Estimates Of Environmental Correlations Research Articles

The estimation of (co)variance components growth, reproduction, carcass, FECS and FECN traits in Lleyn sheep

Genetic parameters for weaning live weight and ultrasound scanning measurements were estimated from performance recorded UK Lleyn sheep. The data for the study were collected from conventional hill and low land farming systems. The data were from 48,277 lambs. Genetic parameters were estimated using uni- and bivariate animal models for weight at birth (BWT), live weight at 8 weeks (8WK), ultrasound scanning at 21 weeks of age (SWT) and weight at tupping (MW), ultrasound scanned muscle (MD) and fat (FD) depth measured at 21 weeks of age, litter size born (LSB), litter size reared (LSR), faecal egg count for strongyle (FECS) and nematodes (FECN). Maternal genetic effects were fitted for BWT, and 8WK. Direct heritability estimates were 0.14±0.01 for BWT, 0.35±0.02 for 8WK, 0.46±0.01 for SWT, 0.31±0.01 for MD, 0.38±0.01 for FD, 0.38±0.01 for MW, 0.22±0.09 for FECS and 0.16±0.10 for FECN. Maternal heritability estimates were 0.14±0.01 for BWT and 0.11±0.01 for 8WK. Direct genetic correlations among studied traits ranged from −0.05 (MW–FD) to 0.90 (SWT–8WK). Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Our results indicate that the genetic parameters generated in this study could be used in selection index calculations to asses the benefits of including lamb carcass traits in future selection programmes for Lleyn sheep. Also, this study provides valuable information in terms of genetic parameters for growth and carcass traits which can be used for genetic evaluation and in designing selection programmes for the Lleyn breed.

Genetic evaluation of European quails by random regression models

The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (co)variance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6) to determine which model had the best fit to describe the (co)variance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT), the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day) to 0.16 (42 days). Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

Estimation of (co)variance components and genetic parameters for growth and wool traits of Chinese superfine merino sheep with the use of a multi-trait animal model

The aim of the current study was to estimate genetic parameters for birth weight (BW), weaning weight (WW), weaning staple length (WSL), yearling liveweight (YLW), and greasy fleece weight (YGFW), staple length (YSL), mean fiber diameter (YFD), fiber diameter standard deviation (YFDSD) and fiber diameter variation (YFDCV) at first shearing, which are essential to design a selection breeding program for Chinese superfine merino sheep. Data was collected on progeny from eight birth years (2001–2008) in the Chinese superfine merino breeding flock maintained at Xinjiang Gongnaisi Fine Wool Sheep Breeding Farm, Xinjiang, China. (Co)Variance components and genetic parameters were estimated by average information restricted maximum likelihood (AIREML) with a multi-trait animal model, and primarily 6 single-trait models for each trait were used to determine the most appropriate model for multi-trait analyses with Akaike's Information Criterion (AIC). Estimates of direct heritability were 0.15 for BW, 0.27 for WSL, 0.16 for WW, 0.23 for YLW, 0.32 for YSL, 0.17 for YGFW, 0.22 for YFD, 0.02 for YFDSD and 0.09 for YFDCV. Maternal heritability estimates for BW and YGFW were 0.15 and 0.05, respectively. Direct genetic correlations among studied traits ranged from − 0.85 (YGFW–YFDCV) to 0.87 (WSL–YSL). Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low to moderate direct heritability estimates for growth at different age, fiber diameter, fleece weight and staple length imply that selection for these traits results in lower to moderate genetic gain. Our results herein lay a practical foundation for performing an optimal breeding program in Chinese superfine merino.

