rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Genetic Data Analysis for Plant and Animal Breeding
  name:
    name part: Isik, Fikret.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Holland, James.
    role:
      role term: author.
  name:
    name part: Maltecca, Christian.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 400 p. 360 illus., 241 illus. in color. online resource.
  abstract: This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses.
  table of contents: Introduction to ASReml Software -- Linear Mixed Models-A Short Review -- Covariance Structures -- Breeding Values (Additive) -- Non-additive Genetic Effects -- Multivariate Models -- Spatial Analysis -- Multi-Environment Trials -- Exploratory Marker Data Analysis -- Imputing Missing Genotypes -- Marker-Trait Association -- Genomic Relationships and GBLUP -- Genomic Selection.
  note: by Fikret Isik, James Holland, Christian Maltecca.
  subject:
    topic: Life sciences
  subject:
    topic: Agriculture
  subject:
    topic: Biostatistics
  subject:
    topic: Plant breeding
  subject:
    topic: Animal genetics
  subject:
    topic: Life Sciences
  subject:
    topic: Biostatistics
  subject:
    topic: Plant Breeding/Biotechnology
  subject:
    topic: Plant Genetics and Genomics
  subject:
    topic: Agriculture
  subject:
    topic: Animal Genetics and Genomics
  classification: QH323.5
  classification: 570.15195
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319551777
  identifier: http://dx.doi.org/10.1007/978-3-319-55177-7
  record info:
    record creation date: 170909
    record change date: 20170909142630.0
    record identifier: 978-3-319-55177-7