A variable-rate decision support tool
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Profitable precision or variable application of inputs depends on many factors; however, the inherent variability in a soil and or crop property and the relative responsiveness of yield to fertilizer inputs at different soil concentration levels are the most important factors in influencing economic gain. Generally, the greater is the spatial variation in the property influencing the input rate, the greater is the potential economic return from precision application compared to uniform application of an input. Based on a quantitative assessment of the spatial variation in soil properties that influence rates of input, a variable-rate decision support tool (VRDST) was developed to: (1) assess the potential profitability of variable-rate compared to uniform application and (2) identify the economic optimal uniform application rate if this is selected. The VRDST was evaluated using spatially distributed soil data from selected fields in North Carolina. Net return from variable-rate application and the economically optimal uniform rates are illustrated. Varying fertilizer cost, crop price and sampling costs greatly influenced net return from variable-rate application.
- Attanandana, T. (2007). Empowering farmer leaders to acquire and practice site-specific nutrient management technology. Jounal of Sustainable Agriculture, 30, 87–104. doi:10.1300/J064v30n01_08. CrossRef
- Comis, D. (1999). Model takes the guesswork out of fertilizing. Agricultural Research, 47, 15.
- Dahnke, W. C., & Olson, R. A. (1990). Soil test correlation, calibration, and recommendations. In R. L. Westerman (Ed.), Soil testing and plant analysis (3rd ed., pp. 45–72). Madison, WI: Soil Science Society of America.
- Hardy, D. H., Tucker, M. R., Stokes, C. E. (2003). Crop fertilization based on North Carolina soil tests. NCDA & CS Agronomic Division. Retrieved March 14, 2009, from http://www.ncagr.com/agronomi/obook.htm
- Havlin, J. L., Beaton, J. D., Tisdale, S. L., & Nelson, W. L. (2005). Soil fertility and fertilizers: An introduction to nutrient management (7th ed.). Upper Saddle River, NJ: Prentice Hall.
- Hergert, G. W., Pan, W. L., Huggins, D. R., Grove, J. H., & Peck, T. R. (1997). Adequacy of current fertilizer recommendations for site-specific management. In F. J. Pierce & E. J. Sadler (Eds.), The state of site-specific management for agriculture (pp. 283–300). Madison, WI: American Society of Agronomy-Crop Science Society of America-Soil Science Society of America (ASA-CSSA-SSSA).
- Hoffman, M. L. (1991). Weed population and crop yield response to populations from a weed control decision aid. Agronomy Journal, 91, 386–392.
- Larson, J. A. (2005). A computer decision aid for the cotton yield monitor investment decision. Computational Electronics Agriculture, 48, 216–234. doi:10.1016/j.compag.2005.04.001. CrossRef
- Lowenberg-DeBoer, J., & Swinton, S. M. (1997). Economics of site-specific management in agronomic crops. In F. J. Pierce & E. J. Sadler (Eds.), The state of site-specific management for agriculture (pp. 369–396). Madison, WI: ASA-CSSA-SSSA.
- Parkin, T. B., Meisinger, J. J., Chester, S. T., Starr, J. L., & Robinson, J. A. (1988). Evaluation of statistical estimation methods for log normally distributed variables. Soil Science Society of America Journal, 52, 323–329. CrossRef
- A variable-rate decision support tool
Volume 10, Issue 4 , pp 356-369
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- Variable application
- Decision support
- Economic return
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