Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

Theoretical and Applied Genetics

Volumn 132, Issue 1, 2019, Pages 177-194

  Juliana, Philomin ^a   Montesinos López, Osval A ^b   Crossa, José ^a   Mondal, Suchismita ^a   González Pérez, Lorena ^a   Poland, Jesse ^c   Huerta Espino, Julio ^e   Crespo Herrera, Leonardo ^a   Govindan, Velu ^a   Dreisigacker, Susanne ^a   Shrestha, Sandesh ^c   Pérez Rodríguez, Paulino ^d   Pinto Espinosa, Francisco ^a   Singh, Ravi P ^a  

^a INTERNATIONAL MAIZE AND WHEAT IMPROVEMENT CENTER CIMMYT   (Mexico)

^b UNIVERSIDAD DE COLIMA   (Mexico)

^c KANSAS STATE UNIVERSITY   (United States)

^d Colegio de Postgraduados ^*  (Mexico)

^e INSTITUTO NACIONAL DE INVESTIGACIONES FORESTALES   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATIVE FILTERING; GENES; THROUGHPUT;

CROSS VALIDATION; GENETIC RELATEDNESS; GENOMIC PREDICTIONS; GREEN NORMALIZED DIFFERENCE VEGETATION INDEX; HIGH-THROUGHPUT PHENOTYPING; ITEM-BASED COLLABORATIVE FILTERING; PREDICTION ACCURACY; WHEAT VARIETIES;

FORECASTING;

BIOLOGICAL MODEL; CLIMATE; FOOD GRAIN; GENETICS; GENOMICS; GENOTYPE; HIGH THROUGHPUT SCREENING; PEDIGREE; PHENOTYPE; PLANT BREEDING; PLANT GENOME; PROCEDURES; QUANTITATIVE TRAIT; STATISTICAL MODEL; WHEAT;

CLIMATE; EDIBLE GRAIN; GENOME, PLANT; GENOMICS; GENOTYPE; HIGH-THROUGHPUT SCREENING ASSAYS; LINEAR MODELS; MODELS, GENETIC; PEDIGREE; PHENOTYPE; PLANT BREEDING; QUANTITATIVE TRAIT, HERITABLE; TRITICUM;

EID: 85055485684     PISSN: 00405752     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00122-018-3206-3     Document Type: Article

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