Agricultural and Biosystems Engineering Publications

Campus Units

Agricultural and Biosystems Engineering

Document Type

Article

Publication Version

Published Version

Publication Date

2018

Journal or Book Title

Precision Agriculture

Research Focus Area(s)

Biological and Process Engineering and Technology

DOI

10.1007/s11119-018-9601-6

Abstract

This article describes the design and field evaluation of a low-cost, high-throughput phenotyping robot for energy sorghum for use in biofuel production. High-throughput phenotyping approaches have been used in isolated growth chambers or greenhouses, but there is a growing need for field-based, precision agriculture techniques to measure large quantities of plants at high spatial and temporal resolutions throughout a growing season. A low-cost, tracked mobile robot was developed to collect phenotypic data for individual plants and tested on two separate energy sorghum fields in Central Illinois during summer 2016. Stereo imaging techniques determined plant height, and a depth sensor measured stem width near the base of the plant. A data capture rate of 0.4 ha, bi-weekly, was demonstrated for platform robustness consistent with various environmental conditions and crop yield modeling needs, and formative human–robot interaction observations were made during the field trials to address usability. This work is of interest to researchers and practitioners advancing the field of plant breeding because it demonstrates a new phenotyping platform that can measure individual plant architecture traits accurately (absolute measurement error at 15% for plant height and 13% for stem width) over large areas at a sub-daily frequency; furthermore, the design of this platform can be extended for phenotyping applications in maize or other agricultural row crops.

Comments

This article is published as Young, Sierra N., Erkan Kayacan, and Joshua M. Peschel. "Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum." Precision Agriculture (2018). DOI: 10.1007/s11119-018-9601-6. Posted with permission.

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Open

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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