Comparing the Value of Soil Test Information Using Deterministic and Stochastic Yield Response Plateau Functions

Abstract

We determined the value of soil test information for potassium (K) in upland cotton production using the linear response plateau (LRP) and linear response stochastic plateau (LRSP) functions. A stochastic dynamic programming model was used to determine the net present value to K fertilizer when optimal K was applied with knowledge about K carryover. Using K carryover information for K application decisions increased net present value and helped maintain steady levels of soil K. The LRSP function fit the data better than the LRP, and the value of soil testing was $27 ha-1 lower over ten years using the LRSP.

Keywords

• cotton
• dynamic programming
• linear response stochastic plateau
• potassium
• soil test information