Growth data on Jersey crossbred calves, maintained at ICAR-National Dairy Research Institute, Eastern Regional Station, Kalyani, Nadia, West Bengal, India, were collected and analysed to assess the influence of maternal effects on growth traits of calves. Traits considered for this study were birth weight (BW) and weights at 3 months (W3M), 6 months (W6M), 9 months (W9M) and 12 months (W12M) of age. Least-squares analyses were employed to obtain the effects of non-genetic factors on the traits of interest. Determination of influence of maternal effects on growth traits was estimated by fitting three univariate animal models (including or excluding maternal effects) using Bayesian approach. The most appropriate model for each trait was selected based on Deviance Information Criterion. Direct heritability (h2) estimates for BW, W3M, W6M, W9M and W12M were 0.31 ± 0.08, 0.26 ± 0.10, 0.48 ± 0.10, 0.44 ± 0.11 and 0.39 ± 0.14, respectively, under the best model. Permanent environmental maternal effects (c2) varied from 0.04 to 0.12 for all traits. Existence of maternal effects for all ages reflects the importance of maternal components for these traits. Moderate to high heritability estimates for growth traits indicate the possibility of modest genetic progress for these traits through selection under prevalent management system.

This study investigates the genetic and phenotypic aspects of early growth performance in the Murciano-Granadina goat breed, using data collected between 2016 and 2022 from a private dairy farm in Ghale-Ganj city, located in the southern area of Kerman province, Iran. Pedigree and data information were collected on several early body weight traits, including birth weight (BW), weaning weight (WW), average daily gain (ADG), Kleiber ratio (KR) and growth efficiency from birth to weaning (GE). Nine univariate animal models included direct additive genetic effects and different combinations of maternal effects were compared by using Akaike information criterion (AIC). Among the tested models, the best genetic analysis model for BW, included direct additive, maternal additive, maternal permanent and maternal temporary environmental effects. The best model for ADG, KR and GE included direct additive, maternal permanent and litter effects. For WW, the best model was determined to be one that included direct additive and maternal additive genetic effects. The estimated direct heritabilities were low values of 0.04, 0.07, 0.08, 0.05 and 0.07 for BW, ADG, KR, GE and WW, respectively. The estimates of genetic correlations among the studied traits were positive and low to high in magnitude which ranged from 0.11 for BW-KR to 0.91 for BW-GE. The phenotypic correlations ranged from 0.03 for KR-WW to 0.87 for ADG-KR. The positive correlations observed among the studied growth traits of the Murciano-Granadina goat breed indicate no negative genetic or phenotypic changes associated with selection for these traits.

This study aimed to conduct a meta-analysis based on a random-effects model to combine different published heritability estimates and genetic correlations for milk and serum minerals in dairy cows. In total, 59 heritability and 25 genetic correlation estimates from 12 articles published between 2009 and 2021 were used. The heritability estimates for milk macro-minerals were moderate to high and ranged from 0.311 (for Na) to 0.420 (for Ca). On the other hand, milk micro-minerals had lower heritabilities with a range from 0.013 (for Fe) to 0.373 (for Zn). The heritability estimates for serum macro-minerals were generally low and varied from 0.126 (for K) to 0.206 (for Mg). The estimates of genetic correlation between milk macro-minerals varied from −0.024 (between Na and K) to 0.625 (between Mg and P). The genetic correlations of milk Ca and P with milk yield were −0.171 and −0.211, respectively. The estimates of genetic parameters reported in this meta-analysis study are appropriate to utilize in breeding plans when valid estimates are not available for milk minerals in dairy cow populations.

