Improving Genomic Prediction in Cassava Field Experiments by Accounting for Interplot Competition

Autor: Ani A. Elias, Ismail Rabbi, Peter Kulakow, Jean-Luc Jannink
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: G3: Genes, Genomes, Genetics, Vol 8, Iss 3, Pp 933-944 (2018)
Druh dokumentu: article
ISSN: 2160-1836
DOI: 10.1534/g3.117.300354
Popis: Plants competing for available resources is an unavoidable phenomenon in a field. We conducted studies in cassava (Manihot esculenta Crantz) in order to understand the pattern of this competition. Taking into account the competitive ability of genotypes while selecting parents for breeding advancement or commercialization can be very useful. We assumed that competition could occur at two levels: (i) the genotypic level, which we call interclonal, and (ii) the plot level irrespective of the type of genotype, which we call interplot competition or competition error. Modification in incidence matrices was applied in order to relate neighboring genotype/plot to the performance of a target genotype/plot with respect to its competitive ability. This was added into a genomic selection (GS) model to simultaneously predict the direct and competitive ability of a genotype. Predictability of the models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error (pRMSE) compared to that of the base model having no competitive component. Results from our real data studies indicated that
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