to h2 = 0.10 (born alive). The estimated heritabilities for birth- and weaning weight were both h2 = 0.10. The genetic correlations between number of piglets born alive and each LOSS trait were analysed bivariately. Of all piglets born alive 84.3% survive the lactation period. Survival decreased with increasing litter size (rg = -0.54 up to -0.78) and the probability of being crushed under the sow increased.     

(Co)Variance components and genetic parameter estimates for growth traits in Moghani sheep

Genetic parameters were estimated for birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (ADG1) and average daily gain from weaning to yearling (ADG2) in Moghani sheep. Maximum number of data was 4237 at birth, but only 1389 records at yearling were investigated. The data was collected from 1995 to 2007 at the Breeding Station of Moghani sheep in Jafarabad, Moghan, Iran. (Co)Variance components and genetic parameters were estimated with different models which including direct effects, with and without maternal additive genetic effects as well as maternal permanent environmental effects using restricted maximum likelihood (REML) method. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Maternal effects were important only for pre-weaning traits. Direct heritability estimates for BW, ADG1, WW, ADG2 and YW were 0.07, 0.08, 0.09, 0.09 and 0.17, respectively. Fractions of variance due to maternal permanent environmental effects on phenotypic variance were 0.08 for ADG1. Maternal heritability estimates for BW and WW were 0.18 and 0.06, respectively. Multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Direct genetic correlations among studied traits were positive and ranged from 0.37 for BW–ADG2 to 0.85 for ADG1–YW. Maternal genetic correlation estimate between BW and WW was 0.33. Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low direct heritability estimates imply that mass selection for these traits results in slow genetic gain.     

Genetic parameters for haemoglobin levels in sows and piglets as well as sow reproductive performance and piglet survival

Genetic parameters were estimated for haemoglobin (Hb) levels in sows and piglets as well as sow reproductive performance and piglet survival. Reproductive traits were available between 2005 and 2014 for 7857 litters from 1029 Large White and 858 Landrace sows. In 2012 and 2013, Hb levels, sow BW and sow back fat depth were measured on 348 sows with 529 litters 5 days prior to farrowing. In addition, Hb levels were available for 1127 one-day-old piglets from 383 litters (a maximum of three piglets per litter) of 277 sows with Hb levels. The average Hb levels in sows (sow Hb), their litters (litter Hb, based on average Hb of three piglets) and individual piglets (piglet Hb) were 112 ± 12.6 g/l, 103 ± 15.3 g/l and 105 ± 21.7 g/l, respectively. Heritabilities for Hb levels were 0.09 ± 0.07 for sow Hb, 0.19 ± 0.11 for litter Hb and 0.08 ± 0.05 for piglet Hb. Estimates for the permanent environment effect of sows were 0.09 ± 0.09 for sow Hb, 0.11 ± 0.12 for litter Hb and 0.12 ± 0.03 for piglet Hb. In comparison, heritabilities for both number of stillborn piglets and pre-weaning survival were lower (0.05 ± 0.01 and 0.04 ± 0.01). Sow BW had no significant heritability, while sow back fat depth was lowly heritable (0.10 ± 0.08). Positive genetic correlations were found between sow Hb and litter Hb (0.64 ± 0.47) and between litter Hb and sow back fat depth (0.71 ± 0.53). Higher litter Hb was genetically associated with lower number of stillborn piglets (−0.78 ± 0.35) and higher pre-weaning survival (0.28 ± 0.33). Negative genetic correlations between sow Hb and average piglet birth weight of the litter (−0.60 ± 0.34) and between piglet Hb and birth weight of individual piglets (−0.37 ± 0.32) indicate that selection for heavier piglets may reduce Hb levels in sows and piglets. Similarly, selection for larger litter size will reduce average piglet birth weight (r_g: −0.40 ± 0.12) and pre-weaning survival (−0.57 ± 0.13) and may lead to lower litter Hb (−0.48 ± 0.27). This study shows promising first results for the use of Hb levels as a selection criterion in pig breeding programs, and selection for higher Hb levels may improve piglet survival and limit further reduction in Hb levels in sows and piglets due to selection for larger and heavier litters.     