The study reported in this Research Communication was conducted to estimate genetic parameters for different lactation persistency indices and their association with reproductive traits in Jersey crossbred cattle. Data on lactation traits (part lactation yields and 305-days milk yield) comprising all lactations as well as reproductive traits viz. calving interval, conception rate and gestation length of 378 Jersey crossbred cattle, maintained at National Dairy Research Institute, Kalyani, West Bengal, India, were collected over a period of 35 years (1982–2016). Five lactation persistency indices of animals (P21, P31, P32, P4 and P5) were calculated using ratio method. A total of six different animal models, ignoring or including maternal genetic or permanent environmental effects, were fitted for all persistency traits. The best model was chosen after testing the improvement of the log-likelihood values. The estimates of direct heritability were low in magnitude and ranged from 0.02 to 0.14 for the studied traits under the best fitted animal model. The permanent maternal environmental (c2) effects of different lactation persistency indices accounted for 2–9% of the total phenotypic variance in this study. Estimated genetic correlations of lactation persistency indices with all studied reproductive traits were low to moderate and negative (−0.11 to −0.68), except for calving interval. Phenotypic correlations of lactation persistency measures with studied reproductive traits were low (0.01 to 0.15). The low heritability estimates of all the persistency indices indicate some limited scope of genetic improvement of lactation persistency of animals through selection under the prevailing management conditions.

Remarkable increases in the production of dairy animals have negatively impacted their tolerance to heat stress (HS). The evaluation of the effect of HS on milk yield is based on the direct impact of HS on performance. However, in practical terms, HS also exerts its influence during gestation (indirect effect). The main purpose of this study was to identify and characterize the genotype by environment interaction (G × E) due to HS during the last 60 days of gestation (THI_g) and also the HS postpartum (THI_m) over first lactation milk production of Brazilian Holstein cattle. A total of 389 127 test day milk yield (TD) records from 1572 first lactation Holstein cows born in Brazil (daughters of 1248 dams and 70 sires) and the corresponding temperature–humidity index (THI) obtained between December 2007 and January 2013 were analyzed using different random regression models. Cows in the cold environment (THI_g = 64 to 73) during the last 60 days of gestation produced more milk than those cows in a hot environment (THI_g = 74 to 84), particularly during the first 150 days of lactation (DIM). The heritabilities (h2) of TD were similar throughout DIM for cows in THI_g hot (0.11 to 0.20) or (0.10 to 0.22), while the genetic correlations (rg) for TD between these two environments ranged from 0.11 to 0.52 along the first 250 DIM. The h2 estimates for TD across THI_m were similar for cows in THI_g hot (0.07 to 0.25) and THI_g cold (0.08 to 0.19). The rg estimates ranged from 0.17 to 0.42 along THI_m between TD of cows in cold and hot THI_g. The results were consistent in demonstrating the existence of an additional source of G × E for TD due to THI_g and THI_m. The present study is probably the first to provide evidence of this source of G × E; further research is needed because of its importance when the breeding objective is to select animals that are more tolerant to HS.

In the mink industry, feed costs are the largest variable expense and breeding for feed efficient animals is warranted. Implementation of selection for feed efficiency must consider the relationships between feed efficiency and the current selection traits BW and litter size. Often, feed intake (FI) is recorded on a cage with a male and a female and there is sexual dimorphism that needs to be accounted for. Study aims were to (1) model group recorded FI accounting for sexual dimorphism, (2) derive genetic residual feed intake (RFI) as a measure of feed efficiency, (3) examine the relationship between feed efficiency and BW in males (BWM) and females (BWF) and litter size at day 21 after whelping (LS21) in Danish brown mink and (4) investigate direct and correlated response to selection on each trait of interest. Feed intake records from 9574 cages, BW records on 16 782 males and 16 875 females and LS21 records on 6446 yearling females were used for analysis. Genetic parameters for FI, BWM, BWF and LS21 were obtained using a multivariate animal model, yielding sex-specific additive genetic variances for FI and BW to account for sexual dimorphism. The analysis was performed in a Bayesian setting using Gibbs sampling, and genetic RFI was obtained from the conditional distribution of FI given BW using genetic regression coefficients. Responses to single trait selection were defined as the posterior distribution of genetic superiority of the top 10% of animals after conditioning on the genetic trends. The heritabilities ranged from 0.13 for RFI in females and LS21 to 0.59 for BWF. Genetic correlations between BW in both sexes and LS21 and FI in both sexes were unfavorable, and single trait selection on BW in either sex showed increased FI in both sexes and reduced litter size. Due to the definition of RFI and high genetic correlation between BWM and BWF, selection on RFI did not significantly alter BW. In addition, selection on RFI in either sex did not affect LS21. Genetic correlation between sexes for FI and BW was high but significantly lower than unity. The high correlations across sex allowed for selection on standardized averages of animals’ breeding values (BVs) for RFI, FI and BW, which yielded selection responses approximately equal to the responses obtained using the sex-specific BVs. The results illustrate the possibility of selecting against RFI in mink with no negative effects on BW and litter size.

