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Diagnostic Tools for Determining Appropriate Sidedress Nitrogen Rates

Several tools are available to help determine an appropriate sidedress nitrogen rate for corn.
Updated:
May 27, 2026

Many farmers have learned from the last few years of heavy rainfall during the growing season that keeping the majority of nitrogen (N) for corn in the bag, bin, or tank until sidedressing is one of the best ways to prevent N losses from occurring early in the season. If you decided to split your N applications this spring, mid-June is the time to determine an appropriate sidedress N rate. There are several in-season N availability assessments that can be used in the coming weeks to help make this decision.  The pre-sidedress soil nitrate test (PSNT) and the chlorophyll meter test, are designed to assess the amount of N that is becoming available from mineralization of soil organic matter. In fields with a frequent manure history or that are rotating out of a legume hay crop, significant N mineralization from organic matter can substantially offset the amount of N fertilizer that is required. These tests are not designed to detect how much N fertilizer that was applied at planting is still available in the soil profile, however.  For those who applied their entire projected N fertilizer requirement at planting, assessing N availability and determining whether there is a need to sidedress additional N becomes more complicated and will be discussed at the end of the article.

The PSNT test involves taking a soil sample to 12" deep and sending the sample to a lab for analysis of the soil nitrate concentration.  The test should be taken when the corn crop is 12" tall, or about the V5 stage.  For normal planting dates, the sampling window usually occurs in mid-June.  When relatively little N has been applied at planting (<50 to 60 lbs N/ac), the soil nitrate level at this growth stage is an indicator of the rate of N mineralization thus far in the growing season and this value has been calibrated to predict future N mineralization throughout the growing season.  The test-predicted N mineralization level is then used to adjust the sidedress N requirement.  Soil samples collected for the PSNT should be dried immediately after collection (preferably before sending to the lab) by spreading the soil in a thin layer on a paper bag, paper plate, or newspaper, and using an electric fan to speed drying.  Alternatively, moist soil samples can be kept refrigerated and you can drop them off in person at the soil testing lab.  The point here is to prevent soil microbes from continuing to mineralize and nitrify N in the soil sample between collection in the field and analysis in the lab.  It is also important not to collect a soil sample immediately after a heavy rainstorm, since the rain can leach nitrate into the subsoil below the 12" sampling depth.  Rather, wait several days after a heavy rainstorm so nitrate levels in the top 12" of soil can recover.  The PSNT fact sheet ("Pre-sidedress Soil Nitrate Test for Corn") has more information about the test and a formula for calculating a recommended sidedress N application rate based on the field history, yield goal, and the PSNT result.

Another option for assessing N mineralization in the soil and determining how much N to sidedress is the chlorophyll meter test.  With this test, a hand-held sensor clips onto the leaf blade of a corn plant and measures the chlorophyll content of the leaf.  Chlorophyll is the nitrogen-rich molecule in a plant leaf that is essential for photosynthesis and gives the leaf it's green color.  This test is only reliable when less than 15 lbs/ac N has been applied at planting, otherwise the greenness of the leaf doesn't accurately reflect N mineralization from the soil.  When soil N mineralization rates are high, as detected by greater chlorophyll content of the corn leaf, the sidedress N recommendation is reduced.  More details about this test, along with the formulas for calculating a sidedress N recommendation, are available in the chlorophyll meter article ("The Early Season Chlorophyll Meter Test for Corn").

As described earlier, these tests are designed to be used when a minimal amount of N is applied at planting.  If you applied more than 50 to 60 lbs N/ac at planting when using the PSNT or more than 15 lbs N/ac when using the chlorophyll meter, the tests may say you have sufficient N available when you really don't.  In cases where large quantities of N were applied at planting, and there is a desire to determine whether additional N needs to be sidedressed to achieve the desired yield goal, computer models are the only additional diagnostic tool that may be available.

Computer models of the N cycle take into account real-time, high resolution rainfall and temperature data for a location.  Models such as Adapt-N and the Granular Agronomy Nitrogen Model (previously branded as Encirca) are now widely available and being increasingly used for N management decision making.  These computer models are a compilation of the best available science of how the N cycle operates and the expert judgement of model developers on how to represent these N cycling processes as algorithms in the computer code.  Ultimately, the success of these models also depends on having accurate inputs, including soil profile characteristics and previous N management practices, and being able to interpret the outputs correctly.  Because of this, N modeling services in some cases may only be available through trained professionals that can help assure the integrity of the inputs and interpretation of the outputs.  While there is much promise in the computer N models tools, there is still much to be learned and improved upon.  If you are planning to use computer N models in your decision making this year, I suggest setting up a simple on-farm experiment to compare the model suggested sidedress rate with your typical practice or another one of the tools such as the PSNT or chlorophyll meter test.  Experimenting with these and other N management tools is an important part of an adaptive management process, through which we can collectively improve upon and build greater confidence in our N management decision making.