Advances in Statistical Methods for Genetic Improvement of Livestock

  • Daniel Gianola
  • Keith Hammond

Part of the Advanced Series in Agricultural Sciences book series (AGRICULTURAL, volume 18)

Table of contents

  1. Front Matter
    Pages i-xx
  2. General

    1. Front Matter
      Pages 1-1
    2. D. Gianola, S. Im, R. L. Fernando, J. L. Foulley
      Pages 15-40
    3. Back Matter
      Pages 56-57
  3. Design of Experiments and Breeding Programs

  4. Estimation of Genetic Parameters

    1. Front Matter
      Pages 135-135
    2. Back Matter
      Pages 207-208
  5. Prediction and Estimation of Genetic Merit

    1. Front Matter
      Pages 209-209
    2. D. Gianola, S. Im, F. W. Macedo
      Pages 210-238

About this book


Developments in statistics and computing as well as their application to genetic improvement of livestock gained momentum over the last 20 years. This text reviews and consolidates the statistical foundations of animal breeding. This text will prove useful as a reference source to animal breeders, quantitative geneticists and statisticians working in these areas. It will also serve as a text in graduate courses in animal breeding methodology with prerequisite courses in linear models, statistical inference and quantitative genetics.


Generalized linear model Likelihood genetics growth statistical inference statistics

Editors and affiliations

  • Daniel Gianola
    • 1
  • Keith Hammond
    • 2
  1. 1.Department of Animal Sciences 126 Animal Sciences LaboratoryUniversity of IllinoisUrbanaUSA
  2. 2.Animal Genetics and Breeding Unit (AGBU)University of New England and NSW Agriculture and FisheriesArmidaleAustralia

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1990
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-74489-1
  • Online ISBN 978-3-642-74487-7
  • Series Print ISSN 0172-4207
  • About this book