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Published with open access
Explains how various types of linear selection indices can be constructed, interpreted, optimized and applied
Invaluable resource for plant and animal breeders
Written by leading experts
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Table of contents (11 chapters)
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Front Matter
About this book
This open access book focuses on the linear selection index (LSI) theory and its statistical properties. It addresses the single-stage LSI theory by assuming that economic weights are fixed and known - or fixed, but unknown - to predict the net genetic merit in the phenotypic, marker and genomic context. Further, it shows how to combine the LSI theory with the independent culling method to develop the multistage selection index theory. The final two chapters present simulation results and SAS and R codes, respectively, to estimate the parameters and make selections using some of the LSIs described. It is essential reading for plant quantitative geneticists, but is also a valuable resource for animal breeders.
Keywords
- quantitative traits
- genomic selection
- selection index theory
- marker-assisted selection
- linear selection index
- best linear unbiased predictor
- phenotypic selection
- multitrait selection
- genomic tools
- Open Access
- LSI
- BLUP
Authors and Affiliations
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Biometrics and Statistics Unit, International Maize and Wheat, Improvement Center (CIMMYT), Mexico, Mexico
J. Jesus Céron-Rojas, José Crossa
About the authors
Bibliographic Information
Book Title: Linear Selection Indices in Modern Plant Breeding
Authors: J. Jesus Céron-Rojas, José Crossa
DOI: https://doi.org/10.1007/978-3-319-91223-3
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2018
License: CC BY
Hardcover ISBN: 978-3-319-91222-6Published: 11 October 2018
Softcover ISBN: 978-3-030-08202-4Published: 22 December 2018
eBook ISBN: 978-3-319-91223-3Published: 26 September 2018
Edition Number: 1
Number of Pages: XXII, 256
Number of Illustrations: 45 illustrations in colour
Topics: Biostatistics, Plant Biotechnology, Genetics and Genomics