Cropwise
powered by syngenta
growth stage model

Optimize crop production with precise growth stage prediction

Smarter Crop Planning

The Crop Growth Stage Prediction Model provides accurate timelines of crop development stages, enabling informed pre-season and in-season decisions on field production journey. By leveraging field-specific data, weather information, and advanced crop modeling, this tool offers valuable insights for various crops and regions.

Observe crop development from planting to harvest.

The model algorithm translates field-centric data, historical weather records, and soil characteristics into crop-specific growth stage predictions.

Crop and variety specific

Physiological parameters defined for various crops and varieties, recognizing that each develops differently under varying conditions.

Flexible inputs

Enhance prediction accuracy with optional field inputs or rely on default values for quick assessments.

Comprehensive predictions

Offers both historical simulations and aggregated growth stage predictions for thorough analysis.

Adaptable time horizons

Provides pre-season planning capabilities using historical data and in-season monitoring with latest real-time weather data and forecasts.

Model insights

Get clear, data-driven insights on crop development for better planning and decision-making.

Historical Growth Stage Simulations

Year-by-year growth stage predictions up to 20 years back

Aggregated Growth Stage Simulations

Consolidated summary of in-season predicted growth stages

Key Characteristics

Core features designed to enhance crop growth predictions and decision-making.

Versatile service for agricultural decision-making

Supports diverse use cases, from individual fields to regional analysis, enabling both pre-season planning and in-season monitoring.

Customizable inputs for tailored predictions

Adjust parameters for specific crops or regions, or use predefined settings to quickly generate accurate growth stage forecasts.

Field-level precision with local data

Leverages field location, crop-specific data, and localized weather patterns to deliver highly accurate growth stage predictions.

Historical and in-season simulations

Provides year-over-year analyses and real-time tracking to support ongoing monitoring and improve future decision-making.