Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate

An alternative implementation of the animal model including indirect genetic effect (IGE) is presented considering pair-mate-specific interaction degrees to improve the performance of the model. Data consisted of average daily gain (ADG) records from 663 pigs kept in groups of 10 to 14 mates during the fattening period. Three types of models were used to fit ADG data: (i) animal model (AM); (ii) AM with classical IGE (AM-IGE); and (iii) AM fitting IGE with a specific degree of interaction between each pair of mates (AM-IGE_i). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGE_i: feeding rate (g/min), feeding frequency (min/day), the time between consecutive visits to the feeder (min/day), occupation time (min/day) and an index considering all these variables. All models included systematic effects batch, initial age (covariate), final age (covariate), number of pigs per pen (covariate), plus the random effect of the pen. Estimated posterior mean (posterior SD) of heritability was 0.47 (0.15) using AM. Including social genetic effects in the model, total heritable variance expressed as a proportion of total phenotypic variance (T²) was 0.54 (0.29) using AM-IGE, whereas it ranged from 0.51 to 0.55 (0.12 to 0.14) with AM-IGE_i, depending on the behavior trait used to define social interactions. These results confirm the contribution of IGEs to the total heritable variation of ADG. Moreover, important differences between models were observed in EBV rankings. The percentage of coincidence of top 10% animals between AM and AM-IGE_i ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGE_i. Based on the goodness of fit and predictive ability, social models are preferred for the genetic evaluation of ADG. Among models including IGEs, when the pair-specific degree of interaction was defined using feeding behavior phenotypes we obtained an increase in the accuracy of genetic parameters estimates, the better goodness of fit and higher predictive ability. We conclude that feeding behavior variables can be used to measure the interaction between pen mates and to improve the performance of models including IGEs.     

Impact of a high-fibre diet on genetic parameters of production traits in growing pigs

The use of diets with increased fibre content from alternative feedstuffs less digestible for pigs is a solution considered to limit the impact of increased feed costs on pig production. This study aimed at determining the impact of an alternative diet on genetic parameters for growth, feed efficiency, carcass composition and meat quality traits. A total of 783 Large White pigs were fed a high-fibre (HF) diet and 880 of their sibs were fed a conventional (CO) cereal-based diet. Individual daily feed intake, average daily gain, feed conversion ratio and residual feed intake were recorded as well as lean meat percentage (LMP), carcass yield (CY) and meat quality traits. Pigs fed the CO diet had better performances for growth and feed efficiency than pigs fed the HF diet. They also had lower LMP and higher CY. In addition, pigs fed the CO diet had lower loin percentage and ham percentage and higher backfat percentage. No differences were observed in meat quality traits between diets, except for a* and b* values. For all traits, the genetic variances and heritability were not different between diets. Genetic correlations for traits between diets ranged between 0.80 ± 0.13 and 0.99 ± not estimable, and none were significantly different from 0.99, except for LMP. Thus, traits in both diets were considered as mainly affected by similar sets of genes in the two diets. A genetic correlation lower than 0.80 would justify redesigning the breeding scheme; however, some genetic correlations did not differ significantly from 0.80 either. Therefore, larger populations are needed for a more definitive answer regarding the design of the breeding scheme. To further evaluate selection strategies, a production index was computed within diets for the 29 sires with estimated breeding value reliability higher than 0.35. The rank correlation between indices estimated in the CO and in the HF diet was 0.72. Altogether, we concluded that limited interaction between feed and genetics could be evidenced, and based on these results there is no need to change pig selection schemes to adapt to the future increased use of alternative feedstuffs in production farms.     

Genetic correlations among milk yield,morphology, performance test traits and somatic cells in dual-purpose Rendena breed

