Precision Agriculture

, Volume 1, Issue 3, pp 327–338 | Cite as

Method for Precision Nitrogen Management in Spring Wheat: I Fundamental Relationships

  • Richard E. Engel
  • Dan S. Long
  • Gregg R. Carlson
  • Corey Meirer
Article

Abstract

Wheat (Triticum aestivum L.) fields in the semi-arid Northern Great Plains are spatially variable in soil N fertility and crop productivity. Consequently, there is interest in applying variable, rather than uniform rates of fertilizer N across the landscape. Intensive soil sampling as a basis for variable-rate fertilizer management is too costly when compared to the value of wheat in this region. The objective of this research was to determine relationships between yield and protein, and protein and available N as needed to develop a cost-effective variable-rate N fertilizer strategy for spring wheat. A three-year study (1996–1998) was carried out at a site near Havre, Montana, USA (48°30′N, 109°22′W). Treatments consisted of three water regimes, four cultivars, and five fertilizer N levels per water regime in a randomized complete block design with four replicates. Scatter diagrams of relative yield vs. grain protein were consistent with earlier investigators, and indicated protein concentrations at harvest provided a method for indexing N nutrition adequacy (deficiency vs. sufficiency) in wheat. A critical protein concentration of 13.2% was defined using a graphical Cate-Nelson analysis. This value appeared to be consistent across the three water regimes and four cultivars as 159 (88%) of the 180 water×cultivar×N level episodes were in positive quadrants. No correlation could be found between relative yield and protein for episodes below the critical level (r2=0.1). Hence, grain protein concentrations could not be used to predict the magnitude of yield losses from N deficiency. Grain protein content would be useful for prescribing fertilizer recommendations where N deficiency (<13.2% protein) reduces grain yield under semi-arid conditions. Inverse slopes (dy/dx) of the protein-available N curves reveal that it takes 12–18 kg N/ha to change protein 1% (e.g., 12% vs. 13%) where wheat is under water stress during grain fill. The total N requirement could then be computed by summing the N required for raising protein and the N removed by the crop in the year when the grain was harvested.

N sufficiency N deficiency critical protein concentration protein mapping 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. B. Cate, Jr. and L. A. Nelson, North Carolina State University International Soil Testing Series Technical Bulletin 1 (1965).Google Scholar
  2. R. E. Engel, D. S. Long, and G. R. Carlson, Better Crops with Plant Food 81(4), 20 (1997).Google Scholar
  3. R. E. Engel, Agronomy Journal 83, 180 (1991).Google Scholar
  4. D. M. Glenn, A. Carey, F. E. Bolton, and M. Vavra, Agronomy Journal 77, 229 (1985).Google Scholar
  5. R. J. Goos, D. G. Westfall, A. E. Ludwick, and J. E. Goris, Soil Science America Journal 74, 1033 (1982).Google Scholar
  6. R. J. Goos, Journal of Agronomic Education 13, 103 (1984).Google Scholar
  7. D. R. Keeney and D. W. Nelson, in Methods of Soil Analysis, Part 2, edited by A. L. Page (American Society of Agronomy, 1982), p. 643.Google Scholar
  8. T. C. Keisling and B. Mullinix, Soil Science Society America Journal 43, 1181 (1979).Google Scholar
  9. W. E. Larson and P. C. Robert, in Soil Management for Sustainability, edited by R. Lal and F. J. Pierce (Soil Water Conservation Society, Ankeny, IA, 1991), p. 103.Google Scholar
  10. D. D. Malo and B. K. Worcester, Agronomy Journal 67, 397 (1975).Google Scholar
  11. M. P. Miller, M. J. Singer, and D. R. Neilsen, Soil Science Society America Journal 52, 1133 (1988).Google Scholar
  12. D. J. Mulla, A. U. Bhatti, M. W. Hammond, and J. A. Benson, Agriculture, Ecosystems, and Environment 38, 301 (1992).Google Scholar
  13. W. H. Pierre, L. Dumenil, V. D. Jolley, J. R. Webb, and W. D. Shrader, Agronomy Journal 69, 215 (1977).Google Scholar
  14. W. H. Pierre, L. Dumenil, and J. Henao, Agronomy Journal 69, 221 (1977).Google Scholar
  15. S. Pocknee, B. C. Boydell, H. M. Green, D. J. Waters, and C. K. Kvien, in Proceedings 3rd Internal Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust, and W. E. Larson (American Society of Agronomy, Minneapolis, MN, 1996), p. 159.Google Scholar
  16. P. C. Robert, Geoderma 60, 57 (1993).Google Scholar
  17. SAS Institute, SAS/STAT Guide for Personal Computers, Ver. 6 ed. (SAS Institute, Incor., Cary, NC, 1985).Google Scholar
  18. S. W. Searcy, in Proceedings 2nd International Conference on Site-specific Management for Agricultural Systems, edited by P. C. Robert, R. H. Rust, and W. E. Larson (American Society of Agronomy, Minneapolis, MN, 1994), p. 603.Google Scholar
  19. J. V. Stafford, in Proceedings 3rd Int. Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust, and W. E. Larson (American Society of Agronomy, Minneapolis, MN, 1996), p. 595.Google Scholar
  20. F. Steenbjerg, Plant and Soil 3, 97 (1951).Google Scholar
  21. R. Sweeney, and P. Rexford, Journal Association of Analytical Chemists 70, 1028 (1987).Google Scholar

Copyright information

© Kluwer Academic Publishers 1999

Authors and Affiliations

  • Richard E. Engel
    • 1
  • Dan S. Long
    • 2
  • Gregg R. Carlson
    • 2
  • Corey Meirer
    • 1
  1. 1.Land Resources and Environmental SciencesMontana State UniversityBozemanUSA
  2. 2.Northern Agricultural Research CenterMontana State UniversityHavreUSA

Personalised recommendations