Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

A total of 19 376 test day (TD) milk yield records from the first three lactations of 1618 cows daughters of 162 sires were used to estimate genetic and phenotypic parameters and determine the relationship between daily milk yield and lactation milk yield in the Sahiwal cattle in Kenya. Variance components were estimated using animal models based on a derivative free restricted maximum likelihood procedure. Variance components were estimated using various univariate and multi-trait fixed regression test day models (TDM) that defined contemporary groups either based on the year-season of calving (YSCV) or on the year-season of TD milk sampling (YSTD). Variance components were influenced by CG which resulted in differences in heritability and repeatability estimates between TDM. Models considering YSTD resulted in higher additive genetic variances and lower residual variances compared with models in which YSCV was considered. Heritability estimates for daily yield ranged from 0.28 to 0.46, 0.38 to 0.52 and 0.33 to 0.52 in the first, second and third lactation, respectively. In the first and second lactation, the heritability estimates were highest between TD 2 and TD 4. Genetic correlations among daily milk yields ranged from 0.41 to 0.93, 0.50 to 0.83 and 0.43 to 86 in the first, second and third lactation, respectively. The phenotypic correlations were correspondingly lower. Genetic correlations were different from unit when fitting multi-trait TDM. Therefore, a multiple trait model would be more ideal in determining the genetic merit of dairy sires and bulls based on daily yield records. Genetic and phenotypic correlations between daily yield and lactation yields were high and positive. Genetic correlations ranged from 0.84 to 0.99, 0.94 to 1.00 and 0.94 to 0.97 in the first, second and third lactations, respectively. The corresponding phenotypic correlation estimates ranged from 0.50 to 0.85, 0.50 to 0.83 and 0.53 to 0.87. The high genetic correlation between daily yield and lactation yield imply that both traits are influenced by similar genes. Therefore daily yields records could be used in genetic evaluation in the Sahiwal cattle breeding programme.     

Genetic relationship between milk urea nitrogen and reproductive performance in Holstein dairy cows

The objective of this study was to describe the genetic and phenotypic relationship between milk urea nitrogen (MUN) and reproductive traits in Iranian Holstein dairy cows. Test-day MUN data obtained from 57 301 dairy cows on 20 large dairy herds in Iran between January 2005 and June 2009. Genetic parameters for MUN and reproductive traits were estimated with a five-trait model using ASREML program. Random regression test-day models were used to estimate heritabilities separately for MUN from first, second and third lactations. Regression curves were modeled using Legendre polynomials of order 3. Herd-year-season along with age at calving was included as fixed effects in all models for reproductive traits. Heritabilities for MUN and reproductive traits were estimated separately for first lactation, second lactation and third lactation. The estimated heritabilities for MUN varied from 0.18 to 0.22. The heritability estimate was low for reproductive traits, which ranged from 0.02 to 0.06 for different traits and across parities. Except for days open, phenotypic and genetic correlations of MUN with reproductive performance traits were close to zero. Genetic correlations between MUN and days open were 0.23, 0.35 and 0.45 in first, second and third lactation, respectively. However, the phenotypic correlation between MUN at different parities was moderate (0.28 to 0.35), but the genetic correlation between MUN at different parities was high and ranged from 0.84 to 0.97. This study shows a limited application of MUN for use in selection programs to improve reproductive performance.     

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.     

Sources of sire-specific genetic variance for birth and weaning weight in Bruna dels Pirineus beef calves

This research investigated two sources of sire-specific genetic effects on the birth weight (BWT) and weaning weight (WWT) of Bruna dels Pirineus beef calves. More specifically, we focused on the influence of genes located in the non-autosomal region of the Y chromosome and the contribution of paternal imprinting. Our analyses were performed on 8130 BWT and 1245 WWT records from 12 and 2 purebred herds, respectively, they being collected between years 1986 and 2010. All animals included in the study were registered in the Yield Recording Scheme of the Bruna dels Pirineus breed. Both BWT and WWT were analyzed using a univariate linear animal model, and the relevance of paternal imprinting and Y chromosome-linked effects were checked by the deviance information criterion (DIC). In addition to sire-specific and direct genetic effects, our model accounted for random permanent effects (dam and herd-year-season) and three systematic sources of variation, that is, sex of the calf (male or female), age of the dam at calving (six levels) and birth type (single or twin). Both weight traits evidenced remarkable effects from the Y chromosome, whereas paternal imprinting was only revealed in WWT. Note that differences in DIC between the preferred model and the remaining ones exceed 39 000 and 2 800 000 DIC units for BWT and WWT, respectively. It is important to highlight that Y chromosome accounted for ∼2% and ∼6% of the total phenotypic variance for BWT and WWT, respectively, and paternal imprinting accounted for ∼13% of the phenotypic variance for WWT. These results revealed two relevant sources of sire-specific genetic variability with potential contributions to the current breeding scheme of the Bruna dels Pirineus beef cattle breed; moreover, these sire-specific effects could be included in other beef cattle breeding programs or, at least, they must be considered and appropriately analyzed.     

Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording,and their relationships with milk yield and quality traits

The aim of this study was to estimate (co)variance components for milk coagulation properties (MCP) predicted by mid-infrared spectroscopy (MIRS) during routine milk recording, and to assess their relationships with yield and quality traits. A total of 63 470 milk samples from Holstein-Friesian cows were analyzed for MCP, pH and quality characteristics using MIRS. Casein to protein and protein to fat ratios were calculated from information obtained by MIRS. Records were collected across 1 year on 16 089 cows in 345 herds. The model used for genetic analysis included fixed effects of parity and stage of lactation, and random effects of herd-test-day, cow permanent environmental, animal additive genetic and residual. (Co)variance components were assessed in a Bayesian framework using the Gibbs Sampler. Estimates of heritabilities were consistent with those reported in the literature, being moderate for MCP (0.210 and 0.238 for rennet coagulation time (RCT) and curd firmness (a₃₀), respectively), milk contents (0.213 to 0.333) and pH (0.262), and low for somatic cell score (0.093) and yield traits (0.098 to 0.130). Repeatabilities were 0.391 and 0.434 for RCT and a₃₀, respectively, and genetic correlations were generally low, with estimates greater than 0.30 (in absolute value) only for a₃₀ with fat, protein and casein contents. Overall, results suggest that genetic evaluation for MCP predicted by MIRS is feasible at population level, and several repeated measures per cow during a lactation are required to estimate reliable breeding values for coagulation traits.     

Genetic correlations between yield traits or days open measured in cows and semen production traits measured in bulls

We used a bivariate animal model to investigate the genetic correlations between yield traits or days open (DO) as characters measured in cows and semen production traits as characters measured in bulls. Lactation records of 305-day milk, fat, and protein yields, and DO, from 386 809 first-lactation Holstein cows in Hokkaido, Japan, that calved between 2008 and 2014 were used. Semen production records were collected between 2005 and 2014 and included volume per ejaculate (VOL), sperm concentration (CON), number of sperm per ejaculate (NUM), progressive motility index of sperm (MOT), and MOT after freeze-thawing (A-MOT). Number of sperm per ejaculate was log-transformed into a NUM score (NUMS). A total of 30 373 semen production records from 1196 bulls were obtained. The pedigree file used for analysing the records was involving 885 345 animals. Heritability was estimated for VOL (0.42), CON (0.12), NUMS (0.37), MOT (0.08), and A-MOT (0.11). Weak and negative genetic correlations were recorded between yield traits measured in cows and VOL, CON or NUMS measured in bulls. Moderate and negative genetic correlations were obtained between DO and MOT (–0.42) or A-MOT (–0.43). Selection focused on MOT or A-MOT measured in bulls may therefore improve DO measured in cows.     

Genetic (co)variation in skin pigmentation patterns and growth in rainbow trout

From a physiological-behavioral perspective, it has been shown that fish with a higher density of black eumelanin spots are more dominant, less sensitive to stress, have higher feed intake, better feed efficiency and therefore are larger in size. Thus, we hypothesized that genetic (co)variation between skin pigmentation patterns and growth exists and it is advantageous in rainbow trout. The objective of this study was to determine the genetic relationships between skin pigmentation patterns and BW in a breeding population of rainbow trout. We performed a genetic analysis of pigmentation traits including dorsal color (DC), lateral band (LB) intensity, amount of spotting above (SA) and below (SB) the lateral line, and BW at harvest (HW). Variance components were estimated using a multi-trait linear animal model fitted by restricted maximum likelihood. Estimated heritabilities were 0.08±0.02, 0.17±0.03, 0.44±0.04, 0.17±0.04 and 0.23±0.04 for DC, LB, SA, SB and HW, respectively. Genetic correlations between HW and skin color traits were 0.42±0.13, 0.32±0.14 and 0.25±0.11 for LB, SA and SB, respectively. These results indicate positive, but low to moderate genetic relationships between the amount of spotting and BW in rainbow trout. Thus, higher levels of spotting are genetically associated with better growth performance in this population.     