Selection in native local breeds needs great carefulness due to the small population size and the risk of inbreeding. Furthermore, most breeds are dual-purpose, and milk and beef attitudes are antagonistic. For preservation purposes functional traits need to be considered. Focusing on the small local Rendena cattle, this study aimed to analyse the genetic correlations among milk, beef and udder health traits and the response to selection predicted under different scenarios. The study considered milk, fat and protein yields (MY), factor scores for udder volume (UV), conformation (UC) and muscularity obtained from type traits scored on primiparous cows, and performance test traits (PT) measured on young bulls at test station: average daily gain, in vivo SEUROP fleshiness, in vivo dressing percentage. Somatic cell score (SCS) was considered as a functional trait, with a possibility of restricting its genetic gain to zero. The study considered 281 497 MY test-day data collected on 16 974 cows, and data from linear type evaluation on 11 992 primiparous cows for factor scores. The PT data were recorded on 1428 young bulls, and SCS obtained from cell counts at milk recording. Bi-trait restricted maximum likelihood animal model analyses were performed to assess genetic parameters. Heritability varied from 0.157 (fat) to 0.442 (dressing percentage). Udder volume and MY resulted positively genetically correlated (average correlation 0.427), whereas the low-negative genetic correlation between MY and UC (−0.141) suggested a negative impact of milk gain on udder form. Beef traits of factor muscularity and PT showed medium-high favourable genetic correlations (from 0.357 to 0.984), excluding a null correlation between daily gain and muscularity. The genetic correlation MY v. muscularity was unfavourable (−0.328 on average), whereas null correlations were found in MY v. PT, apart from fat v. dressing percentage (−0.151). Somatic cell score showed low unfavourable correlations with protein (0.111) and UV (0.092), and favourable correlations with UC (−0.193). Response to selection in different scenarios indicated a good balanced gain for milk and beef when standardized economic weights of 0.66 and 0.34 are given to the two attitudes, and SCS genetic gain is restricted. Current genetic trends (MY and PT increasing, but muscularity lessening) reflect a stronger selection for milk, suggesting a slight progressive change towards a milk conformation. Aiming to preserve the dual-purpose characteristics of a breed, proper breeding policies taking into account the genetic relationships among traits and including functional traits should be applied in local dual-purpose populations.     

Genetic parameters of sow feed efficiency during lactation and its underlying traits in a Duroc population

As a result of the genetic selection for prolificacy and the improvements in the environment and farms management, litter size has increased in the last few years so that energy requirements of the lactating sow are greater. In addition, selection for feed efficiency of growing pigs is also conducted in maternal lines, and this has led to a decrease in appetite and feed intake that is extended to the lactation period, so the females are not able to obtain the necessary energy and nutrients for milk production and they mobilize their energetic reserves. When this mobilization is excessive, reproductive and health problems occur which ends up in an early sow culling. In this context, it has been suggested to improve feed efficiency at lactation through genetic selection. The aim of this study is to know, in a Duroc population, the genetic determinism of sow feed efficiency during lactation and traits involved in its definition, as well as genetic and environmental associations between them. The studied traits are daily lactation feed intake (dLFI), daily sow weight balance (dSWB), backfat thickness balance (BFTB), daily litter weight gain (dLWG), sow residual feed intake (RFI) and sow restricted residual feed intake (RRFI) during lactation. Data corresponded to 851 parities from 581 Duroc sows. A Bayesian analysis was performed using Gibbs sampling. A four-trait repeatability animal model was implemented including the systematic factors of batch and parity order, the standardized covariates of sow weight (SW_f) and litter weight (LWs) at farrowing for all traits and lactation length for BFTB. The posterior mean (posterior SD) of heritabilities were: 0.09 (0.03) for dLFI, 0.37 (0.07) for dSWB, 0.09 (0.03) for BFTB, 0.22 (0.05) for dLWG, 0.04 (0.02) for RFI and null for RRFI. The genetic correlation between dLFI and dSWB was high and positive (0.74 (0.11)) and null between dLFI and BFTB. Genetic correlation was favourable between RFI and dLFI and BFTB (0.71 (0.16) and −0.69 (0.18)), respectively. The other genetic correlations were not statistically different from zero. The phenotypic correlations were low and positive between dLFI and dSWB (0.27 (0.03), dSWB and BFTB (0.25 (0.04)), and between dLFI and dLWG (0.16 (0.03)). Therefore, in the population under study, the improvement of the lactation feed efficiency would be possible either using RFI, which would not have unfavourable correlated effects, or through an index including its component traits.     

Genetic relationship among somatic cell score and some milking traits in Holstein-Friesian primiparous cows milked by an automated milking system

