Linear Selection Indices in Modern Plant Breeding

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 con...

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Bibliographic Details
Main Author: Céron-Rojas, J. Jesus (Author)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing, 2018.
Edition:1st ed. 2018.
Subjects:
ISBN:9783319912233
Online Access: Get full text
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100 1 |a Céron-Rojas, J. Jesus.  |4 aut 
245 1 0 |a Linear Selection Indices in Modern Plant Breeding  |h [electronic resource] /  |c by J. Jesus Céron-Rojas, José Crossa. 
250 |a 1st ed. 2018. 
260 1 |a Cham :  |b Springer International Publishing,  |c 2018. 
300 |a XXII, 256 p. 45 illus. in color.  |b online resource. 
500 |a Biomedical and Life Sciences  
505 0 |a General introduction -- The linear phenotypic selection index theory -- Constrained linear phenotypic selection indices -- Constrained linear phenotypic selection indices -- Linear marker and genomic selection indices -- Linear genomic selection indices -- Constrained linear genomic selection indices -- Linear phenotypic eigen selection index methods -- Linear molecular and genomic eigen selection index methods -- Multistage linear selection indices -- Stochastic simulation of four linear phenotypic selection indices -- RIndSel: Selection indices with R. 
506 0 |a Open Access 
516 |a text file PDF 
520 |a 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. 
650 0 |a Biostatistics. 
650 0 |a Plant breeding. 
650 0 |a Animal genetics. 
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