Chen G - 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: chen l, chen g. 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

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: chen g. 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.

3

A hyperspectral imaging system for an accurate prediction of the above-ground biomass of individual rice plants.

Feng H, Jiang N, Huang C, Fang W, Yang W, Chen G, Xiong L, Liu Q. Feng H, et al. Among authors: chen g. Rev Sci Instrum. 2013 Sep;84(9):095107. doi: 10.1063/1.4818918. Rev Sci Instrum. 2013. PMID: 24089866

4

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: chen g. Nat Commun. 2014 Oct 8;5:5087. doi: 10.1038/ncomms6087. Nat Commun. 2014. PMID: 25295980 Free PMC article.

5

Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer.

Yang W, Guo Z, Huang C, Wang K, Jiang N, Feng H, Chen G, Liu Q, Xiong L. Yang W, et al. Among authors: chen g. J Exp Bot. 2015 Sep;66(18):5605-15. doi: 10.1093/jxb/erv100. Epub 2015 Mar 20. J Exp Bot. 2015. PMID: 25796084 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: chen g. 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

A high-throughput stereo-imaging system for quantifying rape leaf traits during the seedling stage.

Xiong X, Yu L, Yang W, Liu M, Jiang N, Wu D, Chen G, Xiong L, Liu K, Liu Q. Xiong X, et al. Among authors: chen g. Plant Methods. 2017 Jan 31;13:7. doi: 10.1186/s13007-017-0157-7. eCollection 2017. Plant Methods. 2017. PMID: 28163771 Free PMC article.

8

An integrated hyperspectral imaging and genome-wide association analysis platform provides spectral and genetic insights into the natural variation in rice.

Feng H, Guo Z, Yang W, Huang C, Chen G, Fang W, Xiong X, Zhang H, Wang G, Xiong L, Liu Q. Feng H, et al. Among authors: chen g. Sci Rep. 2017 Jun 30;7(1):4401. doi: 10.1038/s41598-017-04668-8. Sci Rep. 2017. PMID: 28667309 Free PMC article.

9

Accurate Digitization of the Chlorophyll Distribution of Individual Rice Leaves Using Hyperspectral Imaging and an Integrated Image Analysis Pipeline.

Feng H, Chen G, Xiong L, Liu Q, Yang W. Feng H, et al. Among authors: chen g. Front Plant Sci. 2017 Jul 25;8:1238. doi: 10.3389/fpls.2017.01238. eCollection 2017. Front Plant Sci. 2017. PMID: 28791031 Free PMC article.

10

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: chen g. Plant Methods. 2017 Nov 28;13:104. doi: 10.1186/s13007-017-0254-7. eCollection 2017. Plant Methods. 2017. PMID: 29209408 Free PMC article.

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