Accuracies of univariate and multivariate genomic prediction models in African cassava
Abstract Background Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suita...
Main Authors: | Uche Godfrey Okeke, Deniz Akdemir, Ismail Rabbi, Peter Kulakow, Jean-Luc Jannink |
---|---|
Format: | Article |
Language: | deu |
Published: |
BMC
2017-12-01
|
Series: | Genetics Selection Evolution |
Online Access: | http://link.springer.com/article/10.1186/s12711-017-0361-y |
Similar Items
-
Regional Heritability Mapping Provides Insights into Dry Matter Content in African White and Yellow Cassava Populations
by: Uche Godfrey Okeke, et al.
Published: (2018-03-01) -
Improving Genomic Prediction in Cassava Field Experiments by Accounting for Interplot Competition
by: Ani A. Elias, et al.
Published: (2018-03-01) -
Improving Genomic Prediction in Cassava Field Experiments Using Spatial Analysis
by: Ani A. Elias, et al.
Published: (2018-01-01) -
Prospects for Genomic Selection in Cassava Breeding
by: Marnin D. Wolfe, et al.
Published: (2017-11-01) -
Marker-Based Estimates Reveal Significant Nonadditive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties
by: Marnin D. Wolfe, et al.
Published: (2016-11-01)