RootRobot: A field-based platform for maize root system architecture phenotyping

Xiaomeng Shi, Daeun Choi, Paul Heinemann, Molly Hanlon, Jonathan Lynch

Research output: Contribution to conferencePaper

Abstract

Field-based phenotyping technologies using automation and image processing can increase the efficiency of quantifying architectures of plant roots. In order to achieve accurate phenotyping results, the first step is to prepare root samples appropriately before imaging and analysis. For maize root architecture phenotyping, the preprocessing steps include excavating maize roots from the soil and removing dirt from the excavated roots. Currently, these operations are conducted manually, resulting in low-throughput with slow processing time. To automate the pre-processing steps and obtain a massive number of images in the field to be used for reconstructing high-resolution 3D phenotyping data, we developed a highly automated field-based platform, the RootRobot. The RootRobot consists of two field units: (1) Mobile Unit, and (2) Imaging Unit. The Mobile Unit collects root samples from a field and preprocesses samples for imaging with an automatic pipeline of excavating, cutting, and cleaning at a target speed of 6 seconds per root. Lab and field experiments were conducted to test the performance of each automated preprocessing step. The Imaging Unit was developed to be a separate field station to automatically acquire and store images from each root sample. The imaging procedure was designed to obtain, store, and transfer 3600 high-resolution images for each root sample in minutes. With greater speed and precision, the RootRobot will accelerate the research on phenotyping the underlying root architecture.

Original languageEnglish (US)
DOIs
StatePublished - Jan 1 2019
Event2019 ASABE Annual International Meeting - Boston, United States
Duration: Jul 7 2019Jul 10 2019

Conference

Conference2019 ASABE Annual International Meeting
CountryUnited States
CityBoston
Period7/7/197/10/19

Fingerprint

root systems
Imaging techniques
phenotype
corn
image analysis
Image resolution
Processing
Cleaning
Image processing
sampling
Automation
Pipelines
Throughput
Soils
automation
plant architecture
cleaning
Experiments

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science
  • Bioengineering

Cite this

Shi, X., Choi, D., Heinemann, P., Hanlon, M., & Lynch, J. (2019). RootRobot: A field-based platform for maize root system architecture phenotyping. Paper presented at 2019 ASABE Annual International Meeting, Boston, United States. https://doi.org/10.13031/aim.201900806
Shi, Xiaomeng ; Choi, Daeun ; Heinemann, Paul ; Hanlon, Molly ; Lynch, Jonathan. / RootRobot : A field-based platform for maize root system architecture phenotyping. Paper presented at 2019 ASABE Annual International Meeting, Boston, United States.
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Shi, X, Choi, D, Heinemann, P, Hanlon, M & Lynch, J 2019, 'RootRobot: A field-based platform for maize root system architecture phenotyping', Paper presented at 2019 ASABE Annual International Meeting, Boston, United States, 7/7/19 - 7/10/19. https://doi.org/10.13031/aim.201900806

RootRobot : A field-based platform for maize root system architecture phenotyping. / Shi, Xiaomeng; Choi, Daeun; Heinemann, Paul; Hanlon, Molly; Lynch, Jonathan.

2019. Paper presented at 2019 ASABE Annual International Meeting, Boston, United States.

Research output: Contribution to conferencePaper

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Shi X, Choi D, Heinemann P, Hanlon M, Lynch J. RootRobot: A field-based platform for maize root system architecture phenotyping. 2019. Paper presented at 2019 ASABE Annual International Meeting, Boston, United States. https://doi.org/10.13031/aim.201900806