Global Maize and Wheat Yield Gap Scenarios with Organic Nutrient Strategies

A 2025 study dataset contains over 447,000 grid cells at ~10 km resolution for global irrigated wheat, irrigated maize, and rainfed maize/wheat. It includes complete grid-level results for four scenarios (Baseline, Only Legume, Only Manure, No Inputs) and validation data from independent field trials. The dataset was created by researchers at Charles University and includes all code and data for the manuscript submitted to Nature Food.

Use Cases

• Model global crop yield gaps based on high-resolution (~10 km) geospatial input data.
• Compare the impact of organic nutrient strategies (legume, manure) against a baseline scenario.
• Validate crop models using the independent field-trial data provided.
• Perform Monte Carlo uncertainty analysis on agricultural system optimization.
• Generate global maps of maize and wheat production under different input scenarios.

Strengths

• Includes input data for over 447,000 grid cells at ~10 km resolution.
• Provides complete grid-level results for four distinct agricultural scenarios.
• Comes with fully reproducible R scripts for all analyses and figure generation.
• Contains an independent validation dataset from field trials.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for individual tables is unknown, which may limit suitability assessment.

Provenance

Source

Charles University, Environment Centre, Prague, Czech Republic.

Collection Method

Genetic algorithm optimization applied to global geospatial input data.

Freshness

Last updated 2026-05-11 12:28:28; freshness should be verified.

Geography

Global coverage for irrigated wheat, irrigated maize, and rainfed maize/wheat.