Relative Yield Model
Anticipate Crop Performance with Relative Yield Model
Informed Crop Development
Monitor how current season yield expectation compares to the historical benchmark with real-time, field and crop practice specific insights.
watch your yield story
watch your yield story unfold in real-time
Built on proven soil-plant-atmosphere science, this model processes daily weather data to deliver field-specific yield forecast insights.
Tailored predictions
Based on local growing conditions, crop, and variety
Customizable crop practice benchmark
Specify alternative crop practices to create tailored comparisons
In-season monitoring
Follow the yield realization journey week by week
Actionable Insights
Understand how current conditions are impacting yield potential and make proactive adjustments to crop production strategies.
Tailored predictions
Based on local growing conditions, crop, and variety
Customizable crop practice benchmark
Specify alternative crop practices to create tailored comparisons
In-season monitoring
Follow the yield realization journey week by week
Actionable Insights
Understand how current conditions are impacting yield potential and make proactive adjustments to crop production strategies.
Model Insights
Model Insights
Probabilistic insights to quantify the variability of yield predictions
Forecasted Percentage of Yield Realization
The Relative Yield Model is a percentage value comparing the current season's predicted yield to a historically derived yield benchmark
Percentile Values
Percentile-based relative yield value reflecting the probability of different outcomes.
Key Characteristics
Key Characteristics
Core features designed to offers insights into likely yield outcomes.
Probabilistic insights
Quantifies the range and likelihood of possible yield outcomes with multiple percentile values.
Customizable inputs
Send detailed field context for tailored predictions, or use predefined settings to quickly generate Relative Yield Model levels.
Field-level precision
Leverages field location, crop-specific parameters, and localized weather data to deliver highly context-aware predictions.
Versatile use-cases
Supports diverse use cases, from individual fields to regional analysis, enabling in-season monitoring.