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818 related items for PubMed ID: 26058362

  • 1. Comprehensive phenotypic analysis and quantitative trait locus identification for grain mineral concentration, content, and yield in maize (Zea mays L.).
    Gu R, Chen F, Liu B, Wang X, Liu J, Li P, Pan Q, Pace J, Soomro AA, Lübberstedt T, Mi G, Yuan L.
    Theor Appl Genet; 2015 Sep; 128(9):1777-89. PubMed ID: 26058362
    [Abstract] [Full Text] [Related]

  • 2. Stability Performance of Inductively Coupled Plasma Mass Spectrometry-Phenotyped Kernel Minerals Concentration and Grain Yield in Maize in Different Agro-Climatic Zones.
    Mallikarjuna MG, Thirunavukkarasu N, Hossain F, Bhat JS, Jha SK, Rathore A, Agrawal PK, Pattanayak A, Reddy SS, Gularia SK, Singh AM, Manjaiah KM, Gupta HS.
    PLoS One; 2015 Sep; 10(9):e0139067. PubMed ID: 26406470
    [Abstract] [Full Text] [Related]

  • 3. Identification of QTL for maize grain yield and kernel-related traits.
    Yang C, Zhang L, Jia A, Rong T.
    J Genet; 2016 Jun; 95(2):239-47. PubMed ID: 27350665
    [Abstract] [Full Text] [Related]

  • 4. Quantitative trait loci for biofortification traits in maize grain.
    Simić D, Mladenović Drinić S, Zdunić Z, Jambrović A, Ledencan T, Brkić J, Brkić A, Brkić I.
    J Hered; 2012 Jun; 103(1):47-54. PubMed ID: 22071312
    [Abstract] [Full Text] [Related]

  • 5. Identification and validation of genomic regions influencing kernel zinc and iron in maize.
    Hindu V, Palacios-Rojas N, Babu R, Suwarno WB, Rashid Z, Usha R, Saykhedkar GR, Nair SK.
    Theor Appl Genet; 2018 Jul; 131(7):1443-1457. PubMed ID: 29574570
    [Abstract] [Full Text] [Related]

  • 6. Verification of QTL for grain starch content and its genetic correlation with oil content using two connected RIL populations in high-oil maize.
    Yang G, Dong Y, Li Y, Wang Q, Shi Q, Zhou Q.
    PLoS One; 2013 Jul; 8(1):e53770. PubMed ID: 23320103
    [Abstract] [Full Text] [Related]

  • 7. Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.).
    Yi Q, Liu Y, Hou X, Zhang X, Li H, Zhang J, Liu H, Hu Y, Yu G, Li Y, Wang Y, Huang Y.
    BMC Plant Biol; 2019 Sep 09; 19(1):392. PubMed ID: 31500559
    [Abstract] [Full Text] [Related]

  • 8. Genetic analysis of seedling root traits reveals the association of root trait with other agronomic traits in maize.
    Ju C, Zhang W, Liu Y, Gao Y, Wang X, Yan J, Yang X, Li J.
    BMC Plant Biol; 2018 Aug 15; 18(1):171. PubMed ID: 30111287
    [Abstract] [Full Text] [Related]

  • 9. Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.
    Zhang Z, Wu X, Shi C, Wang R, Li S, Wang Z, Liu Z, Xue Y, Tang G, Tang J.
    Mol Genet Genomics; 2016 Feb 15; 291(1):437-54. PubMed ID: 26420507
    [Abstract] [Full Text] [Related]

  • 10. Mapping of quantitative trait Loci for grain iron and zinc concentration in diploid A genome wheat.
    Tiwari VK, Rawat N, Chhuneja P, Neelam K, Aggarwal R, Randhawa GS, Dhaliwal HS, Keller B, Singh K.
    J Hered; 2009 Feb 15; 100(6):771-6. PubMed ID: 19520762
    [Abstract] [Full Text] [Related]

  • 11. Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping.
    Zhang C, Zhou Z, Yong H, Zhang X, Hao Z, Zhang F, Li M, Zhang D, Li X, Wang Z, Weng J.
    Theor Appl Genet; 2017 May 15; 130(5):1011-1029. PubMed ID: 28215025
    [Abstract] [Full Text] [Related]

  • 12. Identification of genomic region(s) responsible for high iron and zinc content in rice.
    Dixit S, Singh UM, Abbai R, Ram T, Singh VK, Paul A, Virk PS, Kumar A.
    Sci Rep; 2019 May 31; 9(1):8136. PubMed ID: 31148549
    [Abstract] [Full Text] [Related]

  • 13. Genetic dissection of maize plant architecture with an ultra-high density bin map based on recombinant inbred lines.
    Zhou Z, Zhang C, Zhou Y, Hao Z, Wang Z, Zeng X, Di H, Li M, Zhang D, Yong H, Zhang S, Weng J, Li X.
    BMC Genomics; 2016 Mar 03; 17():178. PubMed ID: 26940065
    [Abstract] [Full Text] [Related]

  • 14. A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments.
    Zhang X, Guan Z, Li Z, Liu P, Ma L, Zhang Y, Pan L, He S, Zhang Y, Li P, Ge F, Zou C, He Y, Gao S, Pan G, Shen Y.
    Theor Appl Genet; 2020 Oct 03; 133(10):2881-2895. PubMed ID: 32594266
    [Abstract] [Full Text] [Related]

  • 15. Mapping of QTL for Grain Yield Components Based on a DH Population in Maize.
    Yang J, Liu Z, Chen Q, Qu Y, Tang J, Lübberstedt T, Li H.
    Sci Rep; 2020 Apr 27; 10(1):7086. PubMed ID: 32341398
    [Abstract] [Full Text] [Related]

  • 16. Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize.
    Peng B, Li Y, Wang Y, Liu C, Liu Z, Zhang Y, Tan W, Wang D, Shi Y, Sun B, Song Y, Wang T, Li Y.
    Theor Appl Genet; 2013 Mar 27; 126(3):773-89. PubMed ID: 23183923
    [Abstract] [Full Text] [Related]

  • 17. Characterization of a major QTL for manganese accumulation in rice grain.
    Liu C, Chen G, Li Y, Peng Y, Zhang A, Hong K, Jiang H, Ruan B, Zhang B, Yang S, Gao Z, Qian Q.
    Sci Rep; 2017 Dec 18; 7(1):17704. PubMed ID: 29255144
    [Abstract] [Full Text] [Related]

  • 18. Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 × SK maize population.
    Raihan MS, Liu J, Huang J, Guo H, Pan Q, Yan J.
    Theor Appl Genet; 2016 Aug 18; 129(8):1465-77. PubMed ID: 27154588
    [Abstract] [Full Text] [Related]

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