Genetic parameters and relationships between growth traits and scrotal circumference measured at different ages in Nellore cattle

Records from 106,212 Nellore animals, born between 1998 and 2006, were used to estimate (co)variance components and genetic parameters for birth weight (BW), average weight gains from birth to weaning (GBW), average weight gains from weaning to after yearling (GWAY), weaning hip height (WHH), postweaning hip height (PHH) and scrotal circumferences at 9 (SC9), 12 (SC12) and 15 (SC15) months of age. (Co)variance components were estimated by an animal model using multi-trait analysis. Heritability estimates for BW, GBW, GWAY, WHH, PHH, SC9, SC12 and SC15 were 0.31 ± 0.01; 0.25 ± 0.02; 0.30 ± 0.04; 0.51 ± 0.04; 0.54 ± 0.04; 0.39 ± 0.01; 0.41 ± 0.01 and 0.44 ± 0.02, respectively. Genetic correlations between growth traits ranged from 0.09 ± 0.01 to 0.88 ± 0.01, thereby implying that, at any age, selection to increase average weight gains will also increase stature. Genetic correlations between BW and average weight gains with scrotal circumferences were all positive and moderate (0.15 ± 0.03 to 0.38 ± 0.01). On the other hand, positive and low genetic associations were estimated between hip height and scrotal circumference at different ages (0.09 ± 0.01 to 0.17 ± 0.02). The results of this study pointed out that selection to larger scrotal circumferences in males will promote changes in average weight gains. In order to obtain Nellore cattle with the stature and size suitable for the production system, both weight gain and hip height should be included in a selection index.     

Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 ± 0.00, 0.42 ± 0.02, 0.49 ± 0.01, 0.11 ± 0.01 and 0.19 ± 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.     

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.     

Genetic correlation between heifer pregnancy and scrotal circumference measured at 15 and 18 months of age in Nellore cattle

Data of pregnancy diagnosis from 24,945 Nellore heifers, raised under tropical conditions in Brazil and exposed to breeding at about 14 months of age, were analyzed simultaneously with 13,742 (analysis 1), 36,091 (analysis 2), 8,405 (analysis 3), and 8,405 (analysis 4) scrotal circumference (SC) records of contemporary young bulls in order to estimate heritability (h(2)) for yearling heifer pregnancy (HP) and for SC measured at around 15 (SC15) and 18 (SC18) months of age and to estimate genetic correlation between HP and SC15 (SC18). Heifer pregnancy was considered as a categorical trait, with the value 1 (success) assigned to heifers that were detected as pregnant by rectal palpation approximately 60 days after the end of a 90-day breeding season and the value 0 (failure) otherwise. In analyses 1 and 3, SC was measured at around 15 months of age and in analysis 2 and 4 it was measured at around 18 months of age. Only 8,848 animals from datasets 1 and 2 were common in both files, which means the same animals measured at different ages. Datasets used in analyses 3 and 4 included the same animals, measured at 15 and at 18 months of age, respectively. Heritability estimates for HP were similar in all analyses, with values ranging from 0.66 +/- 0.08 to 0.67 +/- 0.008. For SC15, the estimates were 0.57 +/- 0.05 in analysis 1 and 0.60 +/- 0.07 in analysis 3. For SC18, the estimates were 0.53 +/- 0.03 in analysis 2 and 0.64 +/- 0.06 in analysis 4. The estimates of genetic correlation between HP and SC15 were 0.15 +/- 0.10 in analysis 1 and 0.11 +/- 0.11 in analysis 3. For the correlation between HP and SC18, the values were 0.27 +/- 0.10 in analysis 2 and 0.16 +/- 0.11 in analysis 4. Based on standard errors and confidence intervals, the best heritability and genetic correlation estimates were obtained from analysis 2, which included more data and a better pedigree structure. Pearson correlation between HP and SC breeding values was similar to the genetic correlation estimates obtained from two-trait models, when all animals in the pedigree file were considered for its calculation. If only sires were considered for the calculation, Pearson correlation was higher but the pattern was the same as from two-trait analyses. The high heritability estimates obtained in the present study confirm that expected progeny difference (EPD) for HP can be used to select bulls for the production of precocious daughters and that the low genetic correlation between SC and HP indicates a greater efficacy of selection based on heifer pregnancy EPD than of selection based on scrotal circumference EPD. The results of the present study, although not conclusive, indicate that SC measured at around SC18 would have a higher genetic correlation with HP than would SC measured at around SC15.     