Genetic parameters for body weight,longissimus muscle depth and fat depth for Suffolk sheep in the Czech Republic

In this study, heritabilities and (co)variance components for body weight at 100 days (BW), muscle depth (MD) and fat depth (FD) were estimated for Suffolk, the most common sheep breed in the Czech Republic. Data from 1996 to 2004 were extracted from the sheep recording database of the Czech Sheep and Goat Breeding Association. Genetic parameters were estimated using multivariate animal models, including both direct and maternal genetic effects and permanent environmental effects. Average values for BW, MD and FD were 27.91 kg, 25.5 mm and 3.3 mm, respectively. Direct and maternal heritability for BW were 0.17 and 0.08, respectively, and direct heritabilities were 0.16 for MD and 0.08 for FD. Maternal heritability estimates for ultrasonic measurements were generally low. Direct genetic correlations between BW and MD and maternal genetic correlations between BW and MD were positive and favourable. Both direct genetic correlations between BW and FD and maternal genetic correlations between BW and FD were negative, but not significantly different from zero. The favourable genetic correlations between BW and MD make ultrasound measurements a valuable tool in breeding programs focusing on growth and carcass characteristics.     

Genotype by environment interaction in response to cold stress in a composite beef cattle breed

Extreme weather conditions such as cold stress influence the productivity and survivability of beef cattle raised on pasture. The objective of this study was to identify and evaluate the extent of the impact of genotype by environment interaction due to cold stress on birth weight (BW) and weaning weight (WW) in a composite beef cattle population. The effect of cold stress was modelled as the accumulation of total cold load (TCL) calculated using the Comprehensive Climate Index units, considering three TCL classes defined based on temperature: less than −5°C (TCL5), −15°C (TCL15) and −25°C (TCL25). A total of 4221 and 4217 records for BW and WW, respectively, were used from a composite beef cattle population (50% Red Angus, 25% Charolais and 25% Tarentaise) between 2002 and 2015. For both BW and WW, a univariate model (ignoring cold stress) and a reaction norm model were implemented. As cold load increased, the direct heritability slightly increased in both BW and WW for TCL5 class; however, this heritability remained consistent across the cold load of TCL25 class. In contrast, the maternal heritability of BW was constant with cold load increase in all TCL classes, although a slight increase of maternal heritability was observed for TCL5 and TCL15. The direct and maternal genetic correlation for BW and maternal genetic correlation for WW across different cold loads between all TCL classes were high (r > 0.99), whereas the lowest direct genetic correlations observed for WW were 0.88 for TCL5 and 0.85 for TCL15. The Spearman rank correlation between the estimated breeding value of top bulls (n = 79) using univariate and reaction norm models across TCL classes showed some re-ranking in direct and maternal effects for both BW and WW particularly for TCL5 and TCL15. In general, cold stress did not have a big impact on direct and maternal genetic effects of BW and WW.     

Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long‐term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation‐derived maternal links and microsatellite‐derived paternal links; (ii) Pedigree 2, using SNP‐derived assignment of both maternity and paternity; and (iii) whole‐genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.     

Genetic parameters for bone strength, osteochondrosis and meat percentage in Finnish Landrace and Yorkshire pigs

Osteochondrosis (OC) is a major factor causing joint problems that affect animal welfare and pork production profitability. Strong bones are also important in the slaughtering process, especially as broken bones can lead to rejections of parts of the carcass. In this study, 326 Finnish Yorkshire and 464 Finnish Landrace test station pigs were examined post mortem for bone strength and osteochondral lesions. The objective was to estimate genetic parameters for OC and bone strength and their genetic and phenotypic correlations with carcass meat percentage. Two formulas were used for lean meat percentage, the first one (Hennessy meat-%) comprising two fat thickness measurements and one muscle depth measurement, and the second one (test station meat-%) also including the weight of lean meat in ham. Finnish Yorkshire had stronger bones than Finnish Landrace on average, but also more OC in the proximal end of the humerus (36%) and the distal end of the femur (51%) than Finnish Landrace (29% and 31% OC in the humerus and femur, respectively). By using the data on both breeds, the OC heritability estimated was 0.05 in the humerus and 0.26 in the femur. The estimated heritability of bone strength was also moderate (0.26). Test station meat-% showed higher heritability (0.40) than meat-% based on the Hennessy formula (0.29). Genetic correlations between meat percentage and the other studied traits were weak and associated with high standard errors. The results show that a mild form of OC is common in both Finnish pig breeds; bone strength and OC in the distal end of the femur are moderately heritable and can be improved through selection; and selection for high meat percentage does not seem to affect bone strength or OC.     