Genetic analysis of ewe productivity traits in Moghani sheep

Genetic and environmental (co)variance components for productivity traits in Moghani sheep were estimated using data from 1344 ewes. The data were collected in the Jafarabad breeding station, north-east of Iran, during a 13-year period (1995–2008). The studied traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB) and total litter weight at weaning (TLWW). A model including direct additive genetic effects as well as permanent environmental effects related to repeated records of ewe was the most appropriate model for all the studied traits. Genetic parameters were estimated applying restricted maximum likelihood (REML) procedure. Direct heritability estimate for LSB, LSW, LMWLB, LMWLW, TLWB and TLWW were 0.11, 0.02, 0.15, 0.07, 0.07 and 0.06, respectively. Corresponding values for repeatability estimates were 0.16, 0.19, 0.18, 0.11, 0.13 and 0.09. Genetic correlations between the studied traits ranged from −0.99 for LSB–LMWLB and LSW–LMWLB to 0.99 for LSB–TLWB. Phenotypic and environmental correlation estimates were generally lower than those of genetic ones. Estimates of permanent environmental correlation among traits were positive and medium to high. Although low direct heritabilities were estimated for the reproductive traits, as these traits are of interest then they should be included in a breeding program.

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

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

Genetic parameters for buffalo milk yield and milk quality traits using Bayesian inference

The availability of accurate genetic parameters for important economic traits in milking buffaloes is critical for implementation of a genetic evaluation program. In the present study, heritabilities and genetic correlations for fat (FY305), protein (PY305), and milk (MY305) yields, milk fat (%F) and protein (%P) percentages, and SCS were estimated using Bayesian methodology. A total of 4,907 lactations from 1,985 cows were used. The (co)variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year and calving season), number of milking (2 levels), and age of cow at calving as (co)variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The posterior means of heritability distributions for MY305, FY305, PY305, %F, P%, and SCS were 0.22, 0.21, 0.23, 0.33, 0.39, and 0.26, respectively. The genetic correlation estimates ranged from −0.13 (between %P and SCS) to 0.94 (between MY305 and PY305). The permanent environmental correlation estimates ranged from −0.38 (between MY305 and %P) to 0.97 (between MY305 and PY305). Residual and phenotypic correlation estimates ranged from −0.26 (between PY305 and SCS) to 0.97 (between MY305 and PY305) and from −0.26 (between MY305 and SCS) to 0.97 (between MY305 and PY305), respectively. Milk yield, milk components, and milk somatic cells counts have enough genetic variation for selection purposes. The genetic correlation estimates suggest that milk components and milk somatic cell counts would be only slightly affected if increasing milk yield were the selection goal. Selecting to increase FY305 or PY305 will also increase MY305, %P, and %F.

Short communication: Genetic and environmental relationships between milk yield and kidding interval in dairy goats

First-parity 305-d milk yield and intervals between first and second kiddings from 1975 through 2005 were analyzed to estimate genetic and environmental parameters for United States Alpine, LaMancha, Nubian, Saanen, and Toggenburg dairy goats. The data set included 43,612 does with first-parity milk yield and 25,863 does with first kidding interval. Parameters were estimated by REML using bivariate mixed models within and across breeds. Fixed effects were month and herd-year of kidding within breed and month and breed-herd-year of kidding across breeds. Random effects were animal and residual. The heritability estimate for first-parity milk yield was 0.36±0.01 across breeds and ranged from 0.35 to 0.38 within breed; heritability for first kidding interval was 0.05±0.01 across breeds and ranged from 0.00 to 0.15 within breed. The estimate of the genetic correlation between first-parity milk yield and first kidding interval was positive (unfavorable) across breeds (0.35±0.09). Estimates of environmental correlations within and across breeds were positive (0.16–0.25). The presence of unfavorable genetic relationships between milk yield and kidding interval indicates a need to include reproductive performance as a selection criterion.

Aplicação do método Bayesiano na estimação de correlações genéticas e fenotípicas de peso em codornas de corte em várias idades

Objetivou-se com este estudo obter estimativas de correlações genéticas e fenotípicas para características peso aos 7 dias (PES7), peso aos 14 dias (PES14), peso aos 28 dias (PES28) e peso aos 42 dias de idade (PES42) de codornas de corte. No galpão de criação, foram alojadas 1.022 aves devidamente identificadas, utilizadas para avaliação do desempenho produtivo, por meio de pesagens individuais. Os componentes de (co)variância e os parâmetros genéticos foram estimados por procedimentos Bayesianos via amostrador de Gibbs utilizando-se o programa MTGSAM. As estimativas de correlações genéticas obtidas foram de 0,73 entre PES7 e PES14, 0,52 entre PES7 e PES28, 0,55 entre PES7 e PES42, 0,73 entre PES14 e PES28 e 0,56 entre PES14 e PES42 dias de idade. Correlação genética de 0,81 entre os pesos de 28 e 42 dias de idade indica a possibilidade de aumento do peso corporal aos 42 dias de idade pela seleção do peso corporal aos 28 dias de idade. As correlações fenotípicas variaram de 0,57 a 0,85 e foram ligeiramente superiores às genéticas, sugerindo que a correlação de ambiente é de pequena magnitude e positiva. Os menores intervalos de credibilidade das estimativas de correlações genéticas foram entre os pesos aos 28 e 42 dias e aos 14 e 28 dias.

Repeatability estimates of genetic, phenotypic and environmental correlations in oats with and without fungicide application

1 ABSTRACT - Estimates of associations among traits are not very precise when based on annual data since the year factor influence the phenotype strongly. Therefore, objective of this work was to estimate the repeatability coefficients and number of years needed for an accurate prediction of genetic, phenotypic and environmental correlations among six important traits in oat with and without fungicide application (treatments). Nine oat cultivars were evaluated for four years (2000, 2001, 2002, and 2003) with and without fungicide, in a random block design with three replications. In the absence of fungicide, two years of trial evaluation were enough to provide reliable phenotypic and genetic correlation estimates; the same was not true for the experiments with fungicide application where at least seven (phenotypic) and 21 (genetic) years were required. In both treatments the environmental correlation estimates were little predictable.

Estimativas de correlações genotípicas e de ambiente em gerações com elevada freqüência de heterozigotos

A correlação genotípica permite avaliar a magnitude e a direção da associação entre caracteres, sendo de grande utilidade por permitir a viabilidade do emprego da seleção indireta, que em alguns casos, pode levar a progressos genéticos mais rápidos e altamente expressivos em programas de melhoramento de aveia (Avena sativa L.). O objetivo deste trabalho foi avaliar a viabilidade da implementação de uma modificação na fórmula de PETR & FREY (1966), para a obtenção de estimativas de correlação genotípica, fenotípica e de ambiente, através da análise de quatro populações segregantes F2 de aveia: OR 2 x UPF 18, UPF 7 x CTC 5, OR 2 x UPF 7, UPF 18 x CTC 5. As estimativas de correlação genotípica indicam que a seleção de plantas de alta produtividade de grãos pode ser realizada indiretamente através dos caracteres número de panículas por planta, peso de panícula, número de grãos por panícula e peso médio de grãos. Entretanto, as diferenças em magnitude e direção das estimativas de correlações, entre os vários pares de caracteres, nas quatro populações estudadas, não permitem a generalização de uma estratégia de seleção, isto devido as limitações impostas pelas diferenças entre as constituições genéticas dos genitores e populações. Desta forma, é de fundamental importância a avaliação da capacidade combinatória das principais constituições genéticas utilizadas em cruzamentos artificiais, a fim de se estabelecer critérios mais efetivos a serem empregados na seleção de genótipos superiores.

Number of calves born, number of calves weaned, and cumulative weaning weight as measures of lifetime production for Hereford cows.

