2018
DOI: 10.1007/978-3-319-91223-3
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Linear Selection Indices in Modern Plant Breeding

Abstract: distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons license and your intended use is not permitted by statutory regulation… Show more

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Cited by 44 publications
(62 citation statements)
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“…. ., α t ] a vector of known and fixed economic weights [19]. Under the breeding perspective, economic values are used to reflect the relative importance of the traits of interest.…”
Section: Construction Of Genomic Selection Indicesmentioning
confidence: 99%
See 3 more Smart Citations
“…. ., α t ] a vector of known and fixed economic weights [19]. Under the breeding perspective, economic values are used to reflect the relative importance of the traits of interest.…”
Section: Construction Of Genomic Selection Indicesmentioning
confidence: 99%
“…Most of genomic selection algorithms implemented thus far were based on the analysis of single traits, while selection index has had limited use in actual plant breeding programs [18][19][20]. Nonetheless, available results indicate that selection index for improving a single trait would not outperform direct selection for the trait itself, whereas selecting simultaneously for more than one trait in selection index might outperform selecting for a single trait [20].…”
Section: Introductionmentioning
confidence: 99%
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“…Selection indices represent a practical breeding strategy to account for these relationships between traits. Selection indices are linear combinations of traits that allow for selection on multiple traits simultaneously on the basis of a single value (reviewed by Céron-Rojas & Crossa, 2018). They are derived using the genetic and phenotypic correlations between traits in conjunction with weights assigned to each trait according to its importance.…”
Section: Introductionmentioning
confidence: 99%