Global Rice Cultivation Data for Irrigation and Nitrogen Management Optimization

4.4 MB of data supporting research on optimizing irrigation and nitrogen use to increase net carbon sequestration in global rice production. The dataset, authored by Qingsong Zhu and last updated in May 2026, includes files in Python, R, Excel, and notebook formats. Its specific contents likely include modeled or measured parameters related to agricultural practices and carbon balance.

Use Cases

• Modeling the carbon sequestration potential of rice paddies based on described management practices.
• Analyzing trade-offs between irrigation strategies and nitrogen application rates for climate goals.
• Training machine learning models to predict optimal agricultural inputs for reducing net emissions.

Strengths

• Data is openly licensed under CC-BY-4.0, permitting broad reuse.
• Includes analysis code in Python (PY, IPYNB) and R (R, RHISTORY) formats, supporting reproducibility.
• Last updated on 2026-05-30, suggesting recent maintenance.

Limitations

• Row count and column definitions are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.
• The 4.4 MB size indicates a relatively small dataset, which may limit model training scope.

Provenance

Source

Qingsong Zhu via figshare

Freshness

Last updated 2026-05-30 08:12:07; freshness should be verified.

Geography

Global