Eurasian Soil Science

, Volume 46, Issue 5, pp 556–564 | Cite as

An application of PCA and fuzzy C-means to delineate management zones and variability analysis of soil

  • Babankumar S. Bansod
  • O. P. Pandey
Soil Physics

Abstract

Within-field variability is a well-known phenomenon and its study is at the centre of precision agriculture (PA). In this paper, site-specific spatial variability (SSSV) of apparent Electrical Conductivity (ECa) and crop yield apart from pH, moisture, temperature and di-electric constant information was analyzed to construct spatial distribution maps. Principal component analysis (PCA) and fuzzy c-means (FCM) clustering algorithm were then performed to delineate management zones (MZs). Various performance indices such as Normalized Classification Entropy (NCE) and Fuzzy Performance Index (FPI) were calculated to determine the clustering performance. The geo-referenced sensor data was analyzed for within-field classification. Results revealed that the variables could be aggregated into MZs that characterize spatial variability in soil chemical properties and crop productivity. The resulting classified MZs showed favorable agreement between ECa and crop yield variability pattern. This enables reduction in number of soil analysis needed to create application maps for certain cultivation operations.

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References

  1. 1.
    B. Bansod and O. P. Pandey, “An application of fuzzy C-means based clustering technique in smart farming.” Proc. 3rd Int. Conf. on Computer and Electrical Engineering (ICCEE 2010), Chengdu, China, November 16–18 (2010).Google Scholar
  2. 2.
    J. C. Bedek (Ed.), Pattern Recognition with Fuzzy Objective-Function Algorithms (Plenum Press, New York, 1981).Google Scholar
  3. 3.
    B. Boydell and A. B. McBratney, “Identifying potential within field management zones from cotton yield estimates,” Proc. 4th Int. Conf. on Precision Agriculture, pp. 335–343 (1998).Google Scholar
  4. 4.
    T. Doerge, “Defining management zones for precision farming,” Crop Insights 8(21) (1999).Google Scholar
  5. 5.
    J. C. Dunn, “A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters,” J. Cybernetics 3, 32–57 (1973).CrossRefGoogle Scholar
  6. 6.
    K. L. Fleming, D. G. Westphall, D. W., Wiens, L. E. Rothe, J. E. Cipra, and D. F. Heerman, Proc. 4th Int. Conf. on Precision Agriculture, pp. 335–343 (1988).Google Scholar
  7. 7.
    C. W. Fraisse, K. A. Sudduth, and N. R. Kitchen, “Delineation of site-specific management zones by unsupervised classification of topographic attributes and soil electrical conductivity, Trans. ASAE 44(1), 155–166 (2001).Google Scholar
  8. 8.
    J. J. Fridgen, N. R. Kitchen, and K. A. Sudduth, “Variability of soil and landscape attributes within sub-field management zones,” Proc. Int. Conf. on Precision Agriculture, Bloomington, 2000.Google Scholar
  9. 9.
    J. J. Fridgen, C. W. Fraisse, N. R. Kitchen, and K. A. Sudduth, “Delineation and analysis of site-specific management zones,” