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Featured researches published by E.J. Pollak.


Journal of Animal Science | 2012

The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations 1,2,3

K. L. Weber; Daniel J. Drake; J. F. Taylor; Dorian J. Garrick; L. A. Kuehn; R. M. Thallman; Robert D. Schnabel; W. M. Snelling; E.J. Pollak; A. L. Van Eenennaam

Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using Bovine SNP50 genotypes and phenotypic or EBV data. Molecular breeding values for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboration between researchers from Iowa State University and the University of Missouri-Columbia (ISU/UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using 2 multibreed populations, the Germplasm Evaluation (GPE) Program and the 2,000 Bull Project (2K(ALL)), and 2 single breed subpopulations of the 2,000 Bull Project, Angus (2K(AN)) and Hereford (2K(HH)). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multisire breeding pastures to commercial cows: 121 for USMARC MBV, 99 for ISU/UMC MBV, and 29 for IGENITY and Pfizer MBV (selected based on number of progeny carcass records). Five traits were analyzed: weaning weight (WW), HCW, marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfizer only, feedlot ADG. The average accuracies of MBV across traits were 0.38 ± 0.05 for IGENITY, 0.61 ± 0.12 for Pfizer, 0.46 ± 0.12 for ISU/UMC, 0.16 ± 0.04 for GPE, 0.26 ± 0.05 for 2K(ALL), 0.24 ± 0.04 for 2K(AN), and 0.02 ± 0.12 for 2K(HH). Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2K(AN)) explained larger proportions of genetic variance in this population than GPE, 2K(ALL), or 2K(HH) MBV for the same traits. In this data set, IGENITY, Pfizer, and ISU/UMC MBV were predictive of realized performance of progeny, and incorporation of that information into national genetic evaluations would be expected to improve EPD accuracy, particularly for young animals.


Journal of Animal Science | 1980

Mixed model methodology for farm and ranch beef cattle testing programs.

R. L. Quaas; E.J. Pollak


Journal of Dairy Science | 1988

Length of Productive Life of Dairy Cows. 2. Variance Component Estimation and Sire Evaluation

V. Ducrocq; R.L. Quaas; E.J. Pollak; G. Casella


Journal of Dairy Science | 1988

Length of Productive Life of Dairy Cows. 1. Justification of a Weibull Model

V. Ducrocq; R.L. Quaas; E.J. Pollak; G. Casella


Journal of Animal Science | 2003

Genetic parameters for carcass traits and their live animal indicators in Simmental cattle

D. H. Crews; E.J. Pollak; Robert L. Weaber; R.L. Quaas; R. J. Lipsey


Journal of Animal Science | 1989

VARIANCE HETEROGENEITY IN DIRECT AND MATERNAL WEIGHT TRAITS BY SEX AND PERCENT PUREBRED FOR SIMMENTAL-SIRED CALVES

D. J. Garrick; E.J. Pollak; R.L. Quaas; L.D. Van Vleck


Journal of Animal Science | 1997

Relationship between sire x year interactions and direct-maternal genetic correlation for weaning weight of Simmental cattle.

Chaeyoung Lee; E.J. Pollak


Journal of Dairy Science | 1984

Selection Bias and Multiple Trait Evaluation

E.J. Pollak; J. H. J. van der Werf; R.L. Quaas


Journal of Dairy Science | 1981

Modified Equations for Sire Models with Groups

R.L. Quaas; E.J. Pollak


Journal of Dairy Science | 2000

Genetic Analysis of Holstein Cattle Populations in Brazil and the United States

C.N. Costa; R.W. Blake; E.J. Pollak; P.A. Oltenacu; R.L. Quaas; Shayle R. Searle

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C.P. Van Tassell

Agricultural Research Service

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D. H. Crews

Colorado State University

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