Illinois grain producers face a series of difficult and complex decisions each growing season. All these decisions can have a major impact on yields and overall profitability of the operation. These decisions can range from what variety to plant, when to plant, and what inputs to apply during the growing season. Farmers can use many different sources of information, such as soil tests and gained knowledge, to determine if fertilizers need to be applied and when they should be applied. While these help to paint the picture for a producer, the crop itself is the best source to determine how much fertilizer is being used and if more is needed. Three recent research studies explore how corn plants at various stages during the growing season can be used to guide fertilizer decisions for the current and future growing seasons. This post will examine these studies and highlight the practical findings that producers can consider when they are setting their fertilizer strategy for the next growing season.
Early-Season Evaluation
Nitrogen is perhaps the most important macronutrient that influences corn growth and yield, so much so that it is the primary focus of fertilizer applications for corn producers. However, in-field variation in soil type, topography, and rainfall means that nitrogen availability can differ greatly across a field. Furthermore, losses due to leaching and denitrification makes the decision of when and how much nitrogen to apply more complicated. Having enough nitrogen at the right time for a plant to use it is extremely difficult to figure out. While methods such as soil tests and leaf tissue sampling help determine available nitrogen, there are still gaps in the information they provide.
A study published in Precision Agriculture in 2025 examined how incorporating data gathered from unmanned aerial vehicles (UAVs or drones) from two sites in Indiana can further determine available nitrogen and nitrogen uptake by corn plants. Their hypotheses included that data gathered at the V4-V5 growth stages (mainly plant height, canopy cover, and vegetative indices) can help predict biomass and nitrogen uptake with enough accuracy to guide in-season application decisions. Both locations had approximately 40 lbs. of 28% UAN applied before planting. The Shelby location received around 18 lbs. of UAN per acre prior to planting, along with approximately 170 lbs. of UAN per acre as a sidedress application. The PPAC location only received a sidedress application of 145 lbs. of UAN per acre.
Across both research sites, the authors found that plant height, canopy cover factor (CCF), and UAV images were all better at calculating crop biomass than satellite imagery. CCF is a measure of how much of a certain area is covered by the crop’s canopy and leaves. The authors note that this reinforced previous research that these physical measurements were more reliable than statistical models. Additionally, the authors found that images captured by UAVs were better for measuring CCF due to a higher resolution than satellite images. The authors noted that there was no reliable way to measure nitrogen concentration because it was too early in the season. For measuring nitrogen uptake, plant height and CCF were again more statistically reliable than other methods. This study highlights how, at the earlier growth stages, these physical measurements can be accurate and effectively used to guide decisions for later in the season.
Data for Variable Rate Applications
It is no secret that input prices have been fluctuating and higher than normal. Global conflicts, trade uncertainty, and domestic economic conditions all contribute their piece to the increase in costs that row crop producers face. One technology producers can adopt on their operation is a variable rate (VR) applicator for fertilizers. Rather than applying a single rate of a fertilizer across an entire field, VR applicators apply different rates depending on their location in the field. This means that parts of the field that need more fertilizers receive them, while parts that need less receive less. This can make fertilizer applications more efficient, reduce costs, and minimize the risk of overapplication.
A 2025 study published in the Precision Agriculture journal examines the profitability of using VR technologies. The authors examined which of the two primary sources of data for VR applications is more important for creating these applications and thus more important for profitability. These sources are previous yields from yield maps and normalized difference vegetation index (NDVI), which is a measure of nitrogen needs and plant vigor. Together, these sources give an idea of where nitrogen is needed and where it is sufficient. This study examined VR applications across 13 different field sites using a control treatment of nitrogen (that utilized both sources), a treatment using only yield maps, and a treatment using only NDVI to grow corn.
The authors noted that weather across the various years and sites for this study have affected the results of study. As has been mentioned in a previous blog post, the availability of nitrogen can vary depending on fertilizer type and moisture. However, despite these variations, the study found that NDVI improves profitability during “normal” growing conditions. When conditions deviate from the norm, data from yield maps are more important for profitability. No matter the weather conditions, having access to both sources of data are crucial for accurate and appropriate VR nitrogen applications.
Using Corn Stalks After Harvest
Producers can use many different methods to evaluate nutrient availability before planting and during the growing season. Soil testing and plant tissue analysis offer important insights to nutrient availability and plant uptake, but they are only a snapshot in time, and may not paint the full picture. A study published in the Agronomy Journal in 2026 examined using corn stalk tissue sampling after harvest to help evaluate nutrient uptake during the growing season. In particular, the study looked at using stalk analysis for detecting potassium and nitrogen uptake by utilizing deionized water or calcium chloride. The authors believed using stalk analysis to accurately determine potassium uptake because of how a corn plant stores potassium. When there is excess potassium, the corn plant will store potassium in the plant tissues mainly in the lower stalks.
This study covered two growing seasons across three sites located across Arkansas. Results from all sites showed a strong correlation between stalk potassium concentration and ear-leaf potassium, showing that testing the stalk tissue is just as reliable as testing leaf tissue. The results also showed that using deionized water was the only method that accurately detected both potassium and nitrogen concentrations in stalk tissue, while calcium chloride could only accurately detect nitrogen concentration. Therefore, using stalk tissue analysis to further paint the picture when making better fertilizer decisions.
This blog post analyzed three research studies that focused on using a corn plant as a tool to determine fertilizer decisions for the future. As input prices have continued to increase in recent years, producers have been utilizing various sources of data and information to help inform their decisions on applying fertilizers. The information in these research studies offer additional information not only on methods to evaluate corn plants for fertilizer decisions, but also which sources of information matter most during certain conditions. As producers continue to feel the strain of increasing input costs, they can look to these studies for yet more tools in their toolbox when it comes to making fertilizer decisions for the year ahead.