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Optimal Sampling Under a Geostatistical Model

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  • Gregory R. Pautsch
  • Bruce A. Babcock
  • F. Jay Breidt

Abstract

Soil sampling has long been advocated as a means of improving the efficiency of fertility management decisions by better matching fertilizer applications with crop nutrient requirements and nutrient availability. Advances in mapping and sensing technologies have renewed interest in soil sampling as a means of moving to variable rate technologies (VRT) whereby a farmer varies fertilizer applications across space and/or time. This paper develops a framework for determining the optimal number of soil samples when applying nitrogen fertilizer under a variable rate program.

Suggested Citation

  • Gregory R. Pautsch & Bruce A. Babcock & F. Jay Breidt, 1998. "Optimal Sampling Under a Geostatistical Model," Center for Agricultural and Rural Development (CARD) Publications 98-wp200, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  • Handle: RePEc:ias:cpaper:98-wp200
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    References listed on IDEAS

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    4. Babcock, Bruce A. & Pautsch, Gregory R., 1998. "Moving From Uniform To Variable Fertilizer Rates On Iowa Corn: Effects On Rates And Returns," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(2), pages 1-16, December.
    5. Sergio H. Lence & Dermot J. Hayes, 1994. "The Empirical Minimum-Variance Hedge," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 94-104.
    6. Bruce A. Babcock & Alfred M. Blackmer, 1994. "The Ex Post Relationship between Growing Conditions and Optimal Fertilizer Levels," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 16(3), pages 353-362.
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    8. Bruce A. Babcock & Alicia L. Carriquiry & Hal S. Stern, 1996. "Evaluation of Soil Test Information in Agricultural Decision‐Making," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 447-461, December.
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