Fundamental to any livestock improvement program by animal scientists is
the prediction of genetic merit in the offspring generation for
desirable production traits such as increased growth rate, superior
meat, milk, and wool production.
Covering the foundational principles on the application of linear models
for the prediction of genetic merit in livestock, this new edition is
fully updated to incorporate recent advances in genomic prediction
approaches, genomic models for multi-breed and crossbred performance,
dominance, and epistasis. It provides models for the analysis of main
production traits as well as functional traits and includes numerous
worked examples. For the first time, R codes for key examples in the
textbook are provided online.
The book covers:
- The relationship between the genome and the phenotype.
- BLUP models for various livestock data and structure.
- Incorporation of related ancestral parents and metafounders in
prediction models.
- Models for survival analysis and social interaction.
- Advancements in genomic prediction approaches and selection.
- Genomic models for multi-breed and crossbred performance.
- Models for non-additive genetic effects including dominance and
epistasis.
- Estimation of genetic parameters including Gibbs sampling approaches.
- Computation methods for solving linear mixed model equations.
Suitable for graduate and postgraduate students, researchers and
lecturers of animal breeding, genetics and genomics, this established
textbook provides a thorough grounding in both the basics and in new
developments of linear models and animal genetics.