Genetic and phenotypic parameter estimates for scrotal circumference and semen traits in young beef bulls

Estimated in this study were heritabilities and genetic and phenotypic correlations involving scrotal circumference (SC), percent live sperm, sperm number, sperm concentration, sperm motility, and an overall measure of a bull's potential breeding efficiency. Potential breeding efficiency is a composite trait based on a consideration of sperm concentration, sperm motility, sperm morphology and scrotal circumference. Data used were from three sources. Records on 863 Angus, 753 Polled Hereford, and 302 Simmental bulls were made available through the Missouri Performance-Tested Bull Sale and records on 1169 Polled Hereford bulls came from the American Polled Hereford Association. Information from these first two data sets were used to estimate heritability of scrotal circumference. The third data set was provided by Nichols Farms of Bridgewater, Iowa, and included information from the records of 465 yearling Polled Hereford and 264 yearling Simmental bulls. This latter data set was used to estimate all of the above mentioned parameters. Each data set was kept separately for the purpose of statistical analysis. Parameters were estimated using components from paternal half-sib analysis of variance and covariance. Pooled estimates of heritability for SC, sperm concentration, sperm motility, percent live sperm, sperm number and potential breeding efficiency were 0.51 +/- 0.09, 0.20 +/- 0.13, 0.11 +/- 0.12, 0.00, 0.19 +/- 0.14 and 0.13 +/- 0.12, respectively. Phenotypic correlations involving the six traits were very consistent for the two breeds. Combined across breeds their values ranged from 0.47 for SC and percent live sperm to 0.96 for sperm concentration and potential breeding efficiency. Corresponding genetic correlations were generally positive and high and ranged from 0.65 for SC and sperm motility to 1.14 for sperm number and potential breeding efficiency.     

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

The objective of this study was to estimate genetic and phenotypic correlations of body weight at 6 weeks of age (BW6), as well as final carcass yield, and moisture, protein, fat and ash contents, using data from 3,422 F2 chickens originated from reciprocal cross between a broiler and a layer line. Variance components were estimated by the REML method, using animal models for evaluating random additive genetic and fixed contemporary group (sex, hatch and genetic group) effects. The heritability estimates (h(2)) for BW6, carcass yield and percentage of carcass moisture were 0.31 ± 0.07, 0.20 ± 0.05 and 0.33 ± 0.07, respectively. The h(2) for the percentages of protein, fat and ash on a dry matter basis were 0.48 ± 0.09, 0.55 ± 0.10 and 0.36 ± 0.08, respectively. BW6 had a positive genetic correlation with fat percentage in the carcass, but a negative one with protein and ash contents. Carcass yield, thus, appears to have only low genetic association with carcass composition traits. The genetic correlations observed between traits, measured on a dry matter basis, indicated that selection for carcass protein content may favor higher ash content and a lower percentage of carcass fat.     

(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.     

Heritability of scrotal circumference adjusted and unadjusted for body weight in Nellore bulls, using univariate and bivariate animal models

Mixed model methodology under univariate and bivariate animal models was used to estimate genetic parameters of scrotal circumference (SC) unadjusted (h2U) and adjusted (h2A) for body weight, from field data on 875 Nellore males sired by 80 bulls. The models included random effect of animal, the fixed effects of age of dam, year of birth, and month and year of measurement, and the covariate age of the animal. In addition, one of the models also included the covariate body weight. Using univariate models, SC estimates of h2U were 0.18, 0.65, 0.77 and 0.60, and of h2A they were 0.15, 0.60, 0.71 and 0.50, at 9, 12, 18 and 24 m.o. of age, respectively. Bivariate estimates of heritability ranged from 0.18 to 0.77 for h2U, and from 0.13 to 0.70 for h2A. The results suggest that it would be better to consider unadjusted SC rather than adjusted SC in selection programs. Bivariate body weight estimates of heritability ranged from 0.15 to 0.45. Genetic correlations between SC and body weight ranged from 0.58 to 0.71 when body weight was not included in the model, and from 0.33 to 0.64 when body weight was included. These results suggest that simultaneous selection for body weight and SC is possible in Nellore cattle.     