Body development in sows, feed intake and maternal capacity. Part 2: gilt body condition before and after lactation, reproductive performance and correlations with lactation feed intake

Data on sow body weight (BW) and fatness (n = ~2250 pregnant sows) and reproductive data (including historical: n = ~18 000) were used to examine the genetic and phenotypic associations between body condition before and after farrowing, gestational outcomes, lactation feed intake and the gilts' ability to survive unculled to farrow in the second parity. Within-trait genetic correlations were very high between weight (0.77 ± 0.06) and fat depth (0.91 ± 0.04) recorded before farrowing and at weaning. Litter size traits were generally uncorrelated genetically with aspects of sow BW and body condition. However, genetic correlations indicated that sows producing heavier piglets at birth had litters with increased gain (0.36 ± 0.16), and were characterised by greater weight (-0.72 ± 0.08) and fat change (-0.19 ± 0.15) during lactation, reflected to a lesser extent by lower weight (-0.12 ± 0.11) and fatness (-0.17 ± 0.10) at weaning. Genetic correlations (r(a)) between reproductive traits and lactation feed intake were generally low, but favourable. However, lactation intake was positively correlated with measures of sow size (r(a) = ~0.55), such that selection for lactation feed intake would likely be accompanied by increased mature sow size. Phenotypic correlations (r(p)) showed that sow survival to the second parity (FAR12) was positively influenced by litter size and fat depth at weaning, supporting attributes of increased fatness before farrowing, less weight loss during lactation and an increased lactation intake.     

Genetic parameter estimates for pre-weaning performance and reproduction traits in Markhoz goats

Genetic parameters for growth, mortality and reproductive performances of Markhoz goats were estimated from data collected during 1993–2010 at Markhoz goat Performance Testing Station in Sanandaj, Iran. For kid performance traits 3763 records were available for birth weight (BW), 2931 for weaning weight (WW), average daily gain (ADG) and Kleiber ratio (KR) (approximated as ADW/WW^0.75) and 3032 for pre-weaning mortality (PWM). For doe reproductive performance traits there were 2920 records available for litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB) and litter mean weight per kid born (LMWKB), and 2182 for total litter weight at weaned (TLWW) and litter mean weight per kid weaned (LMWKW). Genetic parameters were estimated with univariate and bivariate models using restricted maximum likelihood (REML) procedures. Random effects were explored by fitting additive direct genetic effects, maternal additive genetic effects, maternal permanent environmental effects, the covariance between direct and maternal genetic effects, and common litter effects in different models for pre-weaning traits of kids. Also, in addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of PWM. Models for LSB, LSW, TLWB, TLWW, LMWKB, and LMWKW included direct additive genetic effects, permanent environmental effects due to the animal as well as service sire effects. Estimated direct heritabilities were moderate for pre-weaning traits (0.22 for BW, 0.16 for WW, 0.21 for ADG, and 0.27 for KR and 0.29 for PWM), and low for reproduction traits (0.01 for LSB, 0.01 for LSW, 0.02 for TLWB, 0.03 for TLWW, 0.07 for LMWKB, and 0.06 for LMWKW). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BW (0.07) and KR (0.04). The estimate for the maternal permanent environmental variance ratios (c²) varied from 0.01 for KR to 0.07 for WW and ADG. The magnitude of common litter variance ratios (l²) was more substantial for BW (0.46) than the PWM (0.19) and KR (0.16). The estimate for the permanent environmental variance due to the animal (c²) ranged from 0.03 for LMWKB to 0.07 for TLWB and LMWKW, whereas service sire effects (s²) ranged from 0.02 to 0.04. The correlation between direct and maternal genetic effects were negative and high for BW (?0.51) and KR (?0.62). The genetic correlations between pre-weaning growth traits were positive and moderate to strong, as were genetic correlations between reproductive traits. Between BW and PWM the correlation was ?0.35. Phenotypic and environmental correlations for all traits were generally lower than genetic correlations.     

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.     

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.     

