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Article
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Genomic resources in plant breeding for sustainable agriculture 

Thudi, M.; Palakurthi, R.; Schnable, J.C.; Annapurna Chitikineni; Dreisigacker, S.; Mace, E.; Rakesh Kumar Srivastava; Satyavathi, C.T.; Odeny, D.A.; Vijay Tiwari; Hon-Ming Lam; Yan-Bin Hong; Singh, V.K.; Guowei Li; Yunbi Xu; Xiao-Ping Chen; Kaila, S.; Nguyen, H.T.; Sivasankar, S.; Jackson, S.A.; Close, T.J.; Wan Shubo; Varshney, R.K. (Elsevier, 2021)
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A zero altered Poisson random forest model for genomic-enabled prediction 

Montesinos-Lopez, O.A.; Montesinos-López, A.; Mosqueda-Gonzalez, B.A.; Montesinos-Lopez, J.C.; Crossa, J.; Lozano-Ramirez, N.; Singh, P.K.; Valladares-Anguiano, F.A. (Genetics Society of America, 2021)
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Genomic selection for grain yield in the CIMMYT Wheat Breeding Program—status and perspectives 

Juliana, P.; Singh, R.P.; Braun, H.J.; Huerta-Espino, J.; Crespo-Herrera, L.A.; Velu, G.; Mondal, S.; Poland, J.A.; Shrestha, S. (Frontiers, 2020)
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Origin specific genomic selection: a simple process to optimize the favorable contribution of parents to progeny 

Chin Jian Yang; Sharma, R.; Gorjanc, G.; Hearne, S.; Powell, W.; Mackay, I. (Genetics Society of America, 2020)
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A review of deep learning applications for genomic selection 

Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Perez-Rodriguez, P.; Barrón-López, A.; Martini, J.W.R.; Fajardo-Flores, S.B.; Gaytan-Lugo, L.S.; Santana-Mancilla, P.C.; Crossa, J. (BioMed Central, 2021)
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Wheat quality improvement at CIMMYT and the use of genomic selection on it 

Guzman, C.; Peña, R.; Singh, R.G.; Autrique, E.; Dreisigacker, S.; Crossa, J.; Rutkoski, J.; Poland, J.; Battenfield, S. (Elsevier, 2016)
The International Center for Maize and Wheat Improvement (CIMMYT) leads the Global Wheat Program, whose main objective is to increase the productivity of wheat cropping systems to reduce poverty in developing countries. ...
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Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations 

Gorjanc, G.; Jenko, J.; Hearne, S.; Hickey, J.M. (BioMed Central, 2016)
Background: The limited genetic diversity of elite maize germplasms raises concerns about the potential to breed for new challenges. Initiatives have been formed over the years to identify and utilize useful diversity from ...
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A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding 

Montesinos-Lopez, O.A.; Martin-Vallejo, J.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Montesinos-Lopez, A.; Juliana, P.; Singh, R.P. (Genetics Society of America, 2019)
Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...
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High-throughput phenotyping enabled genetic dissection of crop lodging in wheat 

Singh, D.; Xu Wang; Kumar, U.; Liangliang Gao; Muhammad Noor; Imtiaz, M.; Singh, R.P.; Poland, J.A. (Frontiers, 2019)
Novel high-throughput phenotyping (HTP) approaches are needed to advance the understanding of genotype-to-phenotype and accelerate plant breeding. The first generation of HTP has examined simple spectral reflectance traits ...
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New deep learning genomic-based prediction model for multiple traits with binary, ordinal, and continuous phenotypes 

Montesinos-Lopez, O.A.; Martin-Vallejo, J.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Montesinos-López, A.; Juliana, P.; Singh, R.P. (Genetics Society of America, 2019)
Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between ...

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Author
Crossa, J. (5)Montesinos-Lopez, Osval Antonio (4)Singh, R.P. (4)Juliana, P. (3)Poland, Jesse (3)Dreisigacker, S. (2)Gianola, D. (2)Gorjanc, Gregor (2)Hearne, Sarah (2)Martin Vallejo, Francisco Javier (2)... View More
Date Issued
2021 (3)2020 (2)2019 (3)2016 (2)
Type
Article (10)
Agrovoc
PLANT BREEDING (10)
GENOMICS (5)MARKER-ASSISTED SELECTION (5)MAIZE (3)WHEAT (3)ARTIFICIAL SELECTION (2)PHENOTYPES (2)AERIAL SURVEYING (1)ARTIFICIAL INTELLIGENCE (1)BARLEY (1)... View More
Keywords
Genomic Selection (10)
Genomic Prediction (4)GenPred (4)Deep Learning (3)Shared Data Resources (3)Wheat Breeding (2)Climate Resilience (1)Count Data (1)Diversity (1)Genomic Breeding (1)... View More


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