The automated milking system provides breeders with a large amount of automatically collected information about each cow in herd that cannot be easily obtained in non-robotised systems. This knowledge can be used in breeding programs improving somatic cell count (SCC) level. The objective of this study was to estimate heritabilities and genetic correlations among test-day (TD) somatic cell score (SCS) and selected milking traits, such as daily milk yield (MY), milking frequency (MF), milking time (MT) and milking speed (MS), attachment time (AT) to single teat cups, electrical conductivity (EC) and milk temperature (MTEMP). Data were collected for 1 899 Polish Holstein-Friesian primiparous cows milked in an automatic milking system. Genetic parameters of the studied traits were estimated using Bayesian method via Gibbs sampling and two-trait random regression animal model with fixed effect of herd x TD, fixed regressions on days in milk (DIM) nested within age at calving by season of calving and RR for additive genetic and permanent environmental effects. Both fixed and RR were fitted with fourth-order Legendre polynomials on DIM. The estimated daily heritabilities were in the following ranges: MY – 0.162–0.338, MF – 0.156–0.444, MT – 0.090–0.320, MS – 0.252–0.665, AT – 0.105–0.394, EC – 0.269–0.466, MTEMP – 0.135–0.304 and SCS – 0.155–0.321. The heritabilities for traits expressed on a 305-d basis were moderate to high: 0.460 for MY, 0.514 for MF, 0.315 for MT, 0.431 for MS, 0.256 for AT, 0.386 for EC, 0.407 for MTEMP and 0.359 for SCS. Genetic correlations between traits on a 305-d basis showed that SCS was most strongly genetically correlated with MTEMP (0.572) and MS (0.480), whereas genetic relationships of SCS with MT (0.221) and EC (− 0.216) were moderate. Phenotypic correlations between traits on a 305-d basis were moderate or low. Somatic cell score was negatively phenotypically correlated with MY, MF and MT, with the highest relationship with MT (− 0.302). The largest positive phenotypic correlations were observed between SCS and MS (0.311) and with MTEMP (0.286). In summary, it is concluded that there is a chance to carry out effective selection for lower SCS and for some other traits, in particular MS and MTEMP. The obtained results are promising enough to conduct further research to evaluate how these traits can be used both to increase the accuracy of genetic evaluations of SCC and to improve udder health.     

Estimation of social genetic effects on feeding behaviour and production traits in pigs

Pigs are housed in groups during the test period. Social effects between pen mates may affect average daily gain (ADG), backfat thickness (BF), feed conversion rate (FCR), and the feeding behaviour traits of pigs sharing the same pen. The aim of our study was to estimate the genetic parameters of feeding behaviour and production traits with statistical models that include social genetic effects (SGEs). The data contained 3075 Finnish Yorkshire, 3351 Finnish Landrace, and 968 F1-crossbred pigs. Feeding behaviour traits were measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent in feeding per visit (TPV), feed intake per visit (FPV), and feed intake rate (FR). The test period was divided into five periods of 20 days. The number of pigs per pen varied from 8 to 12. Two model approaches were tested, i.e. a fixed group size model and a variable group size model. For the fixed group size model, eight random pigs per pen were included in the analysis, while all pigs in a pen were included for the variable group size model. The linear mixed-effects model included sex, breed, and herd*year*season as fixed effects and group (batch*pen), litter, the animal itself (direct genetic effect (DGE)), and pen mates (SGEs) as random effects. For feeding behaviour traits, estimates of the total heritable variation (T² ± SE) and classical heritability (h² ± SE, values given in brackets) from the variable group size model (e.g. period 1) were 0.34 ± 0.13 (0.30 ± 0.04) for NVD, 0.41 ± 0.10 (0.37 ± 0.04) for TPD, 0.40 ± 0.15 (0.14 ± 0.03) for DFI, 0.53 ± 0.15 (0.28 ± 0.04) for TPV, 0.66 ± 0.17 (0.28 ± 0.04) for FPV, and 0.29 ± 0.13 (0.22 ± 0.03) for FR. The effect of social interaction was minimal for ADG (T² = 0.29 ± 0.11 and h² = 0.29 ± 0.04), BF (T² = 0.48 ± 0.12 and h² = 0.38 ± 0.07), and FCR (T² = 0.37 ± 0.12 and h² = 0.29 ± 0.04) using the variable group size model. In conclusion, the results indicate that social interactions have a considerable indirect genetic effect on the feeding behaviour and FCR of pigs but not on ADG and BF.     

Digestive efficiency traits in growing pigs are genetically correlated with sow litter traits in the Large White breed