Genetic parameters for direct and maternal effects on body weights of Draa goats

Genetic parameters and (co)variance components were estimated for weights at birth and at 30, 90 and 180 days of age for Draa goat maintained at Ouarzazate station over a period of 18 years (1988–2005). Records of 1498 kids, the progeny of 46 sires and 404 dams were used in the study. Analyses were carried out by restricted maximum likelihood. Six different animal models including or ignoring maternal genetic or permanent environmental effects were fitted for all traits. The Model 2 with only permanent environmental maternal effects seemed most suitable. Estimates of direct heritability from this model were 0.16 for birth weight and 0.07, 0.11 and 0.11 for weights at 30, 90 and 180 days, respectively. Maternal heritability estimates varied from 0.00 to 0.24 for all traits according to the model used (Models 4–6). Bivariate analysis by Model 2 was also used to estimate genetic correlations between traits. The estimates of genetic and phenotypic correlations among weights were positive and intermediate to high in value. Despite the low estimated heritabilities of body weight traits of Draa goat, there is a small genetic variability that may be exploited to improve growth performance.     

Genetic parameters for growth, reproductive and maternal traits in a multibreed meat sheep population

The genetic parameters for growth, reproductive and maternal traits in a multibreed meat sheep population were estimated by applying the Average Information Restricted Maximum Likelihood method to an animal model. Data from a flock supported by the Programa de Melhoramento Genético de Caprinos e Ovinos de Corte (GENECOC) were used. The traits studied included birth weight (BW), weaning weight (WW), slaughter weight (SW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to slaughter (GWS), weight gain from weaning to yearling (GWY), age at first lambing (AFL), lambing interval (LI), gestation length (GL), lambing date (LD - number of days between the start of breeding season and lambing), litter weight at birth (LWB) and litter weight at weaning (LWW). The direct heritabilities were 0.35, 0.81, 0.65, 0.49, 0.20, 0.15 and 0.39 for BW, WW, SW, YW, GBW, GWS and GWY, respectively, and 0.04, 0.06, 0.10, 0.05, 0.15 and 0.11 for AFL, LI, GL, LD, LWB and LWW, respectively. Positive genetic correlations were observed among body weights. In contrast, there was a negative genetic correlation between GBW and GWS (-0.49) and GBW and GWY (-0.56). Positive genetic correlations were observed between AFL and LI, LI and GL, and LWB and LWW. These results indicate a strong maternal influence in this herd and the presence of sufficient genetic variation to allow mass selection for growth traits. Additive effects were of little importance for reproductive traits, and other strategies are necessary to improve the performance of these animals.     

Genetic relationship between weaning weight and milk yield in Nguni cattle

A study was conducted to estimate the genetic relationship between weaning weight and milk yield in Nguni cattle. Milk yield data (n=125) were collected from 116 Nguni cows from Mara Research Station located in Limpopo Province and Loskop South Farm located in Mpumalanga Province using the weigh-suckle-weigh technique. Weaning weight data (n=19 065) were obtained from stud Nguni cattle from 146 herds distributed throughout South Africa. Estimates of (co)variance components for milk yield and weaning weight were calculated using PEST and VCE softwares. The average weaning weight, age of the calf at weaning and 24-h milk yield was 158.94 kg, 210 days and 5.25 kg/day, respectively. Heritability estimates for milk yield, direct and maternal weaning weight were 0.22±0.238, 0.47±0.039 and 0.25±0.029, respectively. Estimates of genetic correlations for milk yield and maternal weaning weight, milk yield and direct weaning weight, direct and maternal weaning weight were 0.97±0.063, −0.71±0.416 and −0.56±0.247, respectively. The results indicate that maternal weaning weight is genetically highly predictive of milk yield in Nguni cattle. Maternal breeding values for weaning weight could therefore be used as a selection criterion to improve milk yield in Nguni cattle.     