An analysis of the genetic relationship between udder health and udder conformation traits in South African Jersey cows

A multi-trait animal model was used to estimate genetic parameters among lactation somatic cell score (SCS) and udder-type traits in South African Jersey cattle, through restricted maximum likelihood (REML) procedures. Data comprised records on 18 321 Jersey cows in 470 herds, collected through the National Milk Recording Scheme from 1996 to 2002. Average SCS in the first three lactations (SCS1, SCS2 and SCS3) were considered as different traits and the udder-type traits were fore udder attachment (FUA), rear udder height (RUH), rear udder width (RUW), udder cleft (UC), udder depth (UD), fore teat placement (FTP), rear teat placement (RTP) and fore teat length (FTL). Heritability estimates for the respective lactation SCS were 0.07 ± 0.01, 0.11 ± 0.01 and 0.11 ± 0.02. Udder-type traits had heritability estimates ranging from 0.14 ± 0.01 for UD to 0.30 ± 0.02 for FTL. Genetic correlations between SCS and udder-type traits ranged from -0.003 ± 0.07 between FUA and SCS3 to -0.50 ± 0.07 between UD and SCS3. Slow genetic progress is expected when selection is applied independently on SCS and udder-type traits, due to the generally low heritabilities. Tightly attached shallow udders with narrowly placed rear teats are associated with low SCS in the Jersey population.     

Animal Board Invited Review: Meta-analysis of genetic parameters for resilience and efficiency traits in goats and sheep

Genetic selection focused purely on production traits has proven very successful in improving the productive performance of livestock. However, heightened environmental and infectious disease challenges have raised the need to also improve the resilience of animals to such external stressors, as well as their efficiency in utilising available resources. A better understanding of the relationship between efficiency and production and health traits is needed to properly account for it in breeding programmes and to produce animals that can maintain high production performance in a range of environmental conditions with minimal environmental footprint. The aim of this study was to perform a meta-analysis of genetic parameters for production, efficiency and health traits in sheep and goats. The dataset comprised 963 estimates of heritability and 572 genetic correlations collated from 162 published studies. A threelevel meta-analysis model was fitted. Pooled heritability estimates for milk production traits ranged between 0.27 ± 0.03 and 0.48 ± 0.13 in dairy goats and between 0.21 ± 0.06 and 0.33 ± 0.07 in dairy sheep. In meat sheep, the heritability of efficiency traits ranged from 0.09 ± 0.02 (prolificacy) up to 0.32 ± 0.14 (residual feed intake). For health traits, pooled heritability was 0.07 ± 0.01 (faecal egg count) and 0.21 ± 0.01 (somatic cell score) in dairy goats and 0.14 ± 0.04 (faecal egg count) and 0.13 ± 0.02 (somatic cell score) in dairy sheep. In meat sheep, the heritability of disease resistance and survival traits ranged between 0.07 ± 0.02 (mastitis) and 0.50 ± 0.10 (breech strike). Pooled estimates of genetic correlations between resilience and efficiency traits in dairy goats were not significantly different from zero with the exception of somatic cell score and fat content (?0.19 ± 0.01). In dairy sheep, only the unfavourable genetic correlation between somatic cell score and protein content (0.12 ± 0.03) was statistically significant. In meat sheep only, the correlations between growth and faecal egg count (?0.28 ± 0.11) as well as between growth and dagginess (?0.33 ± 0.13) were statistically significant and favourable. Results of this meta-analysis provide evidence of genetic antagonism between production and health in dairy sheep and goats. This was not observed in meat sheep where most of the pooled estimates had high standard errors and were non-significant. Based on the obtained results, it seems feasible to simultaneously improve efficiency and health in addition to production by including the different types of traits in the breeding goal. However, a better understanding of potential trade-offs between these traits would be beneficial. Particularly, more studies focused on reproduction and resilience traits linked to the animal’s multi-trait response to challenges are required.     

