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 Video

Updated: May 9, 2026

Embryo Transfer Surgery via Laparotomy in Gilts
05:41

Embryo Transfer Surgery via Laparotomy in Gilts

Published on: October 18, 2024

Genome-enabled methods for predicting litter size in pigs: a comparison.

L Tusell1, P Pérez-Rodríguez, S Forni

  • 11 Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.

Animal : an International Journal of Animal Bioscience
|July 25, 2013
PubMed
Summary
This summary is machine-generated.

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

Effects of exercise training on frail older adults with heart failure: a systematic-review.

Frontiers in aging·2026
Same author

Temporal evolution of Sow herd age structure and its impact on the performance of Spanish commercial farms.

Porcine health management·2025
Same author

Unravelling the mechanisms underlying the social interaction effects on the feed efficiency of rabbits.

Animal : an international journal of animal bioscience·2024
Same author

Fabrication and evaluation of porous coatings doped with bioactive elements on titanium surfaces.

European review for medical and pharmacological sciences·2024
Same author

Novel phenotypes of feeding and social behaviour and their relationship with individual rabbit growth and feed efficiency.

Animal : an international journal of animal bioscience·2024
Same author

Recombinant erythropoietin protective and related effects on brain injury in premature infants.

European review for medical and pharmacological sciences·2023

Genomic models improved litter size prediction in swine compared to traditional methods. Bayesian regularized neural networks showed the highest predictive ability, especially in crossbred pigs.

Area of Science:

  • Animal Genetics
  • Quantitative Genetics
  • Swine Breeding

Background:

  • Accurate prediction of litter size is crucial for efficient swine production.
  • Genomic selection offers potential for improving predictive accuracy over pedigree-based methods.

Purpose of the Study:

  • To investigate the predictive ability of various genetic models for litter size in swine.
  • To compare the performance of different genomic and pedigree-based models across purebred and crossbred lines.

Main Methods:

  • Evaluated pedigree-based mixed-effects model (PED), Bayesian ridge regression (BRR), Bayesian LASSO (BL), genomic BLUP (GBLUP), reproducing kernel Hilbert spaces regression (RKHS), Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN).
  • Utilized 60K SNP data from 2598, 1604, and 1897 genotyped sows across two purebred and one crossbred line.

More Related Videos

Accurate and Phenol Free DNA Sexing of Day 30 Porcine Embryos by PCR
10:16

Accurate and Phenol Free DNA Sexing of Day 30 Porcine Embryos by PCR

Published on: February 14, 2016

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs
06:30

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs

Published on: June 5, 2019

Related Experiment Videos

Last Updated: May 9, 2026

Embryo Transfer Surgery via Laparotomy in Gilts
05:41

Embryo Transfer Surgery via Laparotomy in Gilts

Published on: October 18, 2024

Accurate and Phenol Free DNA Sexing of Day 30 Porcine Embryos by PCR
10:16

Accurate and Phenol Free DNA Sexing of Day 30 Porcine Embryos by PCR

Published on: February 14, 2016

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs
06:30

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs

Published on: June 5, 2019

  • Assessed predictive ability using 10-fold cross-validation and average correlation (r) between observed and predicted phenotypes.

    • Main Results:

    • Genome-based models generally outperformed the pedigree-based model (PED).
    • Non-parametric models (RKHS, BRNN, RBFNN) showed predictive abilities ranging from 0.15 to 0.23, similar to parametric models.
    • Bayesian regularized neural networks (BRNN) achieved the highest prediction accuracy (r = 0.31) in crossbreds using the genomic relationship matrix (G).
    • Predictive ability was higher in crossbreds (0.26) than in purebreds (0.15–0.22), potentially due to family structure differences.

    Conclusions:

    • Genomic information significantly enhances the prediction of litter size in swine.
    • Model choice and population structure (purebred vs. crossbred) influence predictive performance.
    • BRNN demonstrates strong potential for genomic prediction of litter size, particularly in crossbred populations.