The objectives of this study were to analyse the differences in the genetic determination of functional longevity in five Spanish lines of rabbits and to check how different systematic factors might affect this genetic determination. Four of the lines were maternal (lines A, V, H and LP), these lines were established selecting base generation animals according to different criteria, but in the subsequent generations all of them were selected for litter size at weaning. The other is the paternal line R, this line was constituted by selecting animals with an outstanding daily growth rate. The trait analysed, length of productive life, was the time in days between the date of the first positive pregnancy test and the date of culling or death of a doe. Four models extended from the Cox proportional hazard model were used to analyse data of each line separately and jointly. The complete model (Model 1) included the fixed effect of year-season (YS) combination, positive palpation order (OPP), that is, reproductive cycle, physiological status of the doe (PS) at service and number of kits born alive (NBA) in each kindling as time-dependent factors. The inbreeding coefficient was fitted as a continuous covariate and the animal’s additive genetic effect was also fitted to the model (Model 1). The other models were identical to Model 1 but excluding OPP (Model 2) or PS (Model 3) or NBA (Model 4), which were explored to assess the consequence on additive variance estimates of not correcting for these animal-dependent factors. Estimated effective heritabilities of longevity were 0.07 ± 0.03, 0.03 ± 0.02, 0.14 ± 0.09, 0.05 ± 0.04, 0.02 ± 0.01 and 0.04 ± 0.01 for lines A, V, H, LP, R and for the merged data set, respectively. Removing the PS from the model led to an increase in the estimated additive genetic variance in all lines (0.17 ± 0.05, 0.05 ± 0.03, 0.29 ± 0.19, 0.29 ± 0.20, 0.07 ± 0.04 and 0.05 ± 0.02 for lines A, V, H, LP, R and the merged data set, respectively). The highest hazard of death and/or culling was observed during the first two parities and decreased as the order of parity progressed. Does non-pregnant-non-lactating had the highest risk of death or culling. The does that had zero kits born alive incurred the highest risk, and this risk decreased as the NBA increased. In conclusion, the consideration of longevity as selection criterion for the studied rabbit lines is not recommended.

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 (SWf) 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.

Young stock survival is a trait of crucial importance in cattle breeding as calf mortality leads to economic losses and represents an animal welfare issue. The aim of this study was to estimate genetic parameters and sire breeding values for young stock survival in beef x dairy crossbred calves. Two traits were analysed with a univariate animal model: young stock survival between 1 to 30 days and 31 to 200 days after birth. Breed combinations with Belgian Blue sires outperformed all other sire breeds. The lowest survival rates were found for breed combinations with Jersey dams or Blonde d’Aquitaine sires. The results showed low but significant heritabilities (0.045 to 0.075) for both survival traits. Differences in breeding values between sires ranged from −2.5% to 3.5% and from −5.4% to 4.7% survival from 1 to 30 days and 31 to 200 days, respectively. Based on these findings, we concluded that it is feasible to breed for improved young stock survival in beef x dairy crossbred calves. This will hopefully contribute to increasing the survival rate of the calves and reduce economic losses for the farmers.

