By Elizabeth Hawkins and Maninder Singh
When applied correctly, variable rate seeding (VRS) has potential to reduce crop input costs in areas of low productivity and increase yields in areas of high productivity. VRS provides the opportunity to optimize seed inputs spatially by matching plant populations with productivity zones within a field. This process is achieved by creating a prescription that can be executed by a variable rate capable planter.
The first step to successfully create a VRS prescription is to identify and understand the field variability that can be managed with different plant populations. Once the variation is identified, the field can be divided into “zones” that can be managed similarly. These zones can be created within a given field based on various data layers such as historical yields, soil properties, topography and/or aerial imagery. If using yield data, it is important to use multiple years of data from the same crop that will be planted. Accurate yield data is critical when using it for VRS, so it should be recorded from a calibrated yield monitor and the data should be cleaned prior to using it for creating prescriptions. Data from areas that offer a relatively stable yield response over time are ideal.
Once zones are identified, information on agronomic response to seeding rates can be used to create variable rate prescriptions. This allows for customized seeding rate in different zones in the field, potentially resulting in higher yield and lower input cost. Typically for corn, seeding rates are increased in high productivity zones and decreased in low productivity zones. For soybeans, seeding rates are often decreased in high productivity zones and increased in low productivity areas. The ideal number and size of zones will depend on the field size and variability as well as equipment size and capability, however three to five zones within a field are common. Conducting on-farm strip trials makes it possible to observe how yield responds to the seeding rate for each field. Spatial yield analysis can be conducted to help investigate whether VRS has potential to provide a positive return on investment.
When using VRS, it is important to take time to validate prescriptions to ensure target seeding rates are accurately placed to optimize returns. Check strips should be included in the field to evaluate accuracy of the prescription and compare it to the standard practice seeding rate. Over time, this will guide prescription adjustments and hone in on seeding rates that allow for maximize returns.
There are many precision ag tools that can help manage data, create prescriptions and analyze spatial yield results (e.g. SMS, Encirca, John Deere Operations Center, Fieldview). Participants at the
2019 MSU Agriculture Innovation Day attending the “Art and Science of Variable Rate Seeding” session will learn more about these precision ag tools, explore the importance of proper data stewardship, calculate return on investment of VRS for individual fields, and learn the necessity of check strips to evaluate the accuracy of prescriptions.
MSU Agriculture Innovation Day is an annual event focusing on in-depth education on critical topics. The event rotates to various locations throughout the state to give farmers access to experts who can help them improve their businesses while maintaining environmentally sound practices on their farms.