Introduction
This book describes the TERRA-REF data collection, computing, and analysis pipelines. The following links provide quick access to:
The ARPA-E-funded Transportation Energy Resources from Renewable Agriculture Phenotyping Reference Platform (TERRA-REF) program aims to transform plant breeding by using remote sensing to quantify plant traits such as plant architecture, carbon uptake, tissue chemistry, water use, and other features to predict the yield potential and stress resistance of 300+ diverse Sorghum lines.
The data storage and computing system provides researchers with access to the reference phenotyping data and analytics resources using a high performance computing environment. The reference phenotyping data includes direct measurements and sensor observations, derived plant phenotypes, and genetic and genomic data.
Our objectives are to ensure that the software and data in the reference data and computing pipeline are interoperable, reusable, extensible, and understandable. Providing clear definitions of common formats will make it easier to analyze and exchange data and results.
We have a large and diverse team - and an even larger community of contributors. See terraref.org/team.
This documentation is intended to enable a wide variety of user-groups to use and contribute to the datasets and tools contained in the TERRA-REF platform, including:
- Plant Physiologists interested in finding data and contributing phenotyping protocols. Relevant sections include the scientific objectives and protocols.
- Computer/Data Scientists looking for computer vision and machine learning problems. See a complete list of data products and how to access data.
- Engineers, Developers and Institutional IT looking for infrastructure required to turn big data into scientific understanding. See an overview of the software used, the developer manual and technical documentation. Note: ongoing pipeline development has migrated to https://agpipeline.github.io/.
- Github organization github.com/terraref that includes repositories containing algorithms as well as discussions, documentation, and other tools. Key repositories include:
- Email:
- David LeBauer (Data / Computing Lead): [email protected]
- Nadia Shakoor (Project Director): [email protected]
- Todd Mockler (Principal Investigator): [email protected]
Last modified 1yr ago