Crop Yield and Health

Crop Yield and Health combines field-based agricultural data with environmental and modeled data. By using predictive analytics, Crop Yield and Health provide insights to farmers, food processors, and distributors about crops, risks, and yields. The insights help to reduce supply chain risk, reduce costs, and provide better quality products.

The following types of data are used in analytics in Crop Yield and Health:
  • Farm management system details, such as field names, boundaries, and ownership
  • Crop types, planting dates, and seed variety
  • Soil conditions, such as moisture, pH level, and nutrients
  • Weather data, such as historical, current, and forecasted weather conditions
  • High-definition satellite and drone imagery
During the onboarding process, your administrator completes the following steps to set up the Crop Yield and Health industry solution in your environment:
  1. Import your custom sensor and asset data into Environmental Intelligence Suite.
  2. Define fields by using a KML file format and upload the files to IBM Cloud Object Storage.
  3. Add the field definitions from Cloud Object Storage to Environmental Intelligence Suite and define polygons to represent each field.
  4. Create queries based on proprietary and public data sets in Geospatial Analytics, including agricultural-specific data sets.

When the environment is set up, AI-based, machine learning analytics are run on the field data and the field-related KPIs, such as crop health, field soil moisture, field soil temperature, can be visualized by the operations teams on dashboards and maps, which is shown in Figure 1, from the Dashboard Visualization component.

Figure 1. Agriculture dashboard
Dashboard that displays the layout of a field on a farm.

Use Crop Yield and Health to alert employees and customers about weather events that might impact the supply chain.