X-ray driven peanut trait estimation-Plant Methods paper

The ground-truth dataset linked to the research article "X-ray driven peanut trait estimation: Computer vision aided agri-system transformation" of Plant Methods is available in this data repository.

Description of the headers:

1. Peanut variety name [39 peanut varieties were used]
2. Variety number [number linked to variety]
3. Variety Type [Breeding lines, Released popular cultivar, or Farmers' produce]
4. Rep [number of replicates per sample used in the study]
5. Corresponding TIFF image number
6. kernel_weight_(g) [unit = g]
7. shell_weight_(g) [unit = g]
8. percentage_shelling_(%) [unit = %]

For additional information please contact the corresponding author Jana Kholova (j.kholova@cgiar.org)

Grant Support: The data included herein have been obtained owing to support from the following grants: Internal grant agency of the Faculty of Economics and Management from the Czech University of Life Sciences Prague, grant, Life Sciences 4.0 Plus", no. 2022B0006, and the following grants from ICRISAT: Accelerated Varietal Improvement and Seed Delivery of Legumes and Cereals in Africa (AVISA), CGIAR's Crop to End Hunger initiative–ICRISAT (a multi-funder initiative led by USAID and including the Gates Foundation; DFID, UK; GiZ, Germany; and ACIAR, Australia; CtEH-ICRISAT; 2019–2021); and CGIAR Research Program grant for Grain Legumes and Dryland Cereals–ICRISAT (GLDC-ICRISAT; 2018–2022).