Genetic parameters for lifetime production for cows with the opportunity to produce from 2 through 7 yr of age, as measured by the number of calves born (NB2, ..., NB7), the number of calves weaned (NW2, ..., NW7), and cumulative weaning weight (CW2, ..., CW7), were estimated using data from 3,064 Hereford cows from a selection experiment with a control line (CTL) and three lines selected for weaning weight (WWL), yearling weight (YWL), and an index of yearling weight and muscle score (IXL). Weaning weights were adjusted to 200 d of age and for sex and age of dam. Estimates of heritability and genetic and environmental correlations were obtained by restricted maximum likelihood with bivariate animal models, with year of birth of the cow as a fixed effect and direct genetic and residual as random effects. Genetic trends were estimated by regressing means of estimated breeding values by year of birth and line on birth year. Estimates of heritability (SE) for opportunity groups of 2 to 7 yr of age ranged from 0.08 (0.03) to 0.16 (0.05) for NB; from 0.05 (0.02) to 0.16 (0.05) for NW; and from 0.06 (0.02) to 0.16 (0.05) for CW. Estimates of genetic correlations (SE) among NB traits ranged from 0.60 (0.14) to 1.00 (0.00), and estimates of environmental correlations (SE) ranged from 0.67 (0.02) to 0.99 (0.00). For NW, estimates of genetic and environmental correlations ranged from 0.98 (0.11) to 1.00 (0.00) and from 0.65 (0.02) to 0.99 (0.00), respectively. Estimates of genetic correlations (SE) among CW traits ranged from 0.94 (0.08) to 1.00 (0.00). Estimates of environmental correlations (SE) ranged from 0.66 (0.02) to 0.99 (0.00). Estimates of genetic correlations for NB2 with all definitions of NW ranged from 0.47 (0.18) to 0.71 (0.12), and with all definitions of CW ranged from 0.55 (0.16) to 0.80 (0.11). Estimates of genetic correlations between NW2 and all definitions for CW ranged from 0.95 (0.02) to 0.99 (0.06). Estimates of annual genetic (SE) change were negligible for NB2, NB6, NW2, and NW6 for all lines. Estimates of annual genetic (SE) change for CW2 were 0.85 (0.11), 0.79 (0.14), 0.51 (0.10), and 0.52 (0.18) kg/yr, and for CW6 were 5.01 (1.25), 2.64 (1.75), 3.67 (1.16), and 3.33 (2.37) kg/yr for WWL, YWL, IXL, and CTL, respectively. Selection for lifetime production as measured by NB, NW, or CW could be effective but would be relatively slow due to low estimates of heritability and to increased generation intervals.

Genetic parameters for six measures of length of productive life and three measures of lifetime production by 6 yr after first calving for Hereford cows.

Genetic parameters for length of productive life given the opportunity (LPL/O), measured as days between first calving and disposal conditioned on one of six opportunity groups, L1 through L6 (e.g., L2 is length of productive life in days given the opportunity to live 2 yr after first calving), and lifetime production (LP), measured as the number of calves born (NB), number of calves weaned (NW), and cumulative weaning weight (CW) by 6 yr after first calving, were estimated using records of 1,886 Hereford cows from a selection experiment with three selected lines and a control line. Weaning weights were adjusted to 200 d of age and for sex and age of dam. Estimates of heritability and genetic and environmental correlations were obtained by restricted maximum likelihood with bivariate animal models, with year of birth of cow as a fixed effect and direct genetic and residual as random effects. Genetic trends were estimated by regressing means of estimated breeding values by year of birth and line on birth year. Estimates of heritability (SE) for LPL/O ranged from 0.05 (0.01) to 0.15 (0.03). Estimates of genetic correlations (SE) among LPL/O ranged from 0.74 (0.14) to 1.00 (0.00), and estimates of environmental correlations ranged from 0.67 (0.05) to 0.98 (0.01). Estimates of heritability (SE) for NB, NW, and CW were 0.17 (0.05), 0.21 (0.06), and 0.18 (0.01). Estimates of genetic correlations (SE) among NB, NW, and CW ranged from 0.96 (0.02) to 0.99 (0.01). Estimates of environmental correlations (SE) ranged from 0.93 (0.01) to 0.99 (0.01). Estimates of genetic correlations for L6 with NB, NW, and CW were near 1.00 (0.09). Estimates of environmental correlations (SE) ranged from 0.57 (0.03) to 0.60 (0.03). Estimates of genetic change per year (SE) for L6 were low for all lines and ranged from -3.53 (2.09) to 4.63 (2.11) d/yr. Genetic trends for NB and NW were negligible for all lines. Genetic trends for CW were low and ranged from -2.81 (1.67) to 3.29 (1.76) kg/yr. Differences in genetic trends between selected lines and control were not significant (P > 0.05). Estimates of environmental trends (SE) over all lines were -104.00 (25.48) d/yr, -0.26 (0.02) calves/yr, -0.25 (0.02) calves/yr, and -55.10 (15.63) kg/yr, for L6, NB, NW, and CW, respectively. Selection for LPLIO or LP could be successful in a breeding program, but may be relatively slow due to the low magnitude of heritability and extended generation interval.

