Predicting hybrid performance in rice using genomic best linear unbiased prediction

Proceedings of the National Academy of Sciences of the United States of America

Volumn 111, Issue 34, 2014, Pages 12456-12461

  Xu, Shizhong ^a   Zhu, Dan ^b   Zhang, Qifa ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b HUAZHONG AGRICULTURAL UNIVERSITY   (China)

Author keywords

Hybrid rice; IMF2; Mixed model; Restricted maximum likelihood; Variance component analysis

Indexed keywords

ALACHLOR; ALGORITHM; ARTICLE; BAYES B; CROSS BREEDING; EPISTASIS; GBLUP; GENETIC VARIABILITY; GENOMIC BEST LINEAR UNBIASED PREDICTION; HERITABILITY; MAXIMUM LIKELIHOOD METHOD; MODEL; PRIORITY JOURNAL; QUANTITATIVE TRAIT; RICE; SIMULATION; BIOLOGICAL MODEL; BREEDING; COMPUTER SIMULATION; GENETIC SELECTION; GENETICS; HYBRIDIZATION; PLANT GENOME; QUANTITATIVE TRAIT LOCUS; STATISTICAL MODEL;

BREEDING; COMPUTER SIMULATION; CROSSES, GENETIC; EPISTASIS, GENETIC; GENOME, PLANT; HYBRIDIZATION, GENETIC; LIKELIHOOD FUNCTIONS; LINEAR MODELS; MODELS, GENETIC; ORYZA SATIVA; QUANTITATIVE TRAIT LOCI; SELECTION, GENETIC;

EID: 84906663723     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1413750111     Document Type: Article

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