Genetic parameters for first lactation test-day milk flow in Holstein cows

Genetic parameters for test-day milk flow (TDMF) of 2175 first lactations of Holstein cows were estimated using multiple-trait and repeatability models. The models included the direct additive genetic effect as a random effect and contemporary group (defined as the year and month of test) and age of cow at calving (linear and quadratic effect) as fixed effects. For the repeatability model, in addition to the effects cited, the permanent environmental effect of the animal was also included as a random effect. Variance components were estimated using the restricted maximum likelihood method in single- and multiple-trait and repeatability analyses. The heritability estimates for TDMF ranged from 0.23 (TDMF 6) to 0.32 (TDMF 2 and TDMF 4) in single-trait analysis and from 0.28 (TDMF 7 and TDMF 10) to 0.37 (TDMF 4) in multiple-trait analysis. In general, higher heritabilities were observed at the beginning of lactation until the fourth month. Heritability estimated with the repeatability model was 0.27 and the coefficient of repeatability for first lactation TDMF was 0.66. The genetic correlations were positive and ranged from 0.72 (TDMF 1 and 10) to 0.97 (TDMF 4 and 5). The results indicate that milk flow should respond satisfactorily to selection, promoting rapid genetic gains because the estimated heritabilities were moderate to high. Higher genetic gains might be obtained if selection was performed in the TDMF 4. Both the repeatability model and the multiple-trait model are adequate for the genetic evaluation of animals in terms of milk flow, but the latter provides more accurate estimates of breeding values.     

Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle

The implementation of genetic groups in BLUP evaluations accounts for different expectations of breeding values in base animals. Notwithstanding, many feasible structures of genetic groups exist and there are no analytical tools described to compare them easily. In this sense, the recent development of a simple and stable procedure to calculate the Bayes factor between nested competing models allowed us to develop a new approach of that method focused on compared models with different structures of random genetic groups. The procedure is based on a reparameterization of the model in terms of intraclass correlation of genetic groups. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null intraclass correlation. It compares two nested models, a model with a given structure of genetic groups against a model without genetic groups. The calculation of the Bayes factor between different structures of genetic groups can be quickly and easily obtained from the Bayes factor between the nested models. We applied this approach to a weaning weight data set of the Bruna dels Pirineus beef cattle, comparing several structures of genetic groups, and the final results showed that the preferable structure was an only group for unknown dams and different groups for unknown sires for each year of calving.     

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

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

Genetic variation in milk urea nitrogen concentration of dairy cattle and its implications for reducing urinary nitrogen excretion

Nitrogen (N) leached into groundwater from urine patches of cattle grazing in situ is an environmental problem in pasture-based dairy industries. One potential mitigation is to breed cattle for lower urinary nitrogen (UN) excretion. Urinary nitrogen is difficult to measure, while milk urea nitrogen concentration (MUN) is relatively easy to measure. For animals fed diets of differing N content in confinement, MUN is moderately heritable and is positively related to UN. However, there is little information on the heritability of MUN, and its relationship with other traits such as milk yield and composition, for animals grazing fresh pasture. Milk urea nitrogen concentration data together with milk yield, fat, protein and lactose composition and somatic cell count was collected from 133 624 Holstein-Friesian (HF), Jersey (J) and HF×J (XBd) cows fed predominantly pasture over three full lactations and one part lactation. Mean MUN was 14.0; and 14.4, 13.2 and 13.9 mg/dl for HF, J and XBd cows, respectively. Estimates of heritability of MUN were 0.22 using a repeatability model that fitted year-of-lactation by month-of-lactation by cow-age with days-in-milk within month-of-lactation and cow-age, and 0.28 using a test-day model analysis with Gibbs sampling methods. Sire breeding values (BVs) ranged from −2.8 to +3.2 indicating that MUN could be changed by selection. The genetic correlation between MUN and percent true protein in milk was −0.22; −0.29 for J cows and −0.16 for HF cows. Should the relationship between MUN and UN observed in dietary manipulation studies hold similarly when MUN is manipulated by genetic selection, UN excretion could be reduced by 6.6 kg/cow per year in one generation of selection using sires with low MUN BVs. Although J cows had lower MUN than HF, total herd UN excretion may be similar for the same fixed feed supply because more J cows are required to utilise the available feed. The close relationship between blood plasma urea N concentration and MUN may enable early selection of bulls to breed progeny that excrete less UN.     

