PO 19. Recognize how the following affect soil test interpretation.

  1. Probability of crop response to added nutrients
  2. Estimate of nutrient sufficiency level
  3. Results reported as ppm or lbs/acre
  4. Within-field variability
  5. Laboratory choice
  6. Environmental risk
  7. Extraction method

An agronomic soil test is an INDEX of nutrient availability: something we can measure that is correlated with a likeliness of a crop response.  An agronomic soil test is NOT a measure of the total amount of a nutrient in the soil.

  • For instance, a random soil sample from the Cornell database had a total P test of 550 mg kg-1 (1100 lbs/acre).  The Cornell Morgan test P level, however, was only 32 mg kg-1 (64 lbs/acre).

An agronomic soil test is NOT a measure of the total amount of soil nutrient available to the crop.

  • For instance, Cornell scientists grew a 25 ton corn crop without additional P.  On this field, the Cornell Morgan test P was 15 lbs P/acre, but calculations proved that the crop would have removed 47 lbs P/acre.

The probability of crop response to added nutrients is estimated when soil tests are classified as high, medium, or low.  These classifications are matched with recommended fertilizer rates.  Other factors, such as irrigation, may influence the availability or loss of nutrients in a soil, and can further change the recommended fertilizer rate; tables or equations are used to arrive at the final rate.

The estimate of nutrient sufficiency level affects the likelihood of a crop response.  As nutrient sufficiency increases (i.e. a high test level), the probability for crop response to fertilizer decreases, and the soil test recommendation becomes less reliable.

The units used in soil test reports and fertilizer recommendations may vary, as already mentioned.  Conversion equations can be found in PO 15.

High variation within the field being tested will decrease the accuracy and reliability of the soil test recommendation.  PO 16, 17, and 20 emphasize the importance of proper soil sampling techniques to reduce variability and poor representation.

 


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