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Genome‑wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm 

Gowda, M.; Das, B.; Makumbi, D.; Babu, R.; Semagn, K.; Mahuku, G.; Olsen, M.S.; Bright, J.M.; Beyene, Y.; Prasanna, B.M. (Springer, 2015)
The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. ...
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Genomic prediction models for count data 

Montesinos-López, O.A.; Montesinos-López, A.; Pérez-Rodríguez, P.; Eskridge, K.; Xinyao He; Juliana, P.; Singh, P.; Crossa, J. (Springer Verlag; American Statistical Association; International Biometrics Society, 2015)
Whole genome prediction models are useful tools for breeders when selecting candidate individuals early in life for rapid genetic gains. However, most prediction models developed so far assume that the response variable ...

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Author
Babu, R. (1)Beyene, Y. (1)Boddupalli, Prasanna (1)Crossa, J. (1)Das, Biswanath (1)Eskridge, K. (1)Gowda, Manje (1)He, Xinyao (1)Juliana, P. (1)Jumbo, MacDonald (1)... View More
Date Issued
2015 (2)
Type
Article (2)
Agrovoc
FORECASTING (2)MATHEMATICAL MODELS (2)BAYESIAN THEORY (1)CHROMOSOME MAPPING (1)DATA ANALYSIS (1)GENOMIC FEATURES (1)GENOTYPES (1)MARKER-ASSISTED SELECTION (1)QUANTITATIVE TRAIT LOCI (1)... View More
Keywords
Genomic Prediction (2)
Association Mapping (1)Bayesian Analysis (1)Best Linear Unbiased Prediction (1)Count Data (1)Data Augmentation (1)Genomic Selection (1)Gibbs Sampler (1)Quantitative Trait Locus (1)... View More


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