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The relative efficiency of two multistage linear phenotypic selection indices to predict the net genetic merit

Author: Ceron-Rojas, J.J.
Author: Toledo, F.H.
Author: Crossa, J.
Year: 2019
ISSN: 0011-183X
Abstract: Multistage linear phenotypic selection indices predict the individual net genetic merit at different individual ages or stages and are cost-saving strategies for improving several traits. In a two-stage context, we compared the relative efficiency of the optimum multistage linear phenotypic selection index (OMLPSI) and the decorrelated multistage linear phenotypic selection index (DMLPSI) theory to predict the individual net genetic merit and selection response using a real and a simulated dataset. In addition, we described a method for obtaining the OMLPSI selection intensity in a two-stage context. The criteria used to compare the relative efficiency of both indices were that the total selection response of each index must be lower than or equal to the single-stage linear phenotypic selection index (LPSI) selection response, similar to the accuracy of each index to predict the net genetic merit. Using four different total proportions (p = 0.05, 0.10, 0.20, and 0.30) for the real dataset, the total DMLPSI selection response was 22.80% higher than the estimated single-stage LPSI selection response, whereas the total OMLPSI selection response was only 2.21% higher than the estimated single-stage LPSI selection response. In addition, at Stage 2, OMLPSI accuracy was 62.24% higher than the DMLPSI accuracy for predicting the net genetic merit. We found similar results for the simulated data. Thus, we recommend using OMLPSI when performing the multistage phenotypic selection.
Format: PDF
Language: English
Publisher: Crop Science Society of America (CSSA)
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Type: Article
Place of Publication: Madison (USA)
Pages: 1037-1051
Issue: 3
Volume: 59
DOI: 10.2135/cropsci2018.11.0678
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Journal: Crop Science

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  • Genetic Resources
    Genetic Resources including germplasm collections, wild relatives, genotyping, genomics, and IP

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