What seeding rate and/or fertilizer rate will result in the best possible yield for my field? This is one of the many questions that farmers ask themselves every year and that researchers and agronomists have been trying to answer for decades.
Numerous environmental and genetic hybrid or variety factors, either on their own or through interaction with each other, influence the actual optimum seeding and fertilizer rates for a given field or section of a field.
This is not a new concept. The influence of genetic and environmental variation and the interaction of these two major factors, often denoted as “GxE,” have been recognized since the early days of modern agronomic research.
Until recently, the best tools at the disposal of agronomists and agricultural researchers for estimating and accounting for the influence of these sources of variation in the estimation of optimal levels of a given agronomic input, such as seeding rate, have been multi-site and multi-year replicated trials.
In the analysis of the data from these types of trials, if environmental variation was seen to influence the agronomic factor being evaluated, for example, optimal seeding rate, then regions would be selected based on similarity of environmental factors, for example, soil type, rainfall, temperatures and so forth, and recommendations would be made for each of those regions.
This method has been used historically as a way to control for what we call macro-environmental variation, but it does not necessarily account for micro-environmental variation, which would include field-to-field environmental variation as well as within-field variation.
For this reason, although we have good estimates of what an average optimum seeding rate will be in an average weather year for a given region, these averages come from a range of optimums for different micro-environments within the larger macro-environment.
So, how can we improve this? Might it be possible to give farmers better field — or even site-specific — estimates of optimal seeding and/or fertilizer rates if we could help them execute their own replicated on-farm trials in a user-friendly way?
That is a question that researchers are trying to answer with the Data Intensive Farm Management Project. In this project, researchers leverage the advances made in precision agriculture technology to design and implement field-scale, highly replicated trials in coordination with the farmer and their agronomist or certified crop adviser.
Participation in the project requires the farmer to have a field of at least 80 acres, a variable rate planter for seeding rate trials, a variable rate applicator for fertilizer rate trials and a yield monitor. Since 2016, the DIFM project has conducted trials on over 100 fields in 10 U.S. states.
Farmers will be provided an honorarium of $500 for their participation and will be compensated for any other profit loss associated with the trial.
Because we cannot control the weather, these trials would still need to be run for several years in order to determine how weather variables influence the results for the farmer’s micro-environment.
However, this method allows for estimates of optimal input levels on a field-by-field, or management zone, basis, instead of on a regional basis, likely increasing the accuracy of those estimates for a given field over time.
If you have questions regarding this project or are interested in participating, please contact me via email at firstname.lastname@example.org.
All data collected from this project will be owned by the farmer. Project researchers maintain the right to use the data for analysis and recommendations, but they cannot sell or give the data to other parties without the consent of the farmer.
Talon Becker is a University of Illinois Extension commercial agriculture educator.