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Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives
Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypi...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492853/ https://www.ncbi.nlm.nih.gov/pubmed/28713402 http://dx.doi.org/10.3389/fpls.2017.01111 |
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author | Yang, Guijun Liu, Jiangang Zhao, Chunjiang Li, Zhenhong Huang, Yanbo Yu, Haiyang Xu, Bo Yang, Xiaodong Zhu, Dongmei Zhang, Xiaoyan Zhang, Ruyang Feng, Haikuan Zhao, Xiaoqing Li, Zhenhai Li, Heli Yang, Hao |
author_facet | Yang, Guijun Liu, Jiangang Zhao, Chunjiang Li, Zhenhong Huang, Yanbo Yu, Haiyang Xu, Bo Yang, Xiaodong Zhu, Dongmei Zhang, Xiaoyan Zhang, Ruyang Feng, Haikuan Zhao, Xiaoqing Li, Zhenhai Li, Heli Yang, Hao |
author_sort | Yang, Guijun |
collection | PubMed |
description | Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping. |
format | Online Article Text |
id | pubmed-5492853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-54928532017-07-14 Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives Yang, Guijun Liu, Jiangang Zhao, Chunjiang Li, Zhenhong Huang, Yanbo Yu, Haiyang Xu, Bo Yang, Xiaodong Zhu, Dongmei Zhang, Xiaoyan Zhang, Ruyang Feng, Haikuan Zhao, Xiaoqing Li, Zhenhai Li, Heli Yang, Hao Front Plant Sci Plant Science Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping. Frontiers Media S.A. 2017-06-30 /pmc/articles/PMC5492853/ /pubmed/28713402 http://dx.doi.org/10.3389/fpls.2017.01111 Text en Copyright © 2017 Yang, Liu, Zhao, Li, Huang, Yu, Xu, Yang, Zhu, Zhang, Zhang, Feng, Zhao, Li, Li and Yang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Yang, Guijun Liu, Jiangang Zhao, Chunjiang Li, Zhenhong Huang, Yanbo Yu, Haiyang Xu, Bo Yang, Xiaodong Zhu, Dongmei Zhang, Xiaoyan Zhang, Ruyang Feng, Haikuan Zhao, Xiaoqing Li, Zhenhai Li, Heli Yang, Hao Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title | Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title_full | Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title_fullStr | Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title_full_unstemmed | Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title_short | Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives |
title_sort | unmanned aerial vehicle remote sensing for field-based crop phenotyping: current status and perspectives |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492853/ https://www.ncbi.nlm.nih.gov/pubmed/28713402 http://dx.doi.org/10.3389/fpls.2017.01111 |
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