Correlation and Calibration
Correlation is a relationship between the amount of nutrient extracted from soil by a laboratory test and nutrient uptake by plants in the greenhouse or field and/or crop yield. If such a relationship cannot be established, the chemical procedure has little or no usefulness. Sometimes the relationship can be established only for one nutrient and one crop and on a particular group of soils. If this limitation is known and recognized, then the soil test should only be used for those limited conditions.
A useful correlation has been established between the Bray and Kurtz No. 1 phosphorus test and percent of maximum yield of soybeans, corn, and wheat grown under Nebraska climate conditions and non-calcareous soils. The correlations shown in Figure 9.2 are useful in determining when soil phosphorus, as assessed by soil test, is adequate for maximum yields.
Crops vary in their responses to the amount of phosphorus in the soil measured by the Bray and Kurtz No. 1 procedure. Corn and soybean yields change rapidly with small differences in the amount of phosphorus extracted. For corn or soybeans grown on soils with a Bray and Kurtz #1 of 5 ppm phosphorus, fertilization would be expected to increase yield from about 65 percent of maximum to close to maximum for that site. When soil tests are above 15 ppm, yield is already at about 95 percent of maximum. The rate of change in the yield of wheat or other small grains is not as large. At 15 ppm, wheat is still only at 75 percent of maximum yield. In order to get these types of response curves, correlation research must be conducted with many crops at many sites over many years.
Calibration is a means of establishing a relationship between a given soil test value and the yield response from adding nutrient to soil as fertilizer. The data in Table 9.2 give the pounds of alfalfa hay produced from several rates of applied phosphorus when the assessed soil phosphorus level was eight ppm. Such field experiments are repeated where soil phosphorus levels will range from two to 30 ppm. Optimum P2O5 application would be from 60 to 80 pounds per acre at this site. However, many trials are needed to establish general recommendations for a region. When similar experiments are conducted over many sites, analysis of crop response allows researchers to predict needed fertilizer at various soil phosphorus levels. The result of the calibration effort is to determine the amount of fertilizer phosphorus needed at various soil levels to produce maximum yields.
|Amount of phosphorus applied (pounds/acre P2O5)||Alfalfa hay yield (pounds/acre)||Percent of maximum yield|
Table 9.2. An example of calibration showing the relationship between a given soil test and the yield response from adding a nutrient to a soil1 (Alfalfa)
18 ppm Bray and Kurtz #1
The critical point is shown in Figure 9.2. The critical point is where soil test values delineate responsive soils — those where fertilizer additions increase yields — and nonresponsive soils. There are many ways to determine critical values, but their calculation is beyond the scope of this lesson.
When the calibration procedure is completed, one can place soil phosphorus levels into categories of very low, low, medium, or high. These categories simplify recommendations and probably reflect the reality of the variable nature of soils. Table 9.3 gives an example interpretation for small grain.
|Assessed soil phosphorus level||Nutrient index levels||Meaning of the index level for small grain|
|0 to 5||very low||applying phosphorus to a crop will be beneficial over 90 percent of the time.|
|6 to 15||low||applying phosphorus will be beneficial 75 - 95 percent of the time, depending on crop and growing conditions|
|16 to 24||medium||applying phosphorus has about a 50-50 chance of being beneficial in growth or yield|
|Greater than 25||high||the effects of applied phosphorus will be beneficial less than 10 percent of the time|
Table 9.3. Categories of soil phosphorus levels showing chances of small grain yield increases from fertilzers applications.
The increase in yield expected from a specific nutrient application will change as soil test index levels change from low to medium to high. The amount of nutrient needed from fertilizer in each soil test index is illustrated in Figure 9.3.
By combining correlation and calibration research, we can predict the probability of a response from applying a given nutrient. In addition, we can suggest the most probable fertilizer to produce maximum economic yield. Due to the changing value of a specific crop and cost of fertilizer, recommendations may change over time for the same soil test value.
By conducting many of these experiments, scientists can determine the probability of increased yields at a specific soil test level and the amount of fertilizer needed to achieve that yield. Due to other factors besides soil test level, there will be considerable variability in crop response at any soil test level. Proper interpretation of soil test results includes other management factors such as risk, climate and economics. Without a research database, these recommendations are not possible, and maximum economic returns are not going to be achieved.