Responses of prolactin and hair growth to selection for age at puberty in Angus cattle

A trial was carried out over a 7-year period (1999 to 2005 calf crops) to compare indicators of seasonality in Angus cattle, which were part of a long-term genetic selection experiment. Divergent selection was applied for early ('AGE-') or late ('AGE+') age at puberty (AP) in heifers, and selection lines differed over the 7-year period by 62 days (15% of the mean). The primary measures of seasonality studied in 629 heifer progeny (59 sire groups) were serum concentration of prolactin (PRL), and winter and summer hair growth. Serial samples were obtained for PRL from 11 to 18 months of age, and data were analysed with adjustment for cortisol concentration. Using restricted maximum likelihood procedures with an animal model, heritability estimates were: AP, 0.26 ± 0.03; log(e)PRL concentration, 0.23 ± 0.07; log(e)cortisol concentration, 0.22 ± 0.07; hair weight, 0.21 ± 0.04; and hair length, 0.09 ± 0.05. Corresponding repeatability estimates for the last four traits were 0.49 ± 0.03, 0.38 ± 0.03, 0.21 ± 0.04, and 0.64 ± 0.02, respectively. The genetic correlation between AP and log(e)PRL concentration was estimated at -0.29 ± 0.13 (P < 0.05). PRL concentration in the AGE- line after passing through puberty was 11 ± 5% lower than in the AGE+ line (P < 0.05). Line effects were not significant for hair weight or hair length. It was concluded that divergent selection for AP changed PRL concentration, which may partly reflect sensitivity to changing day length.     

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

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

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.     

Estimation of genetic parameters for BW and body measurements in Brahman cattle

Body weight and body measurements are commonly used to represent growth and measured at several growth stages in beef cattle. Those economically important traits should be genetically improved. To achieve breeding programs, genetic parameters are prerequisite, as they are needed for designing and predicting outcomes of breeding programs, as well as estimating of breeding values. (Co)variance components were estimated for BW and body measurements on Brahman cattle born between 1990 and 2016 from 17 research herds across Thailand. The traits measured were BW, heart girth (GR), hip height (HH) and body length (BL) and were measured at birth, 200 days, 400 days and 600 days of age. The number of records varied between traits from 18 890 for birth BW to 876 for GR at 600 days. Estimation of variance components was performed using restricted maximum likelihood using univariate and multivariate animal models. Pre-weaning traits were influenced by genetic and/or permanent environmental effects of the dam, except for BL. Heritability estimates from birth to 600 days of age ranged from 0.28±0.01 to 0.50±0.06 for BW, 0.27±0.01 to 0.43±0.09 for GR, 0.28±0.01 to 0.58±0.08 for HH and 0.34±0.01 to 0.51±0.08 for BL using univariate analysis. Heritability estimates for the traits studied increased with age. A similar trend was observed for the phenotypic and genetic correlations between subsequent BW and body measurements. A positive correlation was observed between different traits measured at a similar age, ranging from 0.22±0.01 to 0.72±0.01 for the phenotypic correlation and 0.25±0.04 to 0.97±0.11 for the genetic correlation. Also, a positive correlation was observed for similar traits across different age classes ranging from 0.07±0.03 to 0.76±0.02 for the phenotypic correlation and 0.24±0.11 to 0.92±0.05 for the genetic correlation. Therefore, all correlations between body measurements at the same age and across age classes were positive. The results show the potential improvement of growth traits in Brahman cattle, and those traits can be improved simultaneously under the same breeding program.     

Genetic relationships among traits related to reproduction and growth of Nelore females

The objective of the study presented here was to analyze the genetic relationships among heifer pregnancy (HP), age at first calving (AFC), stayability (STAY), average annual productivity of the cow, in kilograms of weaned calf per cow per year (PRODAM), postweaning weight gain (PWG), and hip height (HH) of Nelore females from 12 Brazilian herds. (Co)variance components were obtained by six-trait animal model using Gibbs sampling. The posterior mean of the heritability estimates were 0.37, 0.18, 0.19, 0.16, 0.21, and 0.37 for HP, AFC, STAY, PRODAM, PWG, and HH, respectively. In general, the genetic correlations were strong between traits related to reproduction, for example, −0.85 between HP and AFC, and 0.94 between STAY and PRODAM. Weak genetic correlations were obtained between reproductive and growth traits (absolute values ranging from 0.02 to 0.30). Although weak, the genetic correlations between PWG and reproductive traits were favorable, whereas the genetic correlations between HH and reproductive traits were close to zero and slightly unfavorable for HP, AFC, and STAY. An increase of HH is therefore expected to have little or no negative effect on the reproductive performance of females. The posterior mean of genetic correlation between PWG and HH was moderate (0.50). On the basis of the heritability, genetic correlation estimates, and time to obtain data, HP and PRODAM seems to show the best potential as selection criteria to improve the productive and reproductive performance of Nelore females. In principle, it is possible to select for increased PWG without compromising the reproduction of Nelore females. However, selection for PWG may result in an increase of female HH as a correlated response, a fact that could increase management costs in advanced generations of selection. In the light of the results, all traits studied here can be used as selection criteria and there is no strong evidence of genetic antagonism among traits related to reproduction and growth of Nelore females.     

