ArticleFrontiers in genetics2021
A Random Regression Model Based on a Single-Step Method for Improving the Genomic Prediction Accuracy of Residual Feed Intake in Pigs.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Accuracy of single-step genomic selection for egg production in yellow-feathered broilers using a random regression model.Poultry science · 2026Article
- Different feed efficiency modeling approaches for the prediction of genomic breeding values in lactating dairy cows.Frontiers in genetics · 2026Article
- Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.JDS communications · 2024Article
- Analysis of Early Growth of Piglets from Hyperprolific Sows Using Random Regression Coefficient.Animals : an open access journal from MDPI · 2023Article
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8 authors.
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Abstract
Residual feed intake (RFI) is considered as a measurement of feed efficiency, which is greatly related to the growth performance in pigs. Daily feeding records can be obtained from automatic feeders. In general, RFI is usually calculated from the total measurement records during the whole test period. This measurement cannot reflect genetic changes in different growth periods during the test. A random regression model (RRM) provides a method to model such type of longitudinal data. To improve the accuracy of genetic prediction for RFI, the RRM and regular animal models were applied in this study, and their prediction performances were compared. Both traditional pedigree-based relationship matrix (
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