Prospects for Genomic Selection in Cassava Breeding
This study assesses the accuracy of 7 prediction models for 7 traits in 3 prediction scenarios
Abstract
Cassava is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at 3 breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, the authors expand on previous analyses by assessing the accuracy of 7 prediction models for 7 traits in 3 prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. The authors also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm.
This work is part of the “Next Generation Cassava Breeding Project” which is supported by the UK Department for International Development, in partnership with the Bill & Melinda Gates Foundation.
Citation
Marnin Wolfe, Dunia Pino Del Carpio, Olumide Alabi, Lydia Ezenwaka, Ugochukwu Ikeogu, Ismail Kayondo, Roberto Lozano, Uche Okeke, Alfred Ozimati, Esuma Williams, Chiedozie Egesi, Robert Kawuki, Peter Kulakow, Ismail Rabbi, Jean-Luc Jannink Prospects for Genomic Selection in Cassava Breeding. Plant Genome; 28 September 2017 https://doi.org/10.3835/plantgenome2017.03.0015