Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

By Yeyin Shi, J. A. Thomasson, Seth C. Murray, N. A. Pugh, William L. Rooney, Sanaz Shafian, N. Rajan, Gregory Rouze, Cristine L. S. Morgan, Haly L. Neely and 18 more. PLoS ONE, 2016

318 citations recorded by the source corpus.

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/36f5fbc59d903baa6f77737fce59e51f06f0a14e

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In Ecology

1. Yanbo Huang
2. Haikuan Feng
3. Guijun Yang
4. Zhenhai Li

In Environmental Engineering

1. Haikuan Feng
2. Guijun Yang
3. Zhenhai Li

In Plant Science

1. D. Diouf
2. Haikuan Feng
3. Guijun Yang
4. Zhenhai Li

Citations in the corpus

• Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives (2017, background): “However, there are only six articles that explicitly include “Phenotyping” or “Phenomics” in the titles and keyword (Zaman-Allah et al., 2015; Gomez-Candon et al., 2016; Haghighattalab et al., 2016; Holman et al., 2016; Shi et al., 2016; Watanabe et al., 2017).”
• 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): “Thus, errors could occur in both ground truth measurements and UAV estimates [58].”