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Genomic selection for grain yield and quality traits in durum wheat
Jemanesh K. Haile
, Amidou N’Diaye
, Fran Clarke
, John Clarke
, Ron Knox
,
Jessica Rutkoski
, Filippo M. Bassi
, Curtis J. Pozniak
Research output
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peer-review
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Dive into the research topics of 'Genomic selection for grain yield and quality traits in durum wheat'. Together they form a unique fingerprint.
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Keyphrases
Genomic Selection
100%
Grain Yield
100%
Quality Traits
100%
Grain Quality
100%
Yield Attributes
100%
Durum Wheat
100%
Single Trait
100%
Multi-trait
83%
GS Model
66%
Prediction Accuracy
50%
Doubled Haploid
50%
BayesA
50%
Predicted Yield
33%
BayesB
33%
Genomic Best Linear Unbiased Prediction (GBLUP)
33%
Gluten Index
33%
Gluten Strength
33%
RR-BLUP
33%
Yield Strength
16%
Computational Model
16%
Statistical Model
16%
Training Set
16%
Protein Content
16%
Prediction Approach
16%
Trait Value
16%
Genetic Architecture
16%
Bayesian Lasso
16%
Trait Matrix
16%
Genomic Prediction Models
16%
Infinium
16%
Tenacity
16%
Variety Breeding
16%
90K SNP Array
16%
Multi-trait Prediction
16%
Economic Selection Index
16%
Alveograph
16%
Advanced Breeding Lines
16%
Multi-trait Genomic Prediction
16%
Trait Prediction
16%
Agricultural and Biological Sciences
Grains
100%
Marker-Assisted Selection
100%
Doubled Haploids
100%
Durum Wheat
100%
Single Nucleotide Polymorphism
33%
Mathematical Model
33%
Breeding Line
33%
Index Selection
33%
Biochemistry, Genetics and Molecular Biology
Marker-Assisted Selection
100%
Single Nucleotide Polymorphism
50%
Protein Content
50%
Breeding Line
50%
Genetic Architecture
50%
Alpha 1-Antitrypsin
50%
Genomics
50%