Publications by authors named "D Mansan Gordo"
Article Synopsis
- Genetic selection for productive longevity (PL) in beef cattle is essential for improving profitability in beef cow-calf operations, and this study aimed to create a model for predicting genetic merit for PL using large datasets.
- The research utilized extensive pedigree and phenotype data, as well as genotypic information, to fit statistical models that consider various systematic and random effects that influence PL.
- Results indicated that while heritability estimates for PL were low, suggesting environmental factors play a significant role, a repeatability model (REP) proved more efficient than a random regression model (RRM) in predicting PL.
The effect of helmet use on reducing the risk of death in cyclists appears to be distorted by some variables (potential confounders, effect modifiers, or both). Our aim was to provide evidence for or against the hypothesis that cycling area may act as a confounder and effect modifier of the association between helmet use and risk of death of cyclists involved in road crashes. Data were analysed for 24,605 cyclists involved in road crashes in Spain.
View Article and Find Full Text PDFIn dairy, the usual way to measure feed efficiency is through the residual feed intake (RFI) method. However, this method is, in its classical form, a linear regression, which, by construction, does not take into account the evolution of the RFI components across time, inducing approximations in the results. We present here a new approach that incorporates the dynamic dimension of the data.
View Article and Find Full Text PDFIn dairy cattle, selecting for lower methane-emitting animals is one of the new challenges of this decade. However, genetic selection requires a large number of animals with records to get accurate estimated breeding values (EBV). Given that CH records are scarce, the use of information on routinely recorded and highly correlated traits with CH has been suggested to increase the accuracy of genomic EBV (GEBV) through multitrait (genomic) prediction.
View Article and Find Full Text PDFArticle Synopsis
- * Two groups were created: a training population from 2008 to 2013 and a validation population from 2014, using a single-trait animal model for heritability estimates.
- * Three genomic prediction methods were applied, showing prediction accuracies ranging from 0.23 to 0.73, with better accuracy for meat color and tenderness than for fat content, and only minor differences between the methods used.