Combining self-organizing maps and biplot analysis to preselect maize phenotypic components based on UAV high-throughput phenotyping platform
文献类型: 外文期刊
第一作者: Han, Liang
作者: Han, Liang;Yang, Guijun;Yang, Hao;Xu, Bo;Long, Huiling;Yang, Xiaodong;Zhao, Chunjiang;Han, Liang;Yang, Hao;Li, Heli;Long, Huiling;Li, Zhenhai;Yang, Xiaodong;Zhao, Chunjiang;Han, Liang;Dai, Huayang
作者机构:
关键词: SOM; Biplot; UAV; Maize; High-throughput phenotyping
期刊名称:PLANT METHODS ( 影响因子:4.993; 五年影响因子:5.312 )
ISSN: 1746-4811
年卷期: 2019 年 15 卷
页码:
收录情况: SCI
摘要: BackgroundWith environmental deterioration, natural resource scarcity, and rapid population growth, mankind is facing severe global food security problems. To meet future needs, it is necessary to accelerate progress in breeding fornew varieties with high yield and strong resistance. However, the traditional phenotypic screening methods have some disadvantages, such as destructive, inefficient, low-dimensional, labor-intensive and cumbersome, which seriously hinder the development of field breeding. Breeders urgently need a high-throughput technique for acquiring and evaluating phenotypic data that can efficiently screen out excellent phenotypic traits from large-scale genotype populations.ResultsIn the present study, we used an unmanned aerial vehicle (UAV) high-throughput phenotyping (HTP) platform to collect RGB and multispectral images for a breeding program and acquired multiple phenotypic components (or traits), such as plant height, normalized difference vegetation index, biomass accumulation, plant-height growth rate, lodging, and leaf color. By implementing self-organizing maps and principal components analysis biplots to establish phenotypic map and similarity, we proposed an UAV-assisted HTP framework for preselecting maize (Zee mays L.) phenotypic components (or traits).ConclusionsThis framework gives breeders additional information to allow them to quickly identify and preselect plants that have genotypes conferring desirable phenotypic components out of thousands of field plots. The present study also demonstrates that remote sensing is a powerful tool with which to acquire abundant phenotypic components. By using these rich phenotypic components, breeders should be able to more effectively identify and select superior genotypes.
分类号:
- 相关文献
作者其他论文 更多>>
-
Recognition of wheat rusts in a field environment based on improved DenseNet
作者:Chang, Shenglong;Cheng, Jinpeng;Fan, Zehua;Ma, Xinming;Li, Yong;Zhao, Chunjiang;Chang, Shenglong;Yang, Guijun;Cheng, Jinpeng;Fan, Zehua;Yang, Xiaodong;Zhao, Chunjiang
关键词:Plant disease; Wheat rust; Image processing; Deep learning; Computer vision (CV); DenseNet
-
Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images
作者:Wang, Gengze;Chen, Riqiang;Yang, Guijun;Feng, Haikuan;Wang, Gengze;Chen, Riqiang;Yang, Guijun;Feng, Haikuan;Meng, Di;Jin, Hailiang;Ge, Xiaosan;Wang, Laigang;Feng, Haikuan
关键词:early-season rice mapping; spectral index (SI); synthetic aperture radar (SAR); Simple Non-Iterative Clustering (SNIC); time series filtering; K-Means; Jeffries-Matusita (JM) distance
-
GCVC: Graph Convolution Vector Distribution Calibration for Fish Group Activity Recognition
作者:Zhao, Zhenxi;Zhao, Chunjiang;Zhao, Zhenxi;Yang, Xinting;Zhou, Chao;Zhao, Chunjiang;Zhao, Zhenxi;Yang, Xinting;Zhou, Chao;Zhao, Chunjiang;Zhao, Zhenxi;Yang, Xinting;Zhou, Chao;Zhao, Chunjiang;Liu, Jintao
关键词:Fish; Feature extraction; Activity recognition; Calibration; Adhesives; Training; Convolution; Graph convolution vector calibration; fish group activity; activity feature vector calibration; fish activity dataset
-
Adaptive precision cutting method for rootstock grafting of melons: modeling, analysis, and validation
作者:Chen, Shan;Zhao, Chunjiang;Chen, Shan;Jiang, Kai;Zheng, Wengang;Jia, Dongdong;Zhao, Chunjiang;Jiang, Kai;Zheng, Wengang;Jia, Dongdong;Zhao, Chunjiang
关键词:Melon; Grafting robot; Adaptive cutting; Rootstock pith cavity; Machine vision
-
Unveiling Innovative Approaches to Mitigate Metals/Metalloids Toxicity for Sustainable Agriculture
作者:Charagh, Sidra;Hui, Suozhen;Wang, Jingxin;Zhou, Liang;Xu, Bo;Zhang, Yuanyuan;Sheng, Zhonghua;Tang, Shaoqing;Hu, Shikai;Hu, Peisong;Raza, Ali
关键词:
-
Long-range infrared absorption spectroscopy and fast mass spectrometry for rapid online measurements of volatile organic compounds from black tea fermentation
作者:Yang, Chongshan;Li, Guanglin;Zhao, Chunjiang;Fu, Xinglan;Yang, Chongshan;Jiao, Leizi;Wen, Xuelin;Lin, Peng;Duan, Dandan;Zhao, Chunjiang;Dong, Daming;Yang, Chongshan;Jiao, Leizi;Wen, Xuelin;Lin, Peng;Duan, Dandan;Dong, Daming;Dong, Chunwang
关键词:Black tea fermentation; Volatile organic compounds; Proton transfer reaction mass spectrometry; Fourier transform infrared spectroscopy; Principal component analysis; Extreme learning machine
-
Comparison of three models for winter wheat yield prediction based on UAV hyperspectral images
作者:Xu, Xiaobin;Teng, Cong;Zhu, Hongchun;Li, Zhenhai;Teng, Cong;Feng, Haikuan;Zhao, Yu
关键词:hyperspectral imagery; unmanned aerial vehicle; winter wheat; yield prediction model; remote sensing