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Journal Abstract Search

298 related items for PubMed ID: 25114224

  • 1. Predicting hybrid performance in rice using genomic best linear unbiased prediction.
    Xu S, Zhu D, Zhang Q.
    Proc Natl Acad Sci U S A; 2014 Aug 26; 111(34):12456-61. PubMed ID: 25114224
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  • 2. Hybrid breeding of rice via genomic selection.
    Cui Y, Li R, Li G, Zhang F, Zhu T, Zhang Q, Ali J, Li Z, Xu S.
    Plant Biotechnol J; 2020 Jan 26; 18(1):57-67. PubMed ID: 31124256
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  • 3. Metabolomic prediction of yield in hybrid rice.
    Xu S, Xu Y, Gong L, Zhang Q.
    Plant J; 2016 Oct 26; 88(2):219-227. PubMed ID: 27311694
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  • 4. Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.
    Spindel J, Begum H, Akdemir D, Virk P, Collard B, Redoña E, Atlin G, Jannink JL, McCouch SR.
    PLoS Genet; 2015 Feb 26; 11(2):e1004982. PubMed ID: 25689273
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  • 5. Multi-omics-based prediction of hybrid performance in canola.
    Knoch D, Werner CR, Meyer RC, Riewe D, Abbadi A, Lücke S, Snowdon RJ, Altmann T.
    Theor Appl Genet; 2021 Apr 26; 134(4):1147-1165. PubMed ID: 33523261
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  • 10. Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids.
    Liang Z, Gupta SK, Yeh CT, Zhang Y, Ngu DW, Kumar R, Patil HT, Mungra KD, Yadav DV, Rathore A, Srivastava RK, Gupta R, Yang J, Varshney RK, Schnable PS, Schnable JC.
    G3 (Bethesda); 2018 Jul 02; 8(7):2513-2522. PubMed ID: 29794163
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  • 11. Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.
    Schrag TA, Westhues M, Schipprack W, Seifert F, Thiemann A, Scholten S, Melchinger AE.
    Genetics; 2018 Apr 02; 208(4):1373-1385. PubMed ID: 29363551
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  • 12. Genomic Prediction of Yield Traits in Single-Cross Hybrid Rice (Oryza sativa L.).
    Labroo MR, Ali J, Aslam MU, de Asis EJ, Dela Paz MA, Sevilla MA, Lipka AE, Studer AJ, Rutkoski JE.
    Front Genet; 2021 Apr 02; 12():692870. PubMed ID: 34276796
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  • 14. Metabolic prediction of important agronomic traits in hybrid rice (Oryza sativa L.).
    Dan Z, Hu J, Zhou W, Yao G, Zhu R, Zhu Y, Huang W.
    Sci Rep; 2016 Feb 24; 6():21732. PubMed ID: 26907211
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  • 15. Progress in research and development on hybrid rice: a super-domesticate in China.
    Cheng SH, Zhuang JY, Fan YY, Du JH, Cao LY.
    Ann Bot; 2007 Nov 24; 100(5):959-66. PubMed ID: 17704538
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  • 16. Identification of optimal prediction models using multi-omic data for selecting hybrid rice.
    Wang S, Wei J, Li R, Qu H, Chater JM, Ma R, Li Y, Xie W, Jia Z.
    Heredity (Edinb); 2019 Sep 24; 123(3):395-406. PubMed ID: 30911139
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  • 17. Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance.
    Fritsche-Neto R, Ali J, De Asis EJ, Allahgholipour M, Labroo MR.
    Theor Appl Genet; 2023 Dec 12; 137(1):3. PubMed ID: 38085288
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  • 19. Revisiting hybrid breeding designs using genomic predictions: simulations highlight the superiority of incomplete factorials between segregating families over topcross designs.
    Seye AI, Bauland C, Charcosset A, Moreau L.
    Theor Appl Genet; 2020 Jun 12; 133(6):1995-2010. PubMed ID: 32185420
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  • 20. Genomic prediction of rice mesocotyl length indicative of directing seeding suitability using a half-sib hybrid population.
    Chen L, Liu J, He S, Cao L, Ye G.
    PLoS One; 2023 Jun 12; 18(4):e0283989. PubMed ID: 37018326
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