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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.
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.
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