Linear Models for the Prediction of Animal Breeding Values [OP]

The prediction of producing desirable traits in offspring--such as increased growth rate or superior meat, milk and wool production--is a vital economic tool to the animal scientist. Summarizing the latest developments in genomics relating to animal breeding values and design of breeding programs, this new edition includes models of survival analysis, social interaction and sire and dam models, as well as advancements in the use of SNPs in the computation of genomic breeding values.

Raphael Mrode is Professor of Quantitative Genetics and Genomics at Scotland's Rural College. He has been lecturing at Edinburgh University's Masters course on quantitative genetics and genome analysis since 2005, and has given lectures on mixed linear models and the use of various BLUP models for genetic prediction. His research interests include data modelling and analysis, the incorporation of molecular information in genetic evaluation procedures, the application of innovative approaches for data capture, analysis and feedback and investigating methods for generating alternative and novel phenotypes in small dairy systems in developing countries.