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R L Quaas

Publications and source records attributed to R L Quaas.

12 recordsLinked to original sources
PubMed1992

Parameter estimation for carcass traits including growth information of Simmental beef cattle using restricted maximum likelihood with a multiple-trait model.

(Co)variance component estimates were computed for retail cuts per day of age (kilograms per day), cutability (percentage of carcass weight), and marbling score (1 through 11) using a multiple-trait sire model. Restricted maximum likelihood estimates of (co)variance components were obtained via an expectation-maximization algorithm. Carcass data consisted of 8,265 progeny records collected by U.S. Simmental producers. Growth trait information (birth weight, weaning weight, and[or] postweaning gain) for those progeny with carcass data and an additional 5,405 contemporaries formed the complete data set for analysis. A total of 420 sires were represented. Three models differing in number of traits were investigated: 1) carcass traits with growth traits, 2) carcass traits only, and 3) single trait. The final models did not include postweaning gain because of convergence problems. Parameter estimates for all three models were essentially the same. Heritability estimates were .30, .18, and .23 for retail cuts per day, cutability, and marbling score, respectively. Correlations between growth and carcass traits were low except for those with retail cuts per day, which were moderate and positive. The additional information gained by adding growth traits to the carcass-traits-only evaluation lowered prediction error variances most for retail cuts per day. Little change in prediction error variances was found for cutability and marbling score. Inclusion of growth traits in future sire evaluations for carcass traits will benefit the evaluation of retail cuts per day but have considerably less effect on cutability and marbling score.

Analysis of Variance↗
PubMed1991

Simulation study on covariance component estimation for two binary traits in an underlying continuous scale.

The usefulness of the variance and covariance component estimation methods based on a threshold model was studied in a multiple-trait situation with two binary traits. Estimation equations that yield marginal maximum likelihood estimates of variance components on the underlying continuous variable scale and point estimates of location parameters with empirical Bayesian properties are described. Methods were tested on simulated data sets that were generated to exhibit three different incidences, 25, 15, and 5%. Results were compared with analyses of the same data sets with a REML method based on normal distribution and a linear model. Heritabilities and residual correlations calculated from discrete observations were transformed to underlying parameters. In estimation of heritabilities, all methods performed equally well at all incidence levels and with no detectable bias. As suggested by threshold theory, the genetic correlation was accurately estimated directly from the observations without any need of correction for incidence. Marginal maximum likelihood estimates of genetic correlations were similar to linear model estimates; discrepancies from the true parameters were consistent with both methods. In estimation of residual correlations, the method with the linear model approach yielded satisfactory estimates only at the highest incidence level, 25%. For 5% incidence, the uncorrected estimate of residual correlation was 50% less than the true value, and after correction for incidence, the parameter was overestimated by 90%. The estimates of residual correlation from the threshold model were regarded fair, except at the lowest level of incidence, where the estimate was 27% higher than the true value. Results indicated that when an accurate estimate of residual correlation is needed, the marginal maximum likelihood estimates are superior to the estimates calculated with the linear model. Using correction for the incidence level for residual correlation did not work well except at the highest incidence level.

Analysis of Variance↗
PubMed1991

Genotype by environment interaction for Holstein milk yield in Colombia, Mexico, and Puerto Rico.

Components of (co)variance and genetic parameters were estimated by REML procedures from first lactation mature equivalent Holstein milk records from 54,604 Colombian, Mexican, and Puerto Rican cows and 198,079 US cows. The objective was to determine the cause of heterogeneous daughter response to sire selection for milk yield between the regions. Data from Latin America were partitioned by country and by herd-year SD class for milk to obtain five joint analyses between the US and Latin America, low herd-year SD, high herd-year SD, Colombia, and Mexico. Sire and residual variances for milk were 41 and 29% smaller in Latin America than in the US, 47 and 58% smaller for low than for high herd-year SD, and 31 and 49% smaller for Colombia than for Mexico. Resultant heritabilities ranged from .20 to .29. Genetic correlations for milk yield between the US and Latin America, low and high herd-year SD, Colombia, and Mexico were .91, .82, .89, .78, and .90. Expected correlated responses for milk in Latin America, low and high herd-year SD, Colombia, and Mexico were 70, 53, 79, 56, and 78% of the direct response in the US. The scaling effects of heterogeneous variance resulted in smaller daughter milk responses in Latin America compared with the US even when herd-year SD was similar.

Animals↗
PubMed1991

Clinical ketosis: phenotypic and genetic correlations between occurrences and with milk yield.