Performance and feeding behaviour traits in growing pigs could be affected by social interaction effects when animals are raised in group. So, properly knowing the genetic correlations between direct and social interaction effects among performance and feeding behaviour traits could improve the accuracy of the genetic evaluations. Our aim was to explore the role of feeding behaviour traits (FBT) and indirect genetic effects (IGEs) in the genetic evaluations of growing pigs. Thus, genetic parameters were estimated for production traits (PT): average daily gain, average daily feed consumption, feed conversion ratio and backfat thickness; as well as for FBT: average daily feeding rate, average daily feeding frequency, average daily occupation time and average daily time between consecutive visits. Traits were recorded in 1144 Duroc pigs during the fattening period. Two bivariate models were fitted: classic animal model and an animal model fitting IGE. Estimations were done following Bayesian procedures. Heritability estimates obtained with classic animal model for all studied traits were medium-high. The additional heritable variation captured by IGE supposed that the ratios of total genetic variance to phenotypic variance (T2) were higher than the heritability estimates obtained with the classic model, except for occupation time trait, when a lower value (0.20 ± 0.19) was estimated. This is due to a high and negative correlation between IGE and direct genetic effects (DGEs) of this particular trait (−0.78 ± 0.27). Results from classic animal model do not evidence a clear role of FBT to improve the accuracy of breeding value predictions for PT; only average daily feeding rate seems to show a positive correlation (around 0.50 to 0.60) with average daily gain, average daily feed consumption and backfat thickness. However, when IGE model was fitted, the number of estimates of genetic correlations between FBT and PT showing a relevant magnitude increased, generally for the correlations between IGE of FBT and DGE of PT; or particularly for the correlations between IGE of average daily feeding frequency, and the IGE of all the PT, except average daily gain. Thus, in evaluations using the animal model with IGE fitted, the inclusion of FBT could aid the improvement of the accuracy of breeding value predictions for PT. This is a consequence of the improved genetic relationships between traits that can be fitted when considering such models.

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.

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 (QRG0.1), 0.5 (QRG0.5) or 0.9 (QRG0.9). When only part of the data was used to estimate quantile growth curves, all animals from QRG0.1 were correctly classified in their group. Animals in QRG0.1 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 QRG0.1 in the population. Overall, downward genetic trends were observed for all traits as a function of selection for reduced RFI. However, QRG0.1 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.

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.

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-IGEi). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGEi: 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-IGEi, 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-IGEi ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGEi. 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.

Genomic selection is arguably the most promising tool for improving genetic gain in domestic animals to emerge in the last few decades, but is an expensive process. The aim of this study was to evaluate the economic impact related to the implementation of genomic selection in a simulated dairy cattle population. The software QMSim was used to simulate genomic and phenotypic data. The simulated genome contained 30 chromosomes with 100 cm each, 1666 SNPs markers equally spread and 266 QTLs randomly designated for each chromosome. The numbers of markers and QTLs were designated according to information available from Animal QTL (http://www.animalgenome.org/QTLdb) and Bovine QTL (http://bovineqtl.tamu.edu/). The allelic frequency changes were assigned in a gamma distribution with alpha parameters equal to 0·4. Recurrent mutation rates of 1·0e−4 were assumed to apply to markers and QTLs. A historic population of 1000 individuals was generated and the total number of animals was reduced gradually along 850 generations until we obtained a number of 200 animals in the last generation, characterizing a bottleneck effect. Progenies were created along generations from random mating of the male and female gametes, assuming the same proportion of both genders. Than the population was extended for another 150 generations until we obtained 17 000 animals, with only 320 male individuals in the last generation. After this period a 25 year of selection was simulated taking into account a trait limited by sex with heritability of 0·30 (i.e. milk yield), one progeny/cow/year and variance equal to 1·0. Annually, 320 bulls were mated with 16 000 dams, assuming a replacement rate of 60 and 40% for males and females, respectively. Selection and discard criteria were based in four strategies to obtain the EBVs assuming as breeding objective to maximize milk yield. The progeny replaced the discarded animals creating an overlapping generation structure. The selection strategies were: RS is selection based on random values; PS is selection based on phenotypic values; Blup is selection based on EBVs estimated by BLUP; and GEBV is selection based on genomic estimated breeding values in one step, using high (GBlup) and low (GBlupi) density panels. Results indicated that the genetic evaluation using the aid of genomic information could provide better genetic gain rates in dairy cattle breeding programs as well as reduce the average inbreeding coefficient in the population. The economic viability indicators showed that only Blup and GBlup/GBlupi strategies, the ones that used milk control and genetic evaluation were economic viable, considering a discount rate of 6·32% per year.

