Science China Life Sciences, an academic journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, and published by Science China Press, is committed to publishing high-quality, original results in both basic and applied research. Science China Life Sciences is published in both print and electronic forms. It is indexed by Science Citation Index. Categories of articles: Reviews summarize representative results and achievements in a particular topic or an area, comment on the current situation, and advise on the research directions. The author’s own opinion and related discussion is requested. Regular articles report on important original results in all areas of life sciences. Short communications present short reports in a timely manner of the latest important results.
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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