Chapter 32. Theory and practice of phenotypic and genomic selection indices
The plant net genetic merit is a linear combination of trait breeding values weighted by its respective economic weights whereas a linear selection index (LSI) is a linear combination of phenotypic or genomic estimated breeding values (GEBV) which is used to predict the net genetic merit of candidates for selection. Because economic values are difficult to assign, some authors developed economic weight-free LSI. The economic weights LSI are associated with linear regression theory, while the economic weight-free LSI is associated with canonical correlation theory. Both LSI can be unconstrained or constrained. Constrained LSI imposes restrictions on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of the traits change their values without restriction. This work is geared towards plant breeders and researchers interested in LSI theory and practice in the context of wheat breeding. We provide the phenotypic and genomic unconstrained and constrained LSI, which together cover the theoretical and practical cornerstone of the single-stage LSI theory in plant breeding. Our main goal is to offer researchers a starting point for understanding the core tenets of LSI theory in plant selection.
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Format: | Book Chapter biblioteca |
Language: | English |
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Springer Nature
2022
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Subjects: | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Canonical Correlation, WHEAT, BREEDING, PLANT BREEDING, PHENOTYPES, SELECTION RESPONSES, |
Online Access: | https://hdl.handle.net/10883/22207 |
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dig-cimmyt-10883-222072022-10-04T20:37:15Z Chapter 32. Theory and practice of phenotypic and genomic selection indices Crossa, J. Ceron Rojas, J.J. Martini, J.W.R. Covarrubias-Pazaran, G. Alvarado Beltrán, G. Toledo, F.H. Velu, G. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES The plant net genetic merit is a linear combination of trait breeding values weighted by its respective economic weights whereas a linear selection index (LSI) is a linear combination of phenotypic or genomic estimated breeding values (GEBV) which is used to predict the net genetic merit of candidates for selection. Because economic values are difficult to assign, some authors developed economic weight-free LSI. The economic weights LSI are associated with linear regression theory, while the economic weight-free LSI is associated with canonical correlation theory. Both LSI can be unconstrained or constrained. Constrained LSI imposes restrictions on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of the traits change their values without restriction. This work is geared towards plant breeders and researchers interested in LSI theory and practice in the context of wheat breeding. We provide the phenotypic and genomic unconstrained and constrained LSI, which together cover the theoretical and practical cornerstone of the single-stage LSI theory in plant breeding. Our main goal is to offer researchers a starting point for understanding the core tenets of LSI theory in plant selection. 593–616 2022-09-30T00:10:14Z 2022-09-30T00:10:14Z 2022 Book Chapter Published Version 978-3-030-90672-6 978-3-030-90673-3 (Online) https://hdl.handle.net/10883/22207 10.1007/978-3-030-90673-3_32 English CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose Open Access Switzerland Springer Nature 978-3-030-90672-6 |
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AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES |
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AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES Crossa, J. Ceron Rojas, J.J. Martini, J.W.R. Covarrubias-Pazaran, G. Alvarado Beltrán, G. Toledo, F.H. Velu, G. Chapter 32. Theory and practice of phenotypic and genomic selection indices |
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The plant net genetic merit is a linear combination of trait breeding values weighted by its respective economic weights whereas a linear selection index (LSI) is a linear combination of phenotypic or genomic estimated breeding values (GEBV) which is used to predict the net genetic merit of candidates for selection. Because economic values are difficult to assign, some authors developed economic weight-free LSI. The economic weights LSI are associated with linear regression theory, while the economic weight-free LSI is associated with canonical correlation theory. Both LSI can be unconstrained or constrained. Constrained LSI imposes restrictions on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of the traits change their values without restriction. This work is geared towards plant breeders and researchers interested in LSI theory and practice in the context of wheat breeding. We provide the phenotypic and genomic unconstrained and constrained LSI, which together cover the theoretical and practical cornerstone of the single-stage LSI theory in plant breeding. Our main goal is to offer researchers a starting point for understanding the core tenets of LSI theory in plant selection. |
format |
Book Chapter |
topic_facet |
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Canonical Correlation WHEAT BREEDING PLANT BREEDING PHENOTYPES SELECTION RESPONSES |
author |
Crossa, J. Ceron Rojas, J.J. Martini, J.W.R. Covarrubias-Pazaran, G. Alvarado Beltrán, G. Toledo, F.H. Velu, G. |
author_facet |
Crossa, J. Ceron Rojas, J.J. Martini, J.W.R. Covarrubias-Pazaran, G. Alvarado Beltrán, G. Toledo, F.H. Velu, G. |
author_sort |
Crossa, J. |
title |
Chapter 32. Theory and practice of phenotypic and genomic selection indices |
title_short |
Chapter 32. Theory and practice of phenotypic and genomic selection indices |
title_full |
Chapter 32. Theory and practice of phenotypic and genomic selection indices |
title_fullStr |
Chapter 32. Theory and practice of phenotypic and genomic selection indices |
title_full_unstemmed |
Chapter 32. Theory and practice of phenotypic and genomic selection indices |
title_sort |
chapter 32. theory and practice of phenotypic and genomic selection indices |
publisher |
Springer Nature |
publishDate |
2022 |
url |
https://hdl.handle.net/10883/22207 |
work_keys_str_mv |
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