Genetic antagonism between body weight and milk production in beef cattle.

Korean cattle have an unusually short suckling period (4 mo) due to poor milking ability, and this is a hindrance to growth of calves. Therefore, Korean cattle breeders have shown interest in genetic improvement of milking ability. In this study, body weight (birth weight, weaning weight, and yearling weight) and five daily milk yields by period in Korean cattle (Hanwoo) were analyzed using a two-trait sire and maternal grandsire mixed model. The milk yields used were actually measured at sequential intervals from 1 to 4 mo after calving. Posterior means of the parameters were estimated using Gibbs sampling. Heritability estimates (0.25 to 0.26) for daily milk yield at weaning were larger than those with other periods. Genetic impact on daily milk yield, especially at weaning, was emphasized in order to lengthen the suckling period of Korean cattle. Genetic correlation estimates between BW and daily milk yield were all negative (-0.08 to -0.16 for birth weight, -0.04 to -0.21 for weaning weight, and -0.12 to -0.19 for yearling weight), whereas environmental correlation estimates were all positive (0.20 to 0.39 for birth weight, 0.34 to 0.51 for weaning weight, and 0.30 to 0.45 for yearling weight). The negative estimates of genetic correlation between weight and milk yield implied genetic antagonism between direct and maternal effects for weaning weight of beef cattle.

Parameter estimates for direct and maternal genetic effects on yearling, eighteen-month, and slaughter weights of Korean native cattle.

Data collected by the National Livestock Research Institute of the Rural Development Administration of Korea were used to estimate genetic parameters for yearling (YWT, n = 5,848), 18-mo (W18, n = 4,585), and slaughter (SWT, n = 2,279) weights for Korean Native cattle. Nine animal models were used to obtain REML estimates of genetic parameters: DP-2 included genetic, uncorrelated dam, and residual random effects; DQ-2 included genetic, sire x region x year-season interaction, and residual random effects; DPQ-2 was based on DQ-2 but included both interaction and dam effects; DMP-2 was based on DP-2 but with dam effect partitioned to include maternal genetic and permanent environmental effects; and DMPQ-2 was based on DMP-2 but also included sire interaction effects. Those five models included two fixed factors: region x year-season and age of dam x sex effects. Models DP-3, DQ-3, DPQ-3, and DMPQ-3 were based on DP-2, DQ-2, DPQ-2, and DMPQ-2 but included as a third fixed factor whether or not identification of the sire was known. Estimates of heritability with DMPQ-3 for YWT, with DPQ-3 for W18 and SWT when analyzed with single-trait analyses were .14, .11, and .17, respectively, and were nearly the same with bivariate analyses. Estimate of maternal heritability for YWT from single-trait analysis was .04, with estimates for other traits near zero. For bivariate analyses, the estimate for YWT was .01. With single trait analysis, estimate of the direct-maternal genetic correlation for YWT was negative (-.81). Estimates of direct genetic correlations between YWT and W18, YWT and SWT, and W18 and SWT were .99, 1.00, and .97, respectively. Estimates of environmental correlations varied from .60 to .81; the largest was between W18 and SWT. Including a fixed factor for whether sire identification was missing or not missing reduced the estimate of heritability for slaughter weight. The results suggest that the sire x region x year-season interaction is important for yearling weight and may be needed in a model for slaughter weight. Maternal effects may be of slight importance for yearling weight but of no importance for W18 and SWT. Models for national cattle evaluations for Korean Native cattle for YWT should be considered that include maternal genetic and permanent environmental as well as sire x region x year-season interaction effects, but those effects seem not to be needed for models for W18 and SWT. Not much reranking of sires occurred when ranked was based on the different models for W18 and SWT.

