Comparison of Alternative Models for Within-Herd Genetic Evaluation of Beef Cattle

Pollak, Edward; Ufford, G.R.; Gross, Sheila J.

doi:10.2527/jas1977.4551010x

Cited by 20 publications

(14 citation statements)

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“…The reduction of the error variance of prediction, comparing MMR with MM in Durocs, was 41.7% lower for MMR. These values generally are equal to or higher than those found by Kennedy and Moxley (1975), Pollak et al (1977) and Tong et al (1980). In addition to the much lower prediction error variances, MMR allows animals in different subgroups to be more accurately compared (Henderson, 1975b).…”

Section: Resultsmentioning

confidence: 84%

“…Kennedy and Moxley (1975) found that including relationships among dairy bulls reduced the average prediction error variance by 18% compared with a model that grouped bulls according to date of birth. Pollak et al (1977) reported in beef cattle that the prediction error variance increased from 3.5 to 22.2% when genetic relationships were ignored. Also, values for younger sires increased more.…”

Section: An Evaluation Of Four Procedures To Rank Centrally Tested Bomentioning

confidence: 99%

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An Evaluation of Four Procedures to Rank Centrally Tested Boars

Carlson¹,

Christian²,

Rothschild³

et al. 1984

Journal of Animal Science

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Section: Resultsmentioning

confidence: 84%

Section: An Evaluation Of Four Procedures To Rank Centrally Tested Bomentioning

confidence: 99%

An Evaluation of Four Procedures to Rank Centrally Tested Boars

Carlson¹,

Christian²,

Rothschild³

et al. 1984

Journal of Animal Science

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“…E(MSE)=tr(Z'Z+A--1T)--la2e/32 [10] where tr denotes the trace of a matrix. Under a no groups model with all relationships known E(MSE) = .011.…”

Section: Journal Of Dairymentioning

confidence: 99%

“…Use and definition of genetic groups for sire evaluation has received attention in (6,7,8,10). In a review of sire evaluation and genetic groups (2), effects of selection were examined in reference to the problem of defining genetic groups.…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo Study of Genetic Groups in Sire Evaluation

Vleck

1982

Journal of Dairy Science

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Fixed genetic groups have been defined arbitrarily in linear models for sire evaluation. This simulation examined genetic groups under several selection strategies. Sires with highest estimated transmitting abilities were selected to have sons and additional female progeny. The process of evaluation and selection of sires and dams was continued for four generations. Final estimates of transmitting ability were compared to actual transmitting ability for several sire evaluation models on 300 simulated data sets. Genetic groups defined by generation increased the accuracy of estimating sire transmitting abilities over ignoring genetic groups when selected dams and sires of young bulls were mated. A joint selection model was presented which assists in interpreting results of simulation.

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“…Originally applied to dairy cattle AI data (Henderson, 1973), mixed models have been used extensively in the beef industry (Winrock international, 1983) and numerous variations on the original sire evaluation model have been developed (Henderson, 1973;Pollak et al, 1977;Berger, 1983;Blair and Pollak, 1984). A review of topics pertaining to methods of sire evaluation is found in Thompson (1979) ( When large systems of equations are involved, approximations to PEV must be used.…”

Section: Mixed Modelsmentioning

confidence: 99%

Application of mixed model methodology to the evaluation of performance tested boars

Wood

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Comparison of Alternative Models for Within-Herd Genetic Evaluation of Beef Cattle

Cited by 20 publications

References 0 publications

An Evaluation of Four Procedures to Rank Centrally Tested Boars

An Evaluation of Four Procedures to Rank Centrally Tested Boars

Monte Carlo Study of Genetic Groups in Sire Evaluation

Application of mixed model methodology to the evaluation of performance tested boars

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