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Proceedings Paper

A custom multi-modal sensor suite and data analysis pipeline for aerial field phenotyping
Author(s): Paul W. Bartlett; Lauren Coblenz; Gary Sherwin; Adam Stambler; Andries van der Meer
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Paper Abstract

Our group has developed a custom, multi-modal sensor suite and data analysis pipeline to phenotype crops in the field using unpiloted aircraft systems (UAS). This approach to high-throughput field phenotyping is part of a research initiative intending to markedly accelerate the breeding process for refined energy sorghum varieties. To date, single rotor and multirotor helicopters, roughly 14 kg in total weight, are being employed to provide sensor coverage over multiple hectaresized fields in tens of minutes. The quick, autonomous operations allow for complete field coverage at consistent plant and lighting conditions, with low operating costs.

The sensor suite collects data simultaneously from six sensors and registers it for fusion and analysis. High resolution color imagery targets color and geometric phenotypes, along with lidar measurements. Long-wave infrared imagery targets temperature phenomena and plant stress. Hyperspectral visible and near-infrared imagery targets phenotypes such as biomass and chlorophyll content, as well as novel, predictive spectral signatures. Onboard spectrometers and careful laboratory and in-field calibration techniques aim to increase the physical validity of the sensor data throughout and across growing seasons. Off-line processing of data creates basic products such as image maps and digital elevation models. Derived data products include phenotype charts, statistics, and trends.

The outcome of this work is a set of commercially available phenotyping technologies, including sensor suites, a fully integrated phenotyping UAS, and data analysis software. Effort is also underway to transition these technologies to farm management users by way of streamlined, lower cost sensor packages and intuitive software interfaces.

Paper Details

Date Published: 19 May 2017
PDF: 10 pages
Proc. SPIE 10218, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II, 1021804 (19 May 2017); doi: 10.1117/12.2262858
Show Author Affiliations
Paul W. Bartlett, Near Earth Autonomy, Inc. (United States)
Lauren Coblenz, Near Earth Autonomy, Inc. (United States)
Gary Sherwin, Near Earth Autonomy, Inc. (United States)
Adam Stambler, Near Earth Autonomy, Inc. (United States)
Andries van der Meer, Near Earth Autonomy, Inc. (United States)


Published in SPIE Proceedings Vol. 10218:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II
J. Alex Thomasson; Mac McKee; Robert J. Moorhead, Editor(s)

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