The repeatability and heritability of ketosis were estimated using data from 28,277 Finnish Ayrshire cows. A four-trait linear model including community-year, calving age and month, genetic group, and random sire effects was used to describe first and second lactation milk yields and veterinary diagnoses of ketosis. Variance components were estimated using REML. The disease traits were also analyzed with a categorical model including the same effects except that community and year were separate factors. Variance components were estimated with marginal maximum likelihood. Genetic relationships between 339 sires analyzed were included in models. The phenotypic correlation between the first and second lactation was defined as a repeatability of trait. The lactational incidence risk of ketosis was .05 in both the first and the second lactation. Average milk production was 4956 and 5547 kg in the first and second lactations, respectively. Estimates of heritabilities were .09 and .07 for ketosis and .23 and .19 for milk in the first and second lactations, respectively. Genetic correlations between first and second lactation recordings were .64 for ketosis and .93 for milk. Repeatabilities between subsequent lactations were .36 (.13 in linear analysis) for ketosis and .68 for milk. In the first lactation, genetic relationship between milk yield and ketosis was unfavorable, but in the second lactation ketosis and milk yield were genetically and phenotypically unrelated.

Animals↗
PubMed1989

Variance heterogeneity in direct and maternal weight traits by sex and percent purebred for Simmental-sired calves.

Phenotypic variances for linear and transformed weight traits were partitioned into residual, direct genetic (D) and maternal genetic (M) components using REML techniques with American Simmental Association data from calves born 1969 to 1985. Variance components were estimated separately from subclasses defined by sex (male, female) and percent Simmental (50, greater than or equal to 75). The model included fixed effects of contemporary group and age-of-dam (less than 3, 3 to 5, greater than 5 yr). Additive relationships among sires and maternal grandsires were included. Results follow for a sire-maternal grandsire model for greater than or equal to 75% Simmental untransformed data based on 143,280 male and 281,805 female weaning weights (WW) representing 4,763 and 7,406 sires, respectively. Female results are bracketed. For computational simplification, 47,650 [30,909] postweaning gain (PW) records were included in the analysis only for 114,404 [182,255] calves with birth weight (BW). Phenotypic standard deviations (kg) were: BW, 4.5 [4.1]; WW, 26.9 [23.2]; and PW, 25.9 [19.9]. Heritabilities were: BWD, .40 [.45]; WWD, .32 [.39]; PWD, .26 [.32]; BWM, .13 [.15]; WWM, .20 [.16]; and PWM, .01 [.01]. These heritabilities are higher than previously used for genetic evaluations in this breed. Moderate and positive correlations .26 to .50, existed between direct effects and were similar for both sexes. Direct and maternal effects on the same trait were correlated negatively: BW, -.45 [-.31]; and WW, -.27 [-.34]. Genetic correlation between BWM and WWM was .53 [.49]. First-cross progeny exhibited less genetic and residual variation and had lower heritabilities than Simmental calves of higher percent. Correlations between sire evaluations on the subsets were consistent with those expected given a perfect genetic correlation between traits for each sex and percent Simmental. Logarithmic transformed records were no more homogeneous than untransformed records.

Analysis of Variance↗
PubMed1989

Multiple trait prediction for a type of model with heterogeneous genetic and residual covariance structures.

A restricted set of models is defined that allows for heterogeneous genetic and residual covariance structures. Multiple trait models and models with multiple random factors are included. The restriction on the model is that the correlations among genetic effects in different classes are the same. Equivalently, the genetic covariance matrices are assumed to differ between classes due to scaling. This assumption greatly reduces the number of parameters that must be specified and does not adversely affect the computational burden of a mixed model analysis. An application of the model for genetic evaluation of beef cattle is described and illustrated numerically.

Analysis of Variance↗
PubMed1988

Describing interactions in dystocia scores with a threshold model.

Field data on calving difficulty scores provided by the American Simmental Association were subjected to two methods of analysis: ordinary least-squares analysis and maximum likelihood with an assumed threshold model. In each analysis, the model included the interaction of sex of calf X age of dam. This interaction was readily apparent in the data (observed scale): within the youngest dams 58% of the heifer calves and 37% of the bull calves were born unassisted vs 96% and 92%, respectively, in the oldest dams. The objective was to determine if this interaction would be greatly reduced or would disappear on the underlying scale of a threshold model. The least-squares estimate of the sex difference was greatest within the youngest age-of-dam group (18 to 24 mo) and steadily declined with increasing age of dam, approaching zero for dams 6 yr and older. In contrast, the estimates of the sex difference from the threshold analysis were remarkably similar across ages of dam. It was concluded that observed interactions in calving ease data could be adequately described by a threshold model in which the effects of age of dam and sex of calf act additively on the underlying variable.