Digestive efficiency traits are promising selection criteria to improve feed efficiency in pigs. However, the genetic relationships between digestive efficiency and sow reproductive traits are mostly unknown and need to be estimated. In this study, reproductive traits were available for 61 601 litters recorded on 21 719 Large White purebred sows. The traits were comprised of the number of born alive (NBA) and the number of weaned piglets (NWP), the number of stillbirths (NSB) and piglet mortality during suckling (PM). For a subset of 32 518 litters, the mean (MBW) and CV of piglet birth weights (CVBW) were deduced from individual piglet weights as well as the proportion of piglets weighing less than 1 kg (PPL1K). Growth and feed efficiency traits were available for 4 643 Large White male pigs related to sows with reproductive performances. They comprised average daily gain (ADG), daily feed intake (DFI) and feed conversion ratio (FCR). A subset of 1 391 pigs had predictions for digestibility coefficients (DC) of energy, organic matter and nitrogen obtained by analysing faecal samples with near-infrared spectrometry. Estimated heritabilities were low for NBA, NSB, NWP and PM (0.08 ± 0.01 to 0.11 ± 0.01) and low to moderate for litter weight characteristics (0.14 ± 0.02 to 0.38 ± 0.01). Heritability estimates were moderate to high for ADG, DFI and FCR (0.37 ± 0.04 to 0.54 ± 0.05) and moderate for DC traits (0.26 ± 0.06 to 0.38 ± 0.07). Genetic correlations were low between ADG, or alternatively FCR, and reproductive traits. They were significantly different from zero with MBW (0.19 ± 0.06 with ADG and ?0.15 ± 0.06 with FCR) and PPL1K (?0.19 ± 0.07 with ADG and 0.18 ± 0.07 with FCR). All genetic correlations between DFI and reproductive traits were low and not significantly different from zero. Genetic correlations between DC traits and NBA were significantly different from zero for DC of organic matter and energy (<?0.25 ± 0.11). DC traits were moderately correlated with MBW (>0.30 ± 0.11), CVBW (<?0.36 ± 0.11) and PPL1K (<?0.37 ± 0.11) at the genetic level. Genetic correlations between DC traits and PM were significantly negative and hence favourable (<?0.38 ± 0.12). Finally, genetic correlations between DC traits and NWP were close to zero. These results suggested that sows closely related to growing pigs with the best digestive efficiency would produce heavier and more homogeneous piglets, with slightly smaller litter sizes at birth but better survival. Hence, there is usable genetic variation in DC that could be exploited to define new selection strategies in maternal lines aiming at improving not only feed efficiency but also piglet survival.     

Evaluating environmental impacts of selection for residual feed intake in pigs

To identify a proper strategy for future feed-efficient pig farming, it is required to evaluate the ongoing selection scenarios. Tools are lacking for the evaluation of pig selection scenarios in terms of environmental impacts to provide selection guidelines for a more sustainable pig production. Selection on residual feed intake (RFI) has been proposed to improve feed efficiency and potentially reduce the associated environmental impacts. The aim of this study was thus to develop a model to account for individual animal performance in life cycle assessment (LCA) methods to quantify the responses to selection. Experimental data were collected from the fifth generation of pig lines divergently selected for RFI (low line, more efficient pigs, LRFI; high line, less efficient pigs, HRFI). The average feed conversion ratio (FCR) and daily feed intake of LRFI pigs were 7% lower than the average of HRFI pigs (P < 0.0001). A parametric model was developed for LCA based on the dietary net energy fluxes in a pig system. A nutritional pig growth tool, InraPorc®, was included as a module in the model to embed flexibility for changes in feed composition, animal performance traits and housing conditions and to simulate individual pig performance. The comparative individual-based LCA showed that LRFI had an average of 7% lower environmental impacts per kilogram live pig at farm gate compared to HRFI (P < 0.0001) on climate change, acidification potential, freshwater eutrophication potential, land occupation and water depletion. High correlations between FCR and all environmental impact categories (>0.95) confirmed the importance of improvement in feed efficiency to reduce environmental impacts. Significant line differences in all impact categories and moderate correlations with impacts (>0.51) revealed that RFI is an effective measure to select for improved environmental impacts, despite lower correlations compared to FCR. Altogether more optimal criteria for efficient environment-friendly selection can then be expected through restructuring the selection indexes from an environmental point of view.     

Genetic parameters for feed efficiency in Romane rams and responses to single-generation selection

Feeding costs represent one of the highest expenditures in animal production systems. Breeding efficient animals that express their growth potential while eating less is therefore a major objective for breeders. We estimated the genetic parameters for feed intake, feed efficiency traits (residual feed intake (RFI) and feed conversion ratio (FCR)), growth and body composition traits in the Romane meat sheep breed. In these traits, selection responses to single-generation divergent selection on RFI were evaluated. From 2009 to 2016, a total of 951 male lambs were tested for 8 weeks starting from 3 months of age. They were weighed at the beginning and at the end of the testing period. Backfat thickness and muscle depth were recorded at the end of the testing period through ultrasound measurements. Feed intake was continuously recorded over the testing period using the automatic concentrate feeders. The heritability of RFI was estimated at 0.45 ± 0.08, which was higher than the heritability of FCR (0.30 ± 0.08). No significant genetic correlations were observed between RFI and growth traits. A favourable low negative genetic correlation was estimated between RFI and muscle depth (−0.30 ± 0.15), though additional data are needed to confirm these results. The selection of low RFI sires based on their breeding values led to the production of lambs eating significantly less concentrate (3% decrease in the average daily feed intake), but with the same growth as lambs from sires selected based on high RFI breeding values. We concluded that in meat sheep, RFI is a heritable trait that is genetically independent of post-weaning growth and body composition traits. A one-generation divergent selection based on RFI breeding values highlighted that substantial gains in feeding costs can be expected in selection schemes for meat sheep breeds.     

Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. I. Genetic parameters

Genetic parameters of body weight at 4 (W4 w), 8 (W8 w) and 22 (W22 w) weeks of age, days from 20 to 100 kg (DT), average backfat thickness at 100 kg (ABT), teat number (TEAT), number of good teats (GTEAT), total number of piglets born (TNB), born alive (NBA) and weaned (NW) per litter, and birth to weaning survival rate (SURV) were estimated in the Chinese × European Tiameslan composite line using restricted maximum likelihood methodology applied to a multiple trait animal model. Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. Different models were fitted to the data in order to estimate the importance of maternal effects on production traits, as well as genetic correlations between male and female performance. The results showed the existence of significant maternal effects on W4w, W8w and ABT and of variance heterogeneity between sexes for W22w, DT, ABT and GTEAT. Genetic correlations between sexes were 0.79, 0.71 and 0.82, respectively, for W22w, DT and ABT and above 0.90 for the other traits. Heritability estimates were larger than (ABT and TEAT) or similar to (other traits) average literature values. Some genetic antagonism was evidenced between production traits, particularly W4w, W8w and ABT, and reproductive traits.     

Genetic parameters for carcass weight,conformation and fat in five beef cattle breeds

Profitability of beef production can be increased by genetically improving carcass traits. To construct breeding value evaluations for carcass traits, breed-specific genetic parameters were estimated for carcass weight, carcass conformation and carcass fat in five beef cattle breeds in Finland (Hereford, Aberdeen Angus, Simmental, Charolais and Limousin). Conformation and fat were visually scored using the EUROP carcass classification. Each breed was separately analyzed using a multitrait animal model. A total of 6879–19 539 animals per breed had phenotypes. For the five breeds, heritabilities were moderate for carcass weight (h²=0.39 to 0.48, s.e.=0.02 to 0.04) and slightly lower for conformation (h²=0.30 to 0.44, s.e.=0.02 to 0.04) and carcass fat (h²=0.29 to 0.44, s.e.=0.02 to 0.04). The genetic correlation between carcass weight and conformation was favorable in all breeds (r_G=0.37 to 0.53, s.e.=0.04 to 0.05), heavy carcasses being genetically more conformed. The phenotypic correlation between carcass weight and carcass fat was moderately positive in all breeds (r_P=0.21 to 0.32), implying that increasing carcass weight was related to increasing fat levels. The respective genetic correlation was the strongest in Hereford (r_G=0.28, s.e.=0.05) and Angus (r_G=0.15, s.e.=0.05), the two small body-sized British breeds with the lowest conformation and the highest fat level. The correlation was weaker in the other breeds (r_G=0.08 to 0.14). For Hereford, Angus and Simmental, more conformed carcasses were phenotypically fatter (r_P=0.11 to 0.15), but the respective genetic correlations were close to zero (r_G=−0.05 to 0.04). In contrast, in the two large body-sized and muscular French breeds, the genetic correlation between conformation and fat was negative and the phenotypic correlation was close to zero or negative (Charolais: r_G=−0.18, s.e.=0.06, r_P=0.02; Limousin: r_G=−0.56, s.e.=0.04, r_P=−0.13). The results indicate genetic variation for the genetic improvement of the carcass traits, favorable correlations for the simultaneous improvement of carcass weight and conformation in all breeds, and breed differences in the correlations of carcass fat.     

Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs

A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1 449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to escribe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550 000 rounds each, from which 50 000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.     

Impact of environmental disturbances on estimated genetic parameters and breeding values for growth traits in pigs

Due to the diversification of farming systems and climate change, farm animals are exposed to environmental disturbances to which they respond differently depending on their robustness. Disturbances such as heat stress or sanitary challenges (not always recorded, especially when they are of short duration and low intensity) have a transitory impact on animals, resulting in changes in phenotypes of production (feed intake, BW, etc.). The aim of this study was to evaluate the impact of such unknown disturbances on the estimated genetic parameters and breeding values (BV) for production traits. A population of 6 120 individuals over five generations divided into eight batches of 10 pens was generated, each individual underwent an ?100-day test period. A longitudinal phenotype mimicking piglet weight during the fattening period was simulated for each individual in two situations: disturbed and non-disturbed. The disturbed phenotype was modified according to the robustness of the animal and the intensity and duration of the disturbance that the animal was subjected to. Various sets of simulations (1 000 replicates per set) were considered depending on the type of disturbance (at the level of the batch, pen, or individual), the genetic correlation (negative, neutral, or positive) between the two components of the robustness (resistance and resilience), the genetic correlation (negative, neutral, or positive) between growth and the components of robustness, and the heritability of the components of robustness (weak or moderate). An animal model was used to estimate the genetic parameters and BV for two production traits: the BW at 100 days of age (BW₁₀₀) and average daily gain (ADG). The estimated heritability of the production traits was lower in the disturbed situation compared to the non-disturbed one (reduction of 0.08 and 0.05 points respectively for BW₁₀₀ and ADG). The correlations between estimated breeding values of the observed phenotypes (EBV) and BV for production traits in absence of disturbance were lower in the disturbed situation (reduction of 0.04 and 0.06 points for BW₁₀₀ and ADG respectively) while the partial correlation between EBV and BV for robustness was not significantly different from 0 in the two situations. These results suggest that selection in a well-controlled environment with random disturbances of low intensities does not allow to improve animal robustness while it is less effective for improving production traits than selection under no environmental disturbances.     

