Gro’s Yield Forecast Models use a suite of machine-learning models to estimate in-season yields at the district, province, and/or national levels on a daily basis.  Gro’s Argentina Corn Yield Forecast Model is updated daily, providing in-season yields at the district, province, and national levels throughout the growing season.

Customers Use the Model to: 

  • Follow in-season yields in the world’s fifth-largest corn producer
  • Predict future trends such as crop yields and production, agricultural input demand, and significant weather patterns
  • Gauge crop availability and crop prices
  • Understand how weather impacts yields in microclimates
  • Inform other models focused on damage caused by pests and diseases
  • Monitor crop production, the most significant part of the balance sheet, by tracking its most variable component, which is in-season yield

Why It Matters

Argentina is the fifth-largest corn producer in the world, and the third-largest exporter of the crop. The country exports the majority of the corn it produces, injecting over $5 billion a year into the country’s economy. Developments in Argentina’s corn production have implications for the global economy, as a decline in production here heightens pressure on other key exporters of the product. This makes Argentina a significant country to watch when monitoring global trade dynamics. 

Gro’s district-level yield model for corn in Argentina was built using machine-learning techniques that rely on weather and environmental data. The model uses a number of variables, including:

  • Eight-day normalized difference vegetation index (NDVI)
  • Land surface temperature
  • Weather forecasts of air temperature and precipitation
  • Evapotranspiration difference from 10-yr median (2003-2013)
  • Soil characteristics
  • Latitude and longitude

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