Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Approximation of reliabilities for multiple-trait model with maternal effects.

T Strabel1, I Misztal, J K Bertrand

  • 1Department of Animal and Dairy Science, University of Georgia, Athens 30602, USA.

Journal of Animal Science
|April 28, 2001
PubMed
Summary

This study improved genetic reliability estimation in Senepol cattle by comparing single-trait and multiple-trait models. The multiple-trait approach demonstrated reduced approximation bias for estimating direct and maternal effects on traits like birth weight and weaning weight.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Approximating reliabilities of indirect predictions using single nucleotide polymorphism effects from large single-step genomic best linear unbiased predictor evaluations.

Journal of dairy science·2025
Same author

Efficient implementation of multitrait random regression test-day models with external information for dairy cattle genomic evaluations.

Journal of dairy science·2025
Same author

Review: Genomic selection in the era of phenotyping based on digital images.

Animal : an international journal of animal bioscience·2025
Same author

All-breed single-step genomic best linear unbiased predictor evaluations for fertility traits in US dairy cattle.

Journal of dairy science·2024
Same author

Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.

JDS communications·2024
Same author

Single-step genomic predictions for crossbred Holstein and Jersey cattle in the United States.

JDS communications·2024

Area of Science:

  • Animal Genetics
  • Quantitative Genetics
  • Livestock Breeding

Background:

  • Estimating genetic parameters like reliability is crucial for animal breeding programs.
  • Maternal effects significantly influence offspring performance, necessitating their inclusion in genetic models.
  • Previous methods for calculating reliability in multiple-trait models had limitations.

Purpose of the Study:

  • To obtain reliabilities for a multiple-trait maternal model by combining single-trait model reliabilities.
  • To evaluate approximation methods for estimating genetic parameters in Senepol cattle.
  • To compare the accuracy of single-trait versus multiple-trait approximation methods for reliability estimation.

Main Methods:

  • Utilized an approximation method supporting additive and permanent environmental effects for single-trait reliabilities.

Related Experiment Videos

  • Applied generalized inversion and both single-trait and multiple-trait approximation methods to estimate reliabilities.
  • Analyzed birth weight, weaning weight, and postweaning gain records from 10,550, 11,819, and 3,617 Senepol cattle, respectively.

    • Main Results:

    • The multiple-trait approximation method showed reduced bias compared to the single-trait method.
    • High correlations (0.85-0.96) were observed between inversion and multiple-trait reliabilities for direct effects across traits.
    • Strong correlations (0.96-0.98) were found for maternal effects in birth and weaning weights.

    Conclusions:

    • The multiple-trait approximation method offers a more accurate approach for estimating genetic reliabilities, particularly for maternal effects.
    • Refining single-trait procedures could lead to further improvements in reliability estimation.
    • Accurate genetic parameter estimation is vital for effective selection in livestock populations.