Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

By Guijun Yang, Jiangang Liu, Chunjiang Zhao, Zhenhong Li, Yanbo Huang, Haiyang Yu, Bo Xu, Xiaodong Yang, Dongmei Zhu, Xiaoyan Zhang and 6 more. Frontiers in Plant Science, 2017

650 citations recorded by the source corpus.

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.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/aa16882bf32774219d3d3f965ffa70dffc605816

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Citations in the corpus

Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges (2018, positive): “improved image processing algorithms for Big data, and effective UAV regulations, there is potential for wider applications of the UAV-based field crop phenotyping [81].”
A Review on UAV-Based Applications for Precision Agriculture (2019, background): “Although in the recent works studied multispectral sensors are used a lot more frequently than hyperspectral because of their lower cost, hyperspectral technology seems to have a lot of potential and is considered as the future trend for crop phenotyping research [9].”
Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective (2018, positive): “Plant phenotyping frameworks incorporate sensors with mobility systems, such as tray conveyors [18], aerial and ground vehicles [19], UAVs [20], and motorized gantries [21, 22], to continuously capture growth and physiology data from plants.”
Using UAV Borne, Multi-Spectral Imaging for the Field Phenotyping of Shoot Biomass, Leaf Area Index and Height of West African Sorghum Varieties under Two Contrasted Water Conditions (2021, background): “There are more phenotypic parameters that should and can be estimated from UAV images [82,83] to mine the big potential of UAV techniques and promote modern sorghum breeding development.”