← Papers

Unverified paper record

A review on plant high-throughput phenotyping traits using UAV-based sensors

Computers and Electronics in Agriculture · 1 Nov 2020 · 10.1016/j.compag.2020.105731

Abstract

The current methods of phenotyping for breeding lines require a lot of time, labor and cost. In recent years, unmanned aerial system (UAS) has paved the way for the development of field high-throughput phenotyping for crops rapidly. Different sensors such as regular RGB camera (Red, Green and Blue), multispectral imaging camera (several wavebands), hyperspectral imaging camera (hundreds and even thousands of wavebands), thermal imaging sensor and light detection and ranging (LiDAR) sensor can be placed on unmanned aerial vehicle (UAV) to collect remote sensing data in field-scale trials. Based on this technique, the plant traits (e.g., yield, biomass, height, and leaf area index) can be estimated non-destructively, which is critical for high-throughput phenotyping in agriculture. Compared with ground vehicle-based sensors, UAS can increase throughput and frequency for phenotyping. It is low-cost and could provide high-resolution images compared with satellite-based technique. Based upon the phenotypic traits, those crops with high yield and strong stress resistance (e.g., disease resistance and salt resistance) can be selected, which could finally improve the production. This paper talked about the plant high-throughput phenotyping traits based on the sensors on the UAV. Also, the challenges and obstacles of UAV (e.g., flight safety, flight altitude, flight time, and sensor accuracy) were analyzed. In order to provide the updated information of the relationships between remote sensing information taken from UAV and plant phenotyping traits, we summarized the sensors, plants and traits reported in previous research articles. As a result, the review can be very useful for researchers to use appropriate UAV-based sensors to carry out plant phenotyping experiments, and for farmers to use this advanced technology in managing agricultural production.

Plant phenotyping relevance

UAVセンサーによる植物形質推定と高スループット・フィールドフェノタイピングを中心に扱うレビューであり、方法論的役割が明確。

titleA review on plant high-throughput phenotyping traits using UAV-based sensors
abstractThe current methods of phenotyping for breeding lines require a lot of time, labor and cost.
abstractDifferent sensors such as regular RGB camera (Red, Green and Blue), multispectral imaging camera (several wavebands), hyperspectral imaging camera (hundreds and even thousands of wavebands), thermal imaging sensor and light detection and ranging (LiDAR) sensor can be placed on unmanned aerial vehicle (UAV) to collect remote sensing data in field-scale trials.
abstractBased on this technique, the plant traits (e.g., yield, biomass, height, and leaf area index) can be estimated non-destructively, which is critical for high-throughput phenotyping in agriculture.

Code and data availability

公開論文であることは確認できましたが、現在の公式API・許可済み取得経路では本文を自動取得できませんでした。

No evidence-backed public reproduction asset is currently recorded.

This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.