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Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects

文献类型：期刊论文

作者Jin, Shichao3,6,7; Sun, Xiliang6,7; Wu, Fangfang6,7; Su, Yanjun6,7; Li, Yumei5; Song, Shiling6,7; Xu, Kexin6,7; Ma, Qin4; Baret, Frederic1,3; Jiang, Dong
刊名ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
出版日期2021
卷号171页码:202-223
关键词Lidar Traits Phenomics Breeding Management Multi-omits
ISSN号0924-2716
DOI10.1016/j.isprsjprs.2020.11.006
文献子类Review
英文摘要Plant phenomics is a new avenue for linking plant genomics and environmental studies, thereby improving plant breeding and management. Remote sensing techniques have improved high-throughput plant phenotyping. However, the accuracy, efficiency, and applicability of three-dimensional (3D) phenotyping are still challenging, especially in field environments. Light detection and ranging (lidar) provides a powerful new tool for 3D phenotyping with the rapid development of facilities and algorithms. Numerous efforts have been devoted to studying static and dynamic changes of structural and functional phenotypes using lidar in agriculture. These progresses also improve 3D plant modeling across different spatial-temporal scales and disciplines, providing easier and less expensive association with genes and analysis of environmental practices and affords new insights into breeding and management. Beyond agriculture phenotyping, lidar shows great potential in forestry, horticultural, and grass phenotyping. Although lidar has resulted in remarkable improvements in plant phenotyping and modeling, the synthetization of lidar-based phenotyping for breeding and management has not been fully explored. We identify three main challenges in lidar-based phenotyping development: 1) developing low cost, high spatial-temporal, and hyperspectral lidar facilities, 2) moving into multi-dimensional phenotyping with an endeavor to generate new algorithms and models, and 3) embracing open source and big data.
学科主题Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
出版地AMSTERDAM
电子版国际标准刊号1872-8235
WOS关键词LEAF-AREA INDEX ; TERRESTRIAL LASER SCANNER ; WAVE-FORM LIDAR ; ESTIMATING ABOVEGROUND BIOMASS ; INDIVIDUAL TREE CROWNS ; DENSIFICATION FILTERING ALGORITHM ; ESTIMATING CANOPY STRUCTURE ; FIELD PHENOTYPING PLATFORM ; MARKER-FREE REGISTRATION ; DIFFERENT GROWTH-STAGES
WOS研究方向Science Citation Index Expanded (SCI-EXPANDED)
语种英语
WOS记录号WOS:000604406500014
出版者ELSEVIER
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences [XDA24020202] ; Beijing Municipal Science and Technology Project [Z191100007419004] ; Plant Phenomics Research Program of Science and Technology Department of Jiangsu Province [BM2018001]
源URL[http://ir.ibcas.ac.cn/handle/2S10CLM1/26386]  
专题植被与环境变化国家重点实验室
作者单位1.Mississippi State Univ, Dept Forestry, Mississippi State, MS 39759 USA
2.Nanjing Agr Univ, Jiangsu Collaborat Innovat Ctr Modern Crop Prod, Nanjing 210095, Peoples R China
3.INRA, Unite Mixte Rech 1114, Environm Mediterraneen & Modelisat AgroHydrosyst, F-84914 Avignon, France
4.Chinese Acad Sci, Inst Zool, Key Lab Anim Ecol & Conservat Biol, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
7.Nanjing Agr Univ, Plant Phen Res Ctr, 1 Weigang, Nanjing 210095, Peoples R China
推荐引用方式
GB/T 7714		 Jin, Shichao,Sun, Xiliang,Wu, Fangfang,et al. Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2021,171:202-223.
APA Jin, Shichao.,Sun, Xiliang.,Wu, Fangfang.,Su, Yanjun.,Li, Yumei.,...&Guo, Qinghua.(2021).Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,171,202-223.
MLA Jin, Shichao,et al."Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 171(2021):202-223.

入库方式： OAI收割

来源：植物研究所

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