Planting data can provide valuable insights into planter performance and serve as an important data layer for crop management during the season. Here are few considerations to avoid common errors and ensure quality data collection during planting:
Planter Configuration and Section Control: To collect and map accurate data while planting, proper planter configuration, including the length and width of the planting equipment, total number of rows and row width in the seed monitor, is critical. If section or individual row-control capabilities are present, verify the number of sections and width of each section are entered correctly and auto section/row control is enabled. This should be part of pre-plant technology inspection and can easily be done before getting in the field.
GPS Accuracy and Offsets: Planting data is spatially mapped using real-time GPS in the field; therefore, setup and accuracy plays a big part in how accurately the planting data is displayed and recorded. Similarly, GPS offsets, including exact location of the GPS on the tractor and from the planter, should be entered correctly to prevent errors such as data logging out of the field boundary, unnecessary overlap or skips between passes.
Calibration: Planted population is measured using a seed sensor installed on the seed tube. Seed sensor malfunction is somewhat common and will provide inaccurate readings. Hydraulic-driven planters also require a correct gear ratio to be entered into the planter display to control and achieve target seeding rate.
Most modern planting systems have an option to perform a static calibration test to check the accuracy of seed metering for the whole planter and even individual row units in some cases. This step helps verify that the correct crop kit and seed disc is installed and is functioning properly. If you are using the planter display to meter and place other inputs, make sure to calibrate and verify the accuracy of those systems.
Field Names and Jobs: One of the most common issues is data from multiple fields being together in a single job or under the same field name. This makes it harder to visualize data for each field separately and often requires some sort of post-processing to split and assign data to individual fields. Name each field distinctly, and start and end the planting job within that field to keep data clean and organized. This is important when planting multiple varieties and/or seeding rates across the farm, as being able to track planting metrics is one of the benefits of planting data.
Planting Prescriptions: For planting prescriptions that automatically vary seeding rates within the field, proper equipment setup along with GPS offsets (as mentioned above) are crucial. When loading prescription maps, make sure it’s in the correct file format and the appropriate rate column (with right units) is selected in the planter display to read the planting prescription correctly. Appropriate look-ahead distance, based on the planting speed and size of the seeding rate zones, should also be checked for the planter to transition smoothly between prescribed rates.
Data Transfer: Good quality data also means successful transfer into management software or an application. If enabled and active, most new planters wirelessly transfer data into their own management software, whether available as an online web or desktop application. If this functionality is not present or enabled, data should be transferred using an external storage device from the seed monitor to a computer. While the specific timeline for transferring this data depends on what and how it will be used, generally it’s the sooner the better.
Planting data can be useful for evaluating planter performance and assessing crop stand in the field. The quality of planting data is important, especially when making management decisions based on this data. CS