Intramuscular fat (IMF) content and composition are relevant for the meat industry due to their effect on human health and meat organoleptic properties. A divergent selection experiment for IMF of Longissimus dorsi (LD) muscle was performed in rabbits during eight generations. The aim of this study is to estimate the correlated responses to selection for IMF on the fatty acid composition of LD. Response to selection for IMF was 0.34 g/100 g of LD, representing 2.4 phenotypic SD of the trait. High-IMF line showed 9.20% more monounsaturated fatty acids (MUFA) and 0.39%, 9.97% and 10.3% less n-3, n-6 and polyunsaturated fatty acids (PUFA), respectively, than low-IMF line. The main MUFA and PUFA individual fatty acids followed a similar pattern, except for C18:3n-3 that was greater in the high-IMF line. We did not observe differences between lines for the percentage of total saturated fatty acids, although high-IMF line showed greater C14:0 and C16:0 and lower C18:0 percentages than low-IMF line. Heritability estimates were generally high for all fatty acids percentages, ranging from 0.43 to 0.59 with a SD around 0.08, showing an important genetic component on these traits. Genetic correlations between IMF and LD fatty acid percentages were strong and positive for C14:0, C16:1, C18:1n-9, and MUFA, ranging from 0.88 to 0.97, and strong and negative for C18:0, C18:2n-6, C20:4n-6, n-6 and PUFA, ranging from −0.83 to −0.91. These correlations were accurately estimated, with SD ranging from 0.02 to 0.06. The genetic correlations between IMF and other fatty acids were estimated with lower accuracy. In general, phenotypic and genetic correlations were of the same order. Our experiment shows that selection for IMF strongly affects the fatty acid composition of meat, due the high heritabilities of fatty acids and their high genetic correlations with IMF.

Longer-lived cows tend to be more profitable and the stayability trait is a selection criterion correlated to longevity. An alternative to the traditional approach to evaluate stayability is its definition based on consecutive calvings, whose main advantage is the more accurate evaluation of young bulls. However, no study using this alternative approach has been conducted for Zebu breeds. Therefore, the objective of this study was to compare linear random regression models to fit stayability to consecutive calvings of Guzerá, Nelore and Tabapuã cows and to estimate genetic parameters for this trait in the respective breeds. Data up to the eighth calving were used. The models included the fixed effects of age at first calving and year-season of birth of the cow and the random effects of contemporary group, additive genetic, permanent environmental and residual. Random regressions were modeled by orthogonal Legendre polynomials of order 1 to 4 (2 to 5 coefficients) for contemporary group, additive genetic and permanent environmental effects. Using Deviance Information Criterion as the selection criterion, the model with 4 regression coefficients for each effect was the most adequate for the Nelore and Tabapuã breeds and the model with 5 coefficients is recommended for the Guzerá breed. For Guzerá, heritabilities ranged from 0.05 to 0.08, showing a quadratic trend with a peak between the fourth and sixth calving. For the Nelore and Tabapuã breeds, the estimates ranged from 0.03 to 0.07 and from 0.03 to 0.08, respectively, and increased with increasing calving number. The additive genetic correlations exhibited a similar trend among breeds and were higher for stayability between closer calvings. Even between more distant calvings (second v. eighth), stayability showed a moderate to high genetic correlation, which was 0.77, 0.57 and 0.79 for the Guzerá, Nelore and Tabapuã breeds, respectively. For Guzerá, when the models with 4 or 5 regression coefficients were compared, the rank correlations between predicted breeding values for the intercept were always higher than 0.99, indicating the possibility of practical application of the least parameterized model. In conclusion, the model with 4 random regression coefficients is recommended for the genetic evaluation of stayability to consecutive calvings in Zebu cattle.

Recent studies with Nile tilapia have shown divergent results regarding the possibility of selecting on morphometric measurements to promote indirect genetic gains in fillet yield (FY). The use of indirect selection for fillet traits is important as these traits are only measurable after harvesting. Random regression models are a powerful tool in association studies to identify the best time point to measure and select animals. Random regression models can also be applied in a multiple trait approach to analyze indirect response to selection, which would avoid the need to sacrifice candidate fish. Therefore, the aim of this study was to investigate the genetic relationships between several body measurements, weight and fillet traits throughout the growth period and to evaluate the possibility of indirect selection for fillet traits in Nile tilapia. Data were collected from 2042 fish and was divided into two subsets. The first subset was used to estimate genetic parameters, including the permanent environmental effect for BW and body measurements (8758 records for each body measurement, as each fish was individually weighed and measured a maximum of six times). The second subset (2042 records for each trait) was used to estimate genetic correlations and heritabilities, which enabled the calculation of correlated response efficiencies between body measurements and the fillet traits. Heritability estimates across ages ranged from 0.05 to 0.5 for height, 0.02 to 0.48 for corrected length (CL), 0.05 to 0.68 for width, 0.08 to 0.57 for fillet weight (FW) and 0.12 to 0.42 for FY. All genetic correlation estimates between body measurements and FW were positive and strong (0.64 to 0.98). The estimates of genetic correlation between body measurements and FY were positive (except for CL at some ages), but weak to moderate (−0.08 to 0.68). These estimates resulted in strong and favorable correlated response efficiencies for FW and positive, but moderate for FY. These results indicate the possibility of achieving indirect genetic gains for FW and by selecting for morphometric traits, but low efficiency for FY when compared with direct selection.

