Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum

Young, Sierra N.; Kayacan, Erkan; Peschel, Joshua M.

doi:10.1007/s11119-018-9601-6

Title: Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum

Journal Article · Sat Sep 15 00:00:00 EDT 2018 · Precision Agriculture

DOI:https://doi.org/10.1007/s11119-018-9601-6· OSTI ID:1471139

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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 lowcost, 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. In conclusion, 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.

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Research Organization:: Univ. of Illinois at Urbana-Champaign, IL (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0000598

OSTI ID:: 1471139

Alternate ID(s):: OSTI ID: 1475028

Journal Information:: Precision Agriculture, Journal Name: Precision Agriculture Vol. 20 Journal Issue: 4; ISSN 1385-2256

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: Netherlands

Language:: English

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Cited by: 42 works

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Cited By (2)

Maize Plant Phenotyping: Comparing 3D Laser Scanning, Multi-View Stereo Reconstruction, and 3D Digitizing Estimates Wang, Yongjian; Wen, Weiliang; Wu, Sheng Remote Sensing, Vol. 11, Issue 1 https://doi.org/10.3390/rs11010063	journal	December 2018
A Framework for Evaluating Field-Based, High-Throughput Phenotyping Systems: A Meta-Analysis Young, Sierra N. Sensors, Vol. 19, Issue 16 https://doi.org/10.3390/s19163582	journal	August 2019

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