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oapen-20.500.12657-229342024-03-22T19:23:34Z Linear Selection Indices in Modern Plant Breeding Céron-Rojas, J. Jesus Crossa, José Life sciences Biostatistics Plant breeding Animal genetics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSV Zoology and animal sciences 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. 2020-03-18 13:36:15 2020-04-01T08:56:57Z 2020-04-01T08:56:57Z 2018 book 1007227 http://library.oapen.org/handle/20.500.12657/22934 eng application/pdf n/a 1007227.pdf https://www.springer.com/9783319912233 Springer Nature 10.1007/978-3-319-91223-3 10.1007/978-3-319-91223-3 6c6992af-b843-4f46-859c-f6e9998e40d5 256 Cham open access
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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.
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