Objective of this study was to estimate genetic parameters of milk coagulation properties (MCPs) and individual laboratory cheese yield (ILCY) in a sample of 1018 Sarda breed ewes farmed in 47 flocks. Rennet coagulation time (RCT), curd-firming time (k20) and curd firmness (a30) were measured using Formagraph instrument, whereas ILCY were determined by a micromanufacturing protocol. About 10% of the milk samples did not coagulate within 30 min and 13% had zero value for k20. The average ILCY was 36%. (Co)variance components of considered traits were estimated by fitting both single- and multiple-trait animal models. Flock-test date explained from 13% to 28% of the phenotypic variance for MCPs and 26% for ILCY, respectively. The largest value of heritability was estimated for RCT (0.23±0.10), whereas it was about 0.15 for the other traits. Negative genetic correlations between RCT and a30 (−0.80±0.12), a30 and k20 (−0.91±0.09), and a30 and ILCY (−0.67±0.08) were observed. Interesting genetic correlations between MCPs and milk composition (rG>0.40) were estimated for pH, NaCl and casein. Results of the present study suggest to use only one out of three MCPs to measure milk renneting ability, due to high genetic correlations among them. Moreover, negative correlations between ILCY and MCPs suggest that great care should be taken when using these methods to estimate cheese yield from small milk samples.

The aim of this study was to estimate the genetic parameters for preweaning traits and their relationship with reproductive, productive and morphological traits in alpacas. The data were collected from 2001 to 2015 in the Pacomarca experimental farm. The data set contained data from 4330 females and 3788 males corresponding to 6396 and 1722 animals for Huacaya and Suri variants, respectively. The number of records for Huacaya and Suri variants were 5494 and 1461 for birth weight (BW), 5429 and 1431 for birth withers height (BH), 3320 and 896 for both weaning weight (WW) and average daily gain (DG) from birth to weaning, 3317 and 896 for weaning withers height (WH), and 5514 and 1474 for survival to weaning. The reproductive traits analyzed were age at first calving and calving interval. The fiber traits were fiber diameter (FD), standard deviation of FD (SD), comfort factor and coefficient of variation of FD and the morphological traits studied were density, crimp in Huacaya and lock structure in Suri, head, coverage and balance. Regarding preweaning traits, model of analysis included additive, maternal and residual random effects for all traits, with sex, coat color, number of calving, month–year and contemporary group as systematic effects, and age at weaning as linear covariate for WW and WH. The most relevant direct heritabilities for Huacaya and Suri were 0.50 and 0.34 for WW, 0.36 and 0.66 for WH, 0.45 and 0.20 for DG, respectively. Maternal heritabilities were 0.25 and 0.38 for BW, 0.18 and 0.32 for BH, 0.29 and 0.39 for WW, 0.19 and 0.26 for WH, 0.27 and 0.36 for DG, respectively. Direct genetic correlations within preweaning traits were high and favorable and lower between direct and maternal genetic effects. The genetic correlations of preweaning traits with fiber traits were moderate and unfavorable. With morphological traits they were high and positive for Suri but not for Huacaya and favorable for direct genetic effect but unfavorable for maternal genetic effect with reproductive traits. If the selection objective was meat production, the selection would have to be based on the direct genetic effect for WW but not on the maternal genetic effect that has been shown to have less relevance. Other weaning traits such as WH or DG would be indirectly selected.