Genetic aspects for the behaviour of lactating sows towards humans

With the keeping of lactating sows in loose housing systems, ensuring work safety for stockpersons is gaining importance. Aim of the present study was to develop tests characterising the behaviour of lactating sows in farrowing environments with more freedom to move. The behaviour towards humans in different management procedures was examined. Emphasis was given to integrate tests into daily routines. The study was conducted in a nucleus herd with 771 purebred Landrace sows. Data were collected from October 2016 until December 2018. Sows were kept in individual indoor pens with movable farrowing crates in which the animals were restrained from 7 days antepartum (ap) to an average of 7 days postpartum (pp). The Dummy Arm Test (DAT; 1444 observations) was used to assess the sows’ reaction towards a stockperson handling the piglets around day 4 pp (closed crates). With the Towel Test (TT; 2846 observations), the reaction of sows to a novel object and an unexpected situation was assessed. The Trough Cleaning Test (TCT; 2805 observations) described the sows’ response to common procedures such as trough cleaning. TT and TCT were conducted on days 3 pp (closed crates) and 10 pp (open crates). Variance components of behavioural traits were estimated univariately with a linear animal model, and genetic correlations between traits were derived using a multivariate animal model in ASreml 3.0. Most sows showed no or only a slight reaction to human interactions without attempting to attack them. However, a strong defensive reaction of sows was recorded in 4.0% (TCT), 4.5% (TT), and 10.7% (DAT) of observations. This behaviour of sows was observed more frequently in the open than in the closed pen system. Estimates of heritabilities (h² ± SE) were h² = 0.17 ± 0.05 for behaviour of sows towards humans (DAT), h² = 0.19 ± 0.04 for response of sows towards unexpected situations (TT), and h² = 0.13 ± 0.04 for reactions of animals to TCT. Genetic correlations (r_g ± SE) ranged from r_g = 0.59 ± 0.37 between TT and TCT to r_g = 0.77 ± 0.30 between TT and DAT. Our results show that the developed tests are suitable for assessing the behaviour of sows towards humans. Behavioural traits derived from these tests could be used as new phenotypes for the genetic selection of gentle and easy-to-handle sows. The genetic correlations of all tests studied were positive indicating related reaction patterns.     

Evolution of viscera and muscle fractional protein synthesis rate in lean meat selected hybrids and castrated Duroc pigs fed under moderate crude protein restriction

Differences in producing performance and organoleptic meat characteristics among pig genotypes and/or producing types are widely known. These parameters are also subjected to the animal’s development, feeding and management. Detailed knowledge of the effects of production phase (PP), pig producing type (PT), dietary protein availability and their interactions on nutrient digestibility, nitrogen balance and protein metabolism is essential information to improve precision feeding techniques. The experiment was a 2 (PP) × 2 (PT) × 2 (diet) factorial design conducted with 32 male pigs, 16 entire F2 pigs progeny of Pietrain sires and Duroc × Landrace dams, and 16 castrated purebred Durocs belonging to two production phases (growing: 29.5 ± 3.19 v. fattening: 88.6 ± 6.26 kg BW), and assigned to one of two dietary CP levels, either standard (SP: 17% in growing and 15% in fattening) or low (LP: 15% in growing and 13% in fattening). Viscera and muscle fractional protein synthesis rates (FSRs; %/day) were conducted through a single infusion of 15% L-[ring-²H₅]-phenylalanine, with subsequent blood sampling from 12 to 40 min, and sample collection of liver, duodenum, biceps femoris and longissimus dorsi skeletal muscles after sacrifice. Fattening animals acquired a greater feed ingestion capacity, average daily gain (P < 0.01) and apparent ileal digestibility, whereas growing pigs showed higher FSRs in both viscera (duodenum and liver) and in longissimus dorsi. F2 pigs showed higher average daily gain, nitrogen retention rates and FSR in liver and longissimus dorsi (P < 0.01). Nevertheless, apparent ileal digestibility in all essential amino acids was lower in F2 compared with Duroc pigs (P < 0.05). Protein metabolism was barely influenced by dietary CP content, although animals fed LP registered the lowest apparent ileal digestibility for CP and also for most of the essential amino acids compared with SP-fed pigs. This information may reveal differences in amino acid requirements between both PTs, with Duroc pigs receiving excess of dietary amino acids.     