Estimation of genetic parameters for scrotal circumference, age at puberty in heifers, and hip height in Brahman cattle.

Genetic parameters were estimated for scrotal circumference (SC; n=287), age at puberty in heifers (AP; n=292), and hip height in both sexes (HH; n=684) for Brahman cattle born from 1984 to 1994 at the Subtropical Agricultural Research Station, Brooksville, Florida. Age at puberty was defined as the age (days) at first detected ovulatory estrus. Measurements of SC and HH were taken at 18 mo of age. Fixed effects considered in the SC model were year of birth (YOB), age of dam (AOD), and age at measurement (AGE) as a linear covariate. Fixed effects fitted to the AP model were YOB and AOD. Fixed effects in the HH model were YOB, sex, AOD, and AGE as a linear covariate. Variances and covariances were estimated using REML with a derivative-free algorithm and fitting a multiple trait animal model. Estimates of heritability for SC, AP, and HH were .28, .42, and .65, respectively. Estimates of genetic correlations between SC and AP, SC and HH, and AP and HH were -.32, .19, and .25, respectively. Estimates of environmental correlations were .19 between SC and HH, and -.13 between AP and HH. Estimates of genetic parameters indicate a favorable genetic relationship between SC in Brahman bulls and AP in Brahman heifers under subtropical conditions. There was also evidence that selecting Brahman bulls for HH would not adversely affect SC but would have some detrimental effect on AP in female progeny.

Estimates Using an Animal Model of (Co)variances for Yields of Milk, Fat, and Protein for the First Lactation of Holstein Cows in California and New York

First lactation yields of milk, fat, and protein from Holstein cows in New York and California were used to obtain REML estimates of (co)variances for yield traits using a multitrait animal model. Data from each state were split randomly into 10 samples, averaging 5504 cows per sample from California and 5078 from New York. Mean heritability estimates for milk, fat, and protein yields were .30±.02, .31±.01, and .29±.01 for California data and .33±.01, .35±.01, and .30±.01 for New York data. Averages of genetic correlation estimates for California and New York were .63±.01 and .52±.02 between milk and fat, .84±.01 and .83±.01 between milk and protein, and .73±.01 and .68±.01 between fat and protein. Estimates of environmental correlations were larger than estimates of genetic correlations. Mean estimates of phenotypic correlations for California and New York were .75±.01 and .72±.01 between milk and fat, .92±.01 and .91±.01 between milk and protein, and .81±.01 and .79±.01 between fat and protein yields. On average, these estimates agree with those obtained from animal models with limited rounds of iteration for small data files.

Age adjustment factors, heritabilities and genetic correlations for scrotal circumference and related growth traits in Hereford and Brangus bulls.

Field data records on 10,511 Hereford and 2,522 Brangus bulls between 330 and 430 d of age were analyzed to find age of calf and age of dam adjustment factors for yearling scrotal circumference. Age of calf adjustment factors were .024 cm/d for Hereford bulls and .041 cm/d for Brangus bulls. Sons of Hereford dams were adjusted to a 6- to 8-yr dam age basis by adding .7, .3, .2, .2 or .3 cm for dams 2, 3, 4, 5 or 8 or more years old, respectively. Age of dam adjustment factors for Brangus bulls were .8, .4, .3 and .2 for dams 2, 3, 4 or 8 or more years old, respectively. Variance and covariance components for yearling scrotal circumference and several growth traits were estimated within breed using multiple-trait models and pseudo expectations involving the solutions and the right-hand sides of the mixed-model equations. Additive heritability estimates for yearling scrotal circumference of .53 and .16 were found for Hereford and Brangus bulls, respectively. Maternal heritability estimates of .12 and .10 were found for Hereford and Brangus bulls, respectively. Genetic correlations between yearling scrotal circumference and other growth traits were positive for both sets of data indicating that selection for yearling scrotal circumference should not adversely affect other growth traits in either breed. Environmental correlation estimates between yearling scrotal circumference and adjusted birth weight and between yearling scrotal circumference and adjusted 205-d weight and adjusted 365-d height were positive and moderate in magnitude for both breeds.