Research Highlights

Research Highlights
Using Precision Data to Define and Refine Soil Fertility Management

John Spargo (right), director of the Penn State Agricultural Analytical Services Lab, and Zack Sanders (left), research technician, conduct soybean yield checks in fertilizer microplots to validate soil test recommendations. Photo: Charlie White

When soybean farmers are able to identify zones within a field with low fertility levels, they can vary the rate of nutrient application to achieve higher yields, more economically. That’s why researchers in Pennsylvania are helping farmers and agronomists learn to garner the right information from various datasets that will identify soil fertility level differences across a field.

“The overall goals are not only to develop fertility management practices, but also to improve methods for zone-based soil sampling within fields and verify established soil and tissue test critical levels for phosphorus (P) and potassium (K) are still valid under modern practices,” says Charlie White, Penn State University Extension soil fertility and nutrient management specialist and principal investigator for research funded by the Pennsylvania Soybean Promotion Board.

White advises farmers to begin by implementing a regular soil testing program and staging that program to get soil test results for timely action. Collecting soil samples in the fall provides opportunity during winter to make plans for fertilizer or lime applications for subsequent crops. 

“Finding out mid-season that there is a soil fertility issue that should have been addressed before planting is not good management,” he says.

To date, White’s research has confirmed that fertilizer recommendations currently suggested by Penn State, if followed by farmers, should be adequate to maintain soybean yield. 

“We did see some evidence that critical soil test levels for P and K, which are soil test levels at which yield losses occur with no fertilizer applied, may need to be raised above current levels,” he says. “However, our current recommendation system still advises maintenance fertilizer applications based on crop removal levels be made when soil test levels are at critical levels.”

White says if maintenance fertilizer recommendations are followed, farmers should be protecting themselves against potential yield losses even if current soil test critical levels are too low. 

“More data are needed to determine whether raising current critical levels is justified,” he says. 

To make the best applications, farmers must understand where nutrient deficiencies lie, White and his colleagues found zones different in soil fertility levels were most strongly correlated to electrical conductivity (EC) soil maps made by such sensors as Veris 3100 or DUALEM. Zones were also sometimes correlated to yield maps created from combine monitors. 

“You wouldn’t be able to detect irregular patterns of these zones from grid sampling,” he adds. “Using higher resolution spatial data, such as the EC or yield maps, can help generate a picture of the natural soil variability in a field better than coarse resolution grid sampling.”

White encourages farmers to consider higher resolution spatial data since many have the equipment to gather yield maps from their fields. The cost of EC soil mapping, which only needs to be done once, is economical when cost is spread over the many years the data can be used.

“We are now starting to evaluate how satellite imagery can be used to define soil fertility zones,” he says. “Satellite imagery is becoming widely available to farmers and agronomists, and some companies are using it to define soil sampling zones. However, we are in the very early stages of learning how to best use this type of data to make informed decisions.”

Published: Oct 12, 2020

The materials on SRIN were funded with checkoff dollars from United Soybean Board and the North Central Soybean Research Program. To find checkoff funded research related to this research highlight or to see other checkoff research projects, please visit the National Soybean Checkoff Research Database.