Genetic parameters for feed intake,litter weight,body condition and rebreeding success in primiparous Norwegian Landrace sows

The aim of this study was to estimate genetic parameters for feed intake recorded as farmers’ perception of young sows’ appetite for the first 3 weeks of lactation (APP) and feed intake recorded for one day in the 3rd week of lactation (FEED), litter weight (LW) at 3 weeks, sow body condition at weaning (BC) and the following five reproduction traits: weaning-to-service interval of 1 to 7 days (WSI7), weaning-to-service interval of 1 to 50 days (WSI50), delayed service or not (DELAYED), pregnant on first service or not (PREGNANT) and litter size in 2nd parity (NBT2). The analyses included data on 4606 Norwegian Landrace 1st-parity sows and their litters. The Gibbs sampling method was used. The traits DELAYED and PREGNANT were analysed as threshold traits and APP, FEED, LW, BC, WSI7, WSI50 and NBT2 were analysed as linear traits. The heritability estimates for APP and FEED were low (<0.1), whereas the estimates for DELAYED and PREGNANT were rather high (0.4 and 0.3). The heritability estimate for BC was 0.2. The genetic correlations confirmed the complexity of breeding for sow performance; selection for heavy 1st litters may lead to lower body condition at weaning, which in turn leads to lower reproductive performance and smaller litters in 2nd parity. Selection for higher sow feed intake would improve body condition, but the simple way of measuring feed intake tested in this study (APP and FEED) cannot be recommended because of the low heritability obtained for these traits.     

Bayesian inference of genetic parameters for ultrasound scanning traits of Kivircik lambs

Ultrasound scanning traits have been adapted in selection programs in many countries to improve carcass traits for lean meat production. As the genetic parameters of the traits interested are important for breeding programs, the estimation of these parameters was aimed at the present investigation. The estimated parameters were direct and maternal heritability as well as genetic correlations between the studied traits. The traits were backfat thickness (BFT), skin+backfat thickness (SBFT), eye muscle depth (MD) and live weights at the day of scanning (LW). The breed investigated was Kivircik, which has a high quality of meat. Six different multi-trait animal models were fitted to determine the most suitable model for the data using Bayesian approach. Based on deviance information criterion, a model that includes direct additive genetic effects, maternal additive genetic effects, direct maternal genetic covariance and maternal permanent environmental effects revealed to be the most appropriate for the data, and therefore, inferences were built on the results of that model. The direct heritability estimates for BFT, SBFT, MD and LW were 0.26, 0.26, 0.23 and 0.09, whereas the maternal heritability estimates were 0.27, 0.27, 0.24 and 0.20, respectively. Negative genetic correlations were obtained between direct and maternal effects for BFT, SBFT and MD. Both direct and maternal genetic correlations between traits were favorable, whereas BFT–MD and SBFT–MD had negligible direct genetic correlation. The highest direct and maternal genetic correlations were between BFT and SBFT (0.39) and between MD and LW (0.48), respectively. Our results, in general, indicated that maternal effects should be accounted for in estimation of genetic parameters of ultrasound scanning traits in Kivircik lambs, and SBFT can be used as a selection criterion to improve BFT.     

Heritability of the backtest response in piglets and its genetic correlations with production traits

The backtest response of a pig gives an indication of its coping style, that is, its preferred strategy to cope with stressful situations, which may in turn be related to production traits. The objective of this study was therefore to estimate the heritability of the backtest response and estimate genetic correlations with production traits (birth weight, growth, fat depth and loin depth). The backtest was performed by placing the piglet on its back for 60 s and the number of struggles (NrS) and vocalizations (NrV), and the latency to struggle and vocalize (LV) was recorded. In total, 992 piglets were subjected to the backtest. Heritability estimates for backtest traits were statistically moderate (although high for behavioral traits), with LV having the highest heritability estimate (0.56±0.10, P<0.001) and NrS having the lowest estimate (0.37±0.09, P<0.001). Backtest traits also had high genetic correlations with each other, with vocalization traits (NrV and LV) having the highest (−0.94±0.03, P<0.001), and NrS with NrV the lowest correlation (0.70±0.09, P<0.001). No significant correlations were found between backtest traits and production traits, but correlations between NrS and birth weight (−0.38±0.25), and NrV and loin depth (−0.28±0.19) approached significance (P=0.07). More research into genotype-by-environment interactions may be needed to assess possible connections between backtest traits and production traits, as this may depend on the circumstances (environment, experiences, etc.). In conclusion, heritability estimates of backtest traits are high and it would therefore be possible to select for them. The high genetic correlations between backtest traits indicate that it may be possible to only consider one or two traits for characterization and selection purposes. There were no significant genetic correlations found between backtest traits and production traits, although some of the correlations approached significance and hence warrant further research.