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Soil test results and the law of diminishing returns

Dustin Sawyer for Progressive Forage Published on 30 March 2017
What is the probability that yield will increase if we apply fertilizer?

A recent look at some agricultural statistics showed that, as of 2014, roughly half of the farmland in Wisconsin is being actively managed through soil testing. Given that you’re likely already engaged in soil analysis on a regular basis, this article may come across as review.

For those of you who are just starting with an actively managed soil analysis program, I hope this can serve as a bit of a guide as you venture into the worlds of science and statistics.

Given all of the advances that have been made in application equipment, mapping software and fertilizer products, it can be easy to get caught up in the excitement surrounding soil testing. Just the past five years have seen significant improvement in variable rate, or precision application of soil amendments.

Amid all the excitement, it’s important to take a step back once in a while and remind ourselves of just what it is that we’re trying to do. What are the origins of soil testing, how does it work and, most importantly, how do we properly interpret the data? As with all good stories, let’s start at the beginning.

Why do we test our soils? Soil test results are used in a variety of ways these days. Phosphorus levels determine when and where manure can be applied, and GPS-referenced sample points are used to micromanage a field to an unprecedented degree.

While these are worthwhile applications, the original intent of soil testing is to answer a very basic question: What is the probability that yield will increase if we apply fertilizer?

If gaining yield was as simple as applying more fertilizer, it would be no problem to get 20 tons of alfalfa whenever we wanted. The trouble is with the law of diminishing returns.

Figure 1 shows the law of diminishing returns in action in a silage production system. It simply means that as effort increases (in this case, effort is fertilizer additions), the return on that effort becomes less and less.

The law of diminishing returns portrayed as fertilizer is applied to silage

Soil testing tells us where the field in question currently lies on the graph. If the soil test result shows there is not much of a nutrient, there is a high probability that adding fertilizer will increase yield.

There comes a point, however, where the probability of a yield increase becomes small enough that the economics of a fertilizer addition no longer make sense. This is known as the critical point.

The critical point is what most soil test interpretations deem to be the optimum soil nutrient level. If a soil test falls short of the critical point, the result will be placed in a low or deficient category. This means there is a good probability of seeing a benefit from fertilizer additions.

On the contrary, a soil test result above the critical point will have a lower probability of seeing benefit from a fertilizer addition. The next step is to turn these probabilities into actionable items in the field.

Most interpretation strategies are based upon a “build and maintain” ideology. This means soil nutrient levels are slowly moved toward the critical point and then held there.

The distance from the critical point is a primary factor in determining the fertilizer recommendation. A very low-testing soil will result in a higher fertilizer recommendation than a high-testing soil – no surprises there.

The critical point can be difficult to determine, and the soil test result is only a part of it. The probability of a response to fertilizer depends on many other factors, including the soil type, the geographic location, the cropping system and the rotation. Chief among these factors is the cropping rotation.

Forage production removes a lot of nutrients from the soil, so a lot of nutrients will need to be put back. This is known as crop removal and has a major influence on fertilizer recommendations.

For example, a soil test potassium value of 105 parts per million (210 pounds per acre) would be considered optimum for corn grain production but is low for silage production. That means a silage operation has a higher probability of seeing a response to additional potassium than a grain operation would.

The recommended potassium application rate for the silage operation would exceed what the crop is going to remove in the next growing season with the intent of building the potassium levels toward optimum. Of note, the grain operation would still have a moderate potassium application recommendation – just enough to cover what will be lost through harvest but no additional “build” amount.

When it comes to interpreting soil test results, information about the cropping system plays a role just as important as the soil tests themselves. For the best possible interpretation of a soil test, it’s best to provide your lab with as much information as possible.

Yield goals and crop rotations help to understand what the nutrient removal will be. Any additional information, such as manure applications or use of cover crops will help to further dial in the critical point and ensure the highest accuracy of the soil test interpretation.

Fertilizer applications are a lot like playing the stock market: We make an investment now hoping it will pay off in the future. Using all of the information at our fingertips will help to get the most out of soil testing and perhaps give the edge that’s needed in an uncertain world.  end mark

PHOTO: The original intent of soil testing is to answer a very basic question: What is the probability that yield will increase if we apply fertilizer? If gaining yield was as simple as applying more fertilizer, it would be no problem to get 20 tons of alfalfa whenever we wanted. The trouble is with the law of diminishing returns. Photo by Mike Dixon.

Dustin Sawyer
  • Dustin Sawyer

  • Laboratory Director
  • Rock River Laboratory Inc.
  • Email Dustin Sawyer

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