Using quantile regression methodology to evaluate changes in the shape of growth curves in pigs selected for increased feed efficiency based on residual feed intake

Growth rate is a major component of feed efficiency when estimating residual feed intake (RFI). Quantile regression (QR) methodology can be used to identify animals with different growth trajectories. The objective of this study was to evaluate the use of QR to identify phenotypic and genetic differences in pigs selected for low RFI. Using performance data on 750 Yorkshire pigs selected for low RFI, individual average daily gain (ADG), average daily feed intake (ADFI), RFI and Gompertz growth curve parameters (asymptotic weight (a), inflection point (b) and decay parameter (c)) were estimated for each pig. Using QR methodology, three Gompertz growth curves were estimated for the whole population for three quantiles (0.1, 0.5 and 0.9) of the BW data. Each animal was classified into one of the quantile regression groups (QRG) based on their overall Euclidian distance between each observed and estimated BW from the quantile growth curves. These three curves were also estimated using only part of the data (generations −1 to 3, and −1 to 4) in order to evaluate the agreement classification rate of animals from later generations into QRGs. We evaluated the effect of QRG on growth parameters and performance traits. Genetic parameters were estimated for these traits, as well as for QRG. In addition, genetic trends for each QRG were estimated. Three distinct growth curves were observed for animals classified into either quantiles 0.1 (QRG_0.1), 0.5 (QRG_0.5) or 0.9 (QRG_0.9). When only part of the data was used to estimate quantile growth curves, all animals from QRG_0.1 were correctly classified in their group. Animals in QRG_0.1 had significantly lower ADFI, ADG and RFI, and greater a, b and c than animals in the other groups. Quantile regression groups analysed as a trait was highly heritable (0.41) and had high (0.8) and moderate (0.46) genetic correlations with ADG and RFI, respectively. Selection for reduced RFI increased the number of animals classified as QRG_0.1 in the population. Overall, downward genetic trends were observed for all traits as a function of selection for reduced RFI. However, QRG_0.1 was the only group that had a positive genetic trend for ADG. Altogether, these results indicate that selection for reduced RFI changes the shape of growth curves in Yorkshire in pigs, and that QR methodology was able to identify animals having different genetic potential for feed efficiency, bringing a new opportunity to improve selection for reduced RFI.     

Correlated responses on growth traits after two-stage selection for ovulation rate and litter size in rabbits

Rabbit commercial maternal lines are usually selected for litter size (LS) and paternal lines for growth rate (GR). Line OR_LS was selected by ovulation rate (OR) and LS to improve LS more efficiently. In this study, growth traits of line OR_LS were evaluated by estimating the correlated response on weaning weight (WW), slaughter weight (SW) and GR during fattening period as well as their variability (DWW, DSW and DGR, respectively). Data were analyzed using Bayesian inference methods. Heritability estimates were low for growth traits (0.09, 0.13 and 0.14 for WW, SW and GR, respectively) and negligible for growth traits variability (0.01, 0.004 and 0.01 for DWW, DSW and DGR, respectively). Moderate common litter effect ratio (c²; 0.35, 0.28 and 0.27) and low maternal effect ratio (m²; 0.11, 0.05 and 0.01) were obtained for WW, SW and GR, respectively. Both c² and m² were lower at slaughter than at weaning. In addition, low common litter effect and negligible maternal effect were observed for growth traits variability. Genetic correlations between LS and both growth traits and their variability were close to zero. Positive genetic correlations were observed between OR and growth traits (0.19, 0.38 and 0.36 for WW, SW and GR, respectively) as well as between OR and growth traits variability (0.35, 0.62 and 0.20 for DWW, DSW and DGR, respectively). Positive correlated responses in both periods were obtained for growth traits, WW, SW and GR (0.037, 0.156 and 0.110 kg, respectively). The correlated response found in growth traits might be due to the positive genetic correlations between OR and these traits. However, selection for OR and LS using independent culling levels did not modify the growth traits variability. Therefore, no negative consequences on growth traits can be expected in current commercial maternal lines.     

