Yang W - Search Results

1

IHUP: An Integrated High-Throughput Universal Phenotyping Software Platform to Accelerate Unmanned-Aerial-Vehicle-Based Field Plant Phenotypic Data Extraction and Analysis.

Wang B, Yang C, Zhang J, You Y, Wang H, Yang W. Wang B, et al. Among authors: yang c, yang w. Plant Phenomics. 2024 May 15;6:0164. doi: 10.34133/plantphenomics.0164. eCollection 2024. Plant Phenomics. 2024. PMID: 39165669 Free PMC article.

2

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives.

Yang W, Feng H, Zhang X, Zhang J, Doonan JH, Batchelor WD, Xiong L, Yan J. Yang W, et al. Mol Plant. 2020 Feb 3;13(2):187-214. doi: 10.1016/j.molp.2020.01.008. Epub 2020 Jan 22. Mol Plant. 2020. PMID: 31981735 Free article. Review.

3

Rapeseed Stand Count Estimation at Leaf Development Stages With UAV Imagery and Convolutional Neural Networks.

Zhang J, Zhao B, Yang C, Shi Y, Liao Q, Zhou G, Wang C, Xie T, Jiang Z, Zhang D, Yang W, Huang C, Xie J. Zhang J, et al. Among authors: yang c, yang w. Front Plant Sci. 2020 Jun 10;11:617. doi: 10.3389/fpls.2020.00617. eCollection 2020. Front Plant Sci. 2020. PMID: 32587594 Free PMC article.

4

Nondestructive 3D Image Analysis Pipeline to Extract Rice Grain Traits Using X-Ray Computed Tomography.

Hu W, Zhang C, Jiang Y, Huang C, Liu Q, Xiong L, Yang W, Chen F. Hu W, et al. Among authors: yang w. Plant Phenomics. 2020 May 2;2020:3414926. doi: 10.34133/2020/3414926. eCollection 2020. Plant Phenomics. 2020. PMID: 33313550 Free PMC article.

5

Combining UAV-RGB high-throughput field phenotyping and genome-wide association study to reveal genetic variation of rice germplasms in dynamic response to drought stress.

Jiang Z, Tu H, Bai B, Yang C, Zhao B, Guo Z, Liu Q, Zhao H, Yang W, Xiong L, Zhang J. Jiang Z, et al. Among authors: yang c, yang w. New Phytol. 2021 Oct;232(1):440-455. doi: 10.1111/nph.17580. Epub 2021 Jul 23. New Phytol. 2021. PMID: 34165797 Free article.

6

High-throughput unmanned aerial vehicle-based phenotyping provides insights into the dynamic process and genetic basis of rapeseed waterlogging response in the field.

Li J, Xie T, Chen Y, Zhang Y, Wang C, Jiang Z, Yang W, Zhou G, Guo L, Zhang J. Li J, et al. Among authors: yang w. J Exp Bot. 2022 Sep 3;73(15):5264-5278. doi: 10.1093/jxb/erac242. J Exp Bot. 2022. PMID: 35641129

7

A Novel Intelligent System for Dynamic Observation of Cotton Verticillium Wilt.

Huang C, Zhang Z, Zhang X, Jiang L, Hua X, Ye J, Yang W, Song P, Zhu L. Huang C, et al. Among authors: yang w. Plant Phenomics. 2023;5:0013. doi: 10.34133/plantphenomics.0013. Epub 2023 Jan 10. Plant Phenomics. 2023. PMID: 37040292 Free PMC article.

8

A Strategy for the Acquisition and Analysis of Image-Based Phenome in Rice during the Whole Growth Period.

Tang Z, Chen Z, Gao Y, Xue R, Geng Z, Bu Q, Wang Y, Chen X, Jiang Y, Chen F, Yang W, Hu W. Tang Z, et al. Among authors: yang w. Plant Phenomics. 2023 Jun 8;5:0058. doi: 10.34133/plantphenomics.0058. eCollection 2023. Plant Phenomics. 2023. PMID: 37304154 Free PMC article.

9

Enhancing Green Fraction Estimation in Rice and Wheat Crops: A Self-Supervised Deep Learning Semantic Segmentation Approach.

Gao Y, Li Y, Jiang R, Zhan X, Lu H, Guo W, Yang W, Ding Y, Liu S. Gao Y, et al. Among authors: yang w. Plant Phenomics. 2023 Jul 18;5:0064. doi: 10.34133/plantphenomics.0064. eCollection 2023. Plant Phenomics. 2023. PMID: 37469555 Free PMC article.

10

Maturity Classification of Rapeseed Using Hyperspectral Image Combined with Machine Learning.

Feng H, Chen Y, Song J, Lu B, Shu C, Qiao J, Liao Y, Yang W. Feng H, et al. Among authors: yang w. Plant Phenomics. 2024 Mar 26;6:0139. doi: 10.34133/plantphenomics.0139. eCollection 2024. Plant Phenomics. 2024. PMID: 38550661 Free PMC article.

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