Genetic parameter estimates for pre-weaning weight traits in Dorper sheep

Genetic parameters were estimated for birth-, 42-day, and 100-day (weaning) weight in the Dorper flock of the Glen Agricultural Institute in South Africa. Direct heritability estimates of 0.11, 0.28 and 0.20 and maternal heritability estimates of 0.10, 0.10 and 0.10 were obtained for body weights at birth, 42 and 100 days, respectively. The corresponding genetic correlation estimates between direct and maternal effects were 0.35, −0.63 and −0.58, respectively. Both direct and maternal genetic correlation estimates among the traits were of moderate to high magnitude and positive. It is concluded that the traits can be improved by selection with no serious antagonisms among traits studied.     

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.     

Longitudinal analysis of residual feed intake and BW in mink using random regression with heterogeneous residual variance

The aim of this study was to determine the genetic background of longitudinal residual feed intake (RFI) and BW gain in farmed mink using random regression methods considering heterogeneous residual variances. The individual BW was measured every 3 weeks from 63 to 210 days of age for 2139 male+female pairs of juvenile mink during the growing-furring period. Cumulative feed intake was calculated six times with 3-week intervals based on daily feed consumption between weighing’s from 105 to 210 days of age. Genetic parameters for RFI and BW gain in males and females were obtained using univariate random regression with Legendre polynomials containing an animal genetic effect and permanent environmental effect of litter along with heterogeneous residual variances. Heritability estimates for RFI increased with age from 0.18 (0.03, posterior standard deviation (PSD)) at 105 days of age to 0.49 (0.03, PSD) and 0.46 (0.03, PSD) at 210 days of age in male and female mink, respectively. The heritability estimates for BW gain increased with age and had moderate to high range for males (0.33 (0.02, PSD) to 0.84 (0.02, PSD)) and females (0.35 (0.03, PSD) to 0.85 (0.02, PSD)). RFI estimates during the growing period (105 to 126 days of age) showed high positive genetic correlations with the pelting RFI (210 days of age) in male (0.86 to 0.97) and female (0.92 to 0.98). However, phenotypic correlations were lower from 0.47 to 0.76 in males and 0.61 to 0.75 in females. Furthermore, BW records in the growing period (63 to 126 days of age) had moderate (male: 0.39, female: 0.53) to high (male: 0.87, female: 0.94) genetic correlations with pelting BW (210 days of age). The result of current study showed that RFI and BW in mink are highly heritable, especially at the late furring period, suggesting potential for large genetic gains for these traits. The genetic correlations suggested that substantial genetic gain can be obtained by only considering the RFI estimate and BW at pelting, however, lower genetic correlations than unity indicate that extra genetic gain can be obtained by including estimates of these traits during the growing period. This study suggests random regression methods are suitable for analysing feed efficiency and BW gain; and genetic selection for RFI in mink is promising.     

Two-trait random regression model to estimate the genetic association of scrotal circumference with female reproductive performance in Nelore cattle

In an attempt to determine when scrotal circumference (SC) could be a reasonable indicator of female reproductive performance, a series of two-trait random regression model (regression for SC on age at measurement) using Gibbs sampling was applied to field data of Nelore cattle raised in a tropical environment. The female traits evaluated were age at first calving (AFC), first calving interval (FCI), heifer pregnancy (HP), and stayability (STAY). The posterior means of heritability of female traits ranged from 0.15 for AFC to 0.46 for HP and were about 0.50 for SC. The posterior means of genetic correlations between SC and AFC, FCI, HP, STAY were up to −0.70, −0.25, 0.48, and 0.29, respectively. Genetically, SC could be a reasonable indicator of female puberty (e.g., HP) as long as it is measured at a young age (400–440 days). However, for female reproductive traits measured at an older age (e.g., STAY), SC is merely a modest or even poor indicator. The use of sire expected progeny differences for female reproductive traits will be more effective than the use of expected progeny differences for SC to improve the reproductive performance of female cattle.