Genetic (co)variances between milk mineral concentration and chemical composition in lactating Holstein-Friesian dairy cows

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 test-day records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31±0.05 (5 DIM) to 0.67±0.04 (181 DIM) for Ca, from 0.18±0.03 (60 DIM) to 0.24±0.05 (305 DIM) for K, from 0.08±0.03 (15 DIM) to 0.37±0.03 (223 DIM) for Mg, from 0.16±0.03 (30 DIM) to 0.37±0.04 (305 DIM) for Na and from 0.21±0.04 (12 DIM) to 0.57±0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38±0.21 (5 DIM) to 0.79±0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.     

Risk factors and milk yield losses associated with lameness in Holstein-Friesian dairy cattle

Weekly locomotion scores on a scale of 1 to 5 were used to investigate the relationship between cattle lameness, management systems and the impact of lameness on milk production. The data were 14026 locomotion scores from 248 Holstein-Friesian cows. Cows were managed in two groups, XE (high-concentrate feed and housed indoors all year) and XM (low-concentrate feed and outdoors in summer). Analysis was performed using residual maximum likelihood. Results indicated that the most significant variables affecting locomotion were time of year when the animal was locomotion scored and management group. Cows scored during February and August had increased locomotion problems. Cows in the more intensively managed group had significantly poorer locomotion compared with those in the more extensive group. Older animals were more susceptible to lameness than heifers. Body weight, body condition score and days in milk (DIM) also accounted for significant variation in locomotion score. Poor locomotion was associated with a significant reduction in the milk yield of later lactation cows. There was a significant difference in the shape of the lactation curve depending on whether or not the cow was lame during lactation. Average persistency was greater for the group of cows never lame throughout lactation compared with those lame before 60 DIM.     

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 parameters for medullated fiber and its relationship with other productive traits in alpacas

The alpaca fiber diameter (FD) varies from 18 to 36 μm, being the finer fiber categories highly appreciated. However, the alpaca fiber presents some limitations in the textile industry due to the high incidence of fiber medullation and diameter variability, both reduces the comfort feeling of the garments. Decreasing or even removing medullation could be a possible selection objective in alpaca breeding programs for increasing economic value of the alpaca fiber. Therefore, the present work aimed to estimate genetic parameters regarding medullation traits, as well as the genetic correlations with other economical important traits, to be able to select the appropriate criteria to reduce or remove medullation on alpaca fiber and help to reduce the prickle factor in the garments. The data was collected from 2000 to 2017 and belonged to the Pacomarca experimental farm. There were 3698 medullation records corresponding to 1869 Huacaya and 414 Suri genetic types. The fiber samples were taken from the mid side, and were analyzed in an OFDA 100® device. The traits analyzed were percentage of medullation (PM), medullated fiber diameter (MFD), FD, standard deviation of FD, greasy fleece weight as fiber traits; density, crimp in Huacaya and lock structure in Suri, head conformation, leg coverage as morphological traits; weaning weight and age at first calving as secondary and functional traits. Genetic parameters were estimated via a multitrait restricted maximum likelihood. The heritabilities for PM and MFD were 0.225 and 0.237 in Huacaya genetic type and 0.664 and 0.237 in Suri genetic type, respectively; heritabilities for other traits were moderate for productive and morphological traits, and low to moderate for secondary and functional traits. The genetic correlations PM–FD and MFD–FD were high and favorable in both genetic types, between 0.531 and 0.975; the genetic correlation PM–MFD was 0.121 in Huacaya and 0.427 in Suri. The rest of genetic correlations with other traits were in general moderate and favorable. The repeatabilities were 0.556 and 0.668 for PM, and 0.322 and 0.293 for MFD in Huacaya and Suri genetic types, respectively. As a conclusion, PM was identified to be a good selection criterion, probably combined in an index with FD to reduce prickling factor.     

Effect of lactation length adjustment procedures on genetic parameter estimates for buffalo milk yield

The objectives of this study were to estimate the genetic parameters for milk yield unadjusted and adjusted for days in milk and, subsequently, to assess the influence of adjusting for days in milk on sire rank. Complete lactations from 90 or 150 days of lactation to 270 or 350 days in milk were considered in these analyses. Milk yield was adjusted for days in milk by multiplicative correction factors, or by including lactation length as a covariable in the model. Milk yields adjusted by different procedures were considered as different traits. Heritability estimates varied from 0.17 to 0.28. Genetic correlation estimates between milk yields unadjusted and adjusted for days in milk were greater than 0.82. Adjusting for days in milk affected the parameter estimates. Multiplicative correction factors produced the highest heritability estimates. More reliable breeding value estimates can be expected by including short length lactation records in the analyses and adjusting the milk yields for days in milk, regardless of the method used for the adjustment. High selection intensity coupled to the inclusion of short length lactations and adjustment with multiplicative factors can change the sire rank..     

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

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