Creating a Replant Prescription in the Taranis Web App

Creating a Replant Prescription in the Taranis Web App

Taranis stand count insights make it easy to identify underperforming areas in a field and take action quickly. By using emergence data from your early missions, you can create a replant prescription directly within the Taranis Web App. Whether you're adjusting rates or assigning new hybrids to specific zones, the prescription tool helps you respond to early stand issues with precision and confidence.

With your stand count insights in hand, here's how to create a targeted replant prescription

  1. Log in to the Taranis Web App

  1. After logging in, the Recent Insights landing page appears.

  1. To begin creating a replant prescription, scroll down and select the color-coded threat box under stand count for the relevant field.

  1. A map view displays stand count for the field. Click the three-dot menu in the top right corner of the information panel.

  1. Select Create Zones from the dropdown.

  1. If the created zones are acceptable, select Add Prescription.

  1. Enter the name of your prescription, the hybrid/variety name, and then select seeds/ac as the unit.

  1. For a single hybrid/variety, enter the seeding rate for each zone.

  1. Multiple hybrids/varieties can be entered by selecting apply multiple or different products.
  2. For multiple hybrids/varieties, assign the correct hybrid/variety and rate per zone.

  1. Select Use this Rx for export and Save your prescription.

  1. The prescription can be downloaded as a shapefile to your computer for use in your monitor.

  1. The prescription will be saved and stored as information attached to the field. The prescription can be edited at any time.

  1. When creating the prescription, you can also edit zones, divide zones, or draw custom zones by clicking on the map. Don’t forget to Save at the bottom.


Once saved, your replant prescription is stored with the field and can be downloaded or edited anytime. This ensures you have a flexible, data-driven plan to address stand issues and maximize yield potential.


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