Yield Models

These Yield Models are machine-learning based models of end-of-season yields, for selected crops. We combine several algorithms in a multilevel model, and use understanding of physiological processes in temporal feature selection to achieve high precision in our intraseasonal forecasts, including in very anomalous seasons.

Our expanding suite of yield models can add significant value to any business that needs advance knowledge of upcoming harvest sizes.

Some variables selected by our experts for these models include:

  • Normalized Difference Vegetation Index (NDVI)
  • Evapotranspiration (ET)
  • Land Surface Temperature (LST)
  • Weather and Rainfall Data
  • Crop Calendars
  • Crop Condition Analysis
  • Soil Data
  • Acreage Planted and Harvested

We are constantly building more predictive models, which are available to our users. We strongly encourage all those interested in the predictive yield modeling to pay attention to our estimates and contact us with any thoughts or questions.