Journal of Agricultural Big Data ›› 2021, Vol. 3 ›› Issue (3): 62-75.doi: 10.19788/j.issn.2096-6369.210307

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Analysis and Application of High-throughput Plant Phenotypic Big Data Collected from Unmanned Aerial Vehicles

Peisen Yuan1(), Mingjia Xue1, Yingjun Xiong1, Zhaoyu Zhai2, Huanliang Xu1()   

  1. 1.College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
    2.Superior School of Technical Engineering and Telecommunication Systems, Technical University of Madrid, Madrid 28040, Spain
  • Received:2020-03-11 Online:2021-09-26 Published:2020-10-30
  • Contact: Huanliang Xu;


Plant phenotypes refer to the physical, physiological and biochemical characteristics and traits that are determined or influenced by genes and environmental factors. Accurate and rapid access to plant phenotypic information under different environmental conditions, and the analysis of the genetic and performance patterns of their genomes, can effectively promote research on the correlation between genomic and phenotypic information. The Unmanned Aerial Vehicle (UAV) high-throughput plant phenotyping platform is suitable for acquiring plant phenotypic data in field environments owing to the UAV’s mobility and flexibility, and it has the great advantages of a high data acquisition efficiency and low cost. With the help of advanced sensor technologies, such as hyperspectral imaging and LIDAR, the UAV provides a feasible way to efficiently acquire plant phenotypic data. Effective analyses and processing methods and techniques for plant phenotypic data acquired by UAVs must be employed. Thus, high-throughput plant phenotypic analyses based on UAV platforms provides an important tool for studying plant phenotypic information from the field. This paper summarizes and analyzes the latest research results of UAV-based high-throughput crop phenotyping using big data analysis technology and artificial intelligence, as well as its research principles, relevant algorithms, processes, key technologies and applications. The main focus is on big data processing and intelligent analysis techniques related to UAV-based high-throughput plant phenotype big data and to the analysis of typical phenotypes, such as plant height, leaf area index, and plant diseases. We analyzed the current research needs and provide both a summary and outlook on related applications.

Key words: phenotypic big data, unmanned aerial vehicle, high-throughput, plant phenotyping

CLC Number: 

  • S-3