Age Factors↗
PubMed1987

Analysis of gestation length in American Simmental cattle.

Records of gestation length (71,461) for Simmental cattle were distributed with mean 284.3 d and standard deviation 5.52 d. Gestation length was found to increase with percent Simmental and was 1.9 d longer for calves born to mature dams than for those born to heifer dams. Bull calves experienced gestation lengths 1.5 d longer than heifer calves. Sire, maternal grandsire, residual and total variances were estimated to be 2.42, .58, 22.78 and 25.78 d2, respectively, by Henderson's Method III. Heritability of gestation length was calculated to be .374 from the sire variance and .09 from the maternal grandsire variance. Direct additive genetic variance was considered to be of greater importance than maternal additive genetic variance. Correlations between the evaluations of sires for gestation length and heifer calving ease, birth weight and weaning weight were .26, .26 and .13, respectively.

Animals↗
PubMed1987

Estimation of variance and covariance components to determine heritabilities and repeatability of weaning weight in American Simmental cattle.

Components of (co)variance for weaning weight were estimated from field data provided by the American Simmental Association. These components were obtained for the observational components of variance corresponding to a sire, maternal grandsire, and dam within maternal grandsire model. From these estimates, direct additive genetic variance (Sigma2A), maternal additive genetic variance (Sigma2M), covariance between direct and maternal additive genetic effects (SigmaAM), variance of permanent environment(Sigma2pe) and temporary environment variance(Sigma2te) were determined. A procedure to approximate restricted maximum likelihood (REML) estimates of the observational components of variance based on the expectation-maximization (EM) algorithm is described. From these results, phenotypic variance ( ) of weaning weight was 667.88 kg2. Values forSigma2A, Sigma2M, Sigma2pe and Sigma2te were 79,30,58,38,49.45, and 469.97 kg2, respectively. Genetic correlation between direct and maternal additive genetic effects was .16.

Animals↗
PubMed1986

Lambing performance of Morlam and Dorset ewes under accelerated lambing systems.

Two accelerated lambing systems, Morlam using Morlam sheep (USDA, Beltsville 1966 to 1975) and Camal using Dorset ewes (Cornell 1978 to 1981), were evaluated for first lambing ages, interlambing intervals and conception probabilities. Morlam ewes were continuously exposed to rams over the year, while Camal Dorset ewes were exposed every other month. Morlam lambs were mated as early as 367 d of age and Camal Dorset lambs as early as 340 d. Early lambing was associated with higher rates of perinatal mortality (P greater than .05) and smaller litter size (P less than .01). Lambing years among Morlam ewes and season of birth of Camal Dorset ewes influenced (P less than .01) their first lambing ages. Lambing intervals averaged 293 and 303 d among Morlam and Camal Dorset ewes, respectively. Age at first lambing and season in which the previous lambing occurred with influential factors (P less than .01) on lambing intervals of Morlam ewes; longer intervals resulted when ewe lambs were mated at early ages (less than 12 mo), and when the previous lambing occurred in winter. Estimates of conditional probabilities of conception by month given the occurrence of estrus, reflected seasonal changes in both systems. The overall probability of conception for the Morlam system (P = .16) was relatively higher than that for the Camal Dorset system (P = .14); numbers of lambings per ewe per yr were 1.28 and 1.21, respectively. Estimates of heritability for age at first lambing, lambing interval and conception probability were .31, .06 and .30, respectively.

Animals↗
PubMed1986

Approximating prediction error variances for multiple trait sire evaluations.

The coefficient matrix for multiple trait (milk, fat, and protein) mixed model equations may be too large to obtain prediction error variances from inverse elements. The commonly used reciprocals of diagonal elements may not be accurate approximations when sire relationships or multiple traits are included since much information is contained in offdiagonal elements. Approximations incorporating increased information from coefficient matrix were compared with actual prediction error variances for multiple trait evaluations for milk, fat, protein, and dollar value (relationships included) of 229 Ayrshire and 248 Brown Swiss bulls. Six approximations were selection index using number of daughter records, inverses of individual sire diagonal blocks, inverses of group and individual sire blocks, and inverses of all diagonal blocks and offdiagonal blocks associated with individual sires. All approximations under-estimated actual prediction error variances, but most, except selection index, were highly correlated (.90 to .99) with actual prediction error variances of sire evaluations for milk yield and product value for contemporary bulls. The approximation incorporating most information from the coefficient matrix is recommended for use on basis of high correlation with and closeness to actual prediction error variances.

Analysis of Variance↗