Duan L - Search Results

1

Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton.

Li B, Chen L, Sun W, Wu D, Wang M, Yu Y, Chen G, Yang W, Lin Z, Zhang X, Duan L, Yang X. Li B, et al. Among authors: duan l. Plant Biotechnol J. 2020 Dec;18(12):2533-2544. doi: 10.1111/pbi.13431. Epub 2020 Jul 8. Plant Biotechnol J. 2020. PMID: 32558152 Free PMC article.

2

High-throughput measurement of rice tillers using a conveyor equipped with x-ray computed tomography.

Yang W, Xu X, Duan L, Luo Q, Chen S, Zeng S, Liu Q. Yang W, et al. Among authors: duan l. Rev Sci Instrum. 2011 Feb;82(2):025102. doi: 10.1063/1.3531980. Rev Sci Instrum. 2011. PMID: 21361628

3

A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice.

Duan L, Yang W, Huang C, Liu Q. Duan L, et al. Plant Methods. 2011 Dec 12;7:44. doi: 10.1186/1746-4811-7-44. Plant Methods. 2011. PMID: 22152096 Free PMC article.

4

Plant phenomics and high-throughput phenotyping: accelerating rice functional genomics using multidisciplinary technologies.

Yang W, Duan L, Chen G, Xiong L, Liu Q. Yang W, et al. Among authors: duan l. Curr Opin Plant Biol. 2013 May;16(2):180-7. doi: 10.1016/j.pbi.2013.03.005. Epub 2013 Apr 8. Curr Opin Plant Biol. 2013. PMID: 23578473 Review.

5

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice.

Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X, Wang G, Luo Q, Zhang Q, Liu Q, Xiong L. Yang W, et al. Among authors: duan l. Nat Commun. 2014 Oct 8;5:5087. doi: 10.1038/ncomms6087. Nat Commun. 2014. PMID: 25295980 Free PMC article.

6

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

Zhang X, Huang C, Wu D, Qiao F, Li W, Duan L, Wang K, Xiao Y, Chen G, Liu Q, Xiong L, Yang W, Yan J. Zhang X, et al. Among authors: duan l. Plant Physiol. 2017 Mar;173(3):1554-1564. doi: 10.1104/pp.16.01516. Epub 2017 Jan 30. Plant Physiol. 2017. PMID: 28153923 Free PMC article.

7

Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization.

Xiong X, Duan L, Liu L, Tu H, Yang P, Wu D, Chen G, Xiong L, Yang W, Liu Q. Xiong X, et al. Among authors: duan l. Plant Methods. 2017 Nov 28;13:104. doi: 10.1186/s13007-017-0254-7. eCollection 2017. Plant Methods. 2017. PMID: 29209408 Free PMC article.

8

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions.

Duan L, Han J, Guo Z, Tu H, Yang P, Zhang D, Fan Y, Chen G, Xiong L, Dai M, Williams K, Corke F, Doonan JH, Yang W. Duan L, et al. Front Plant Sci. 2018 Apr 17;9:492. doi: 10.3389/fpls.2018.00492. eCollection 2018. Front Plant Sci. 2018. PMID: 29719548 Free PMC article.

9

A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits.

Wu D, Wu D, Feng H, Duan L, Dai G, Liu X, Wang K, Yang P, Chen G, Gay AP, Doonan JH, Niu Z, Xiong L, Yang W. Wu D, et al. Among authors: duan l. Plant Commun. 2021 Jan 29;2(2):100165. doi: 10.1016/j.xplc.2021.100165. eCollection 2021 Mar 8. Plant Commun. 2021. PMID: 33898978 Free PMC article.

10

An Intelligent Rice Yield Trait Evaluation System Based on Threshed Panicle Compensation.

Huang C, Li W, Zhang Z, Hua X, Yang J, Ye J, Duan L, Liang X, Yang W. Huang C, et al. Among authors: duan l. Front Plant Sci. 2022 Jul 22;13:900408. doi: 10.3389/fpls.2022.900408. eCollection 2022. Front Plant Sci. 2022. PMID: 35937323 Free PMC article.

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