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

The improvement of efficiency traits, such as protein efficiency (PE), digestible energy efficiency (EnE) and lipid gain (LipG), are relevant given their associations with environmental pollution, cost of production, and the quality of meat. However, these traits are difficult to measure and usually require slaughtering of pigs. Efficiency traits are complex, and several factors, such as genetic predisposition, feed composition, but also individual feeding behaviour may contribute to efficiency. The objective of this study was therefore to evaluate the potential of using feeding behaviour traits to predict efficiency traits under dietary protein restriction. A total of 587 Swiss Large White pigs, consisting of 312 females and 275 castrated males, had ad libitum access to feed and water, and were fed a protein-reduced diet (80% of recommended digestible protein and essential amino acids) from 22.5 ± 1.6 to 106.6 ± 4.6 kg BW. Individual feed intake was monitored and carcass composition (lean and fat mass) at slaughter was determined by dual-energy X-ray absorptiometry. The PE and EnE were calculated as the ratio of protein or energy in the carcass (estimated by dual-energy X-ray absorptiometry) to the total protein or energy consumed. Feeding behaviour traits monitored were daily feed intake, feed intake per meal, number of daily meals, duration per meal, feeding rate, and feeder occupation. A partial least square (PLS) regression was used to predict PE, EnE and LipG from feeding behaviour traits, while including farrowing series (for PE only), age at slaughter and BW at slaughter. Accuracy of PLS regression was assessed based on RMSE and R² for calibration and validation sets, and on concordance correlation coefficient, which were estimated over 100 replicates of calibration and validation sets. Models with a number of latent variables of 5, 2 and 3 were identified as optimal for PE, EnE, and LipG, which explained 34.64%, 55.42% and 82.68% of the total variation in PE, EnE, and LipG, respectively. Significant concordance correlation coefficient was found between predicted and observed values for PE (0.50), EnE (0.70), and LipG (0.90). In conclusion, individual feeding behaviour traits can better predict EnE and LipG than for PE under dietary protein restriction when fed ad libitum.     

Analysis of genetic correlations between beef traits in young bulls and primiparous cows belonging to the dual-purpose Rendena breed

Selection for beef traits in Italian dual-purpose breeds is often carried out using growth and in vivo conformation recorded on young, performance tested bulls and muscularity traits scored during routinely linear type evaluation on primiparous cows. In this context, the knowledge of the genetic structure of traits obtained in different sexes and at different times is necessary for a proper selection plan. This study aimed to estimate, in the local dual-purpose Rendena breed, the genetic relationships between muscularity linear type traits from primiparous cows, the same traits scored on candidate young bulls, and the performance test traits recorded in candidate young bulls. Type traits included: front (chest and shoulder), back (loins and rump); thigh, buttocks side and rear views (two traits). Performance test traits were: average daily gain; EUROP fleshiness evaluation; and dressing percentage. Muscularity linear type traits were recorded on 11 992 first parity cows, and the muscularity type traits were scored on 957 candidate young bulls. Heritability estimates obtained for muscularity traits were moderate in young bulls (on average 0.326), about 16% higher than in primiparous cows. The average heritability for performance test traits in young bulls resulted 0.342. Moderate to strong genetic correlations were found between performance test and muscularity type traits collected in young bulls (from 0.500 between front (chest and shoulder) and average daily gain to 0.955 between thigh, buttocks side view and in vivo dressing percentage). The genetic relationships obtained between muscularity linear type traits of primiparous cows and performance traits of young bulls were variable (from a null correlation between front (chest and shoulder) and average daily gain to 0.822 between thigh, buttocks rear view and dressing percentage), with an average genetic correlation of 0.532. Generally, the traits measured during performance testing in young bulls were favourably correlated with muscularity traits evaluated on primiparous cows, indicating a common selection pathway.     

Validation of an approximate approach to compute genetic correlations between longevity and linear traits

The estimation of genetic correlations between a nonlinear trait such as longevity and linear traits is computationally difficult on large datasets. A two-step approach was proposed and was checked via simulation. First, univariate analyses were performed to get genetic variance estimates and to compute pseudo-records and their associated weights. These pseudo-records were virtual performances free of all environmental effects that can be used in a BLUP animal model, leading to the same breeding values as in the (possibly nonlinear) initial analyses. By combining these pseudo-records in a multiple trait model and fixing the genetic and residual variances to their values computed during the first step, we obtained correlation estimates by AI-REML and approximate MT-BLUP predicted breeding values that blend direct and indirect information on longevity. Mean genetic correlations and reliabilities obtained on simulated data confirmed the suitability of this approach in a wide range of situations. When nonzero residual correlations exist between traits, a sire model gave nearly unbiased estimates of genetic correlations, while the animal model estimates were biased upwards. Finally, when an incorrect genetic trend was simulated to lead to biased pseudo-records, a joint analysis including a time effect could adequately correct for this bias.