Description
We investigated drivers of sub-field spatial variability in yield for 3 crops (hard red winter wheat, Triticum aestivum L. variety Langin; corn, Zea mays L.; and proso millet, Panicum milaceum L.) usings this multi-year dataset from a dryland research farm in northeastern Colorado, USA. The dataset spanned 18 2.6-4.3 ha management units collected over 4 years (2019-2022). The data includes high resolution topographic data collected via real-time kinematic GPS, densely sampled soil texture and chemical properties, and meteorological data from an on-site weather station.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| 8 | https://ndownloader.figshare.com/files/54132527 | ||
| 8 | https://ndownloader.figshare.com/files/54132539 | ||
| 48 | https://ndownloader.figshare.com/files/54132677 |
Tags
- rainfed
- topographic-position-index
- yield
- random-forest
- spatial-variability
- dryland
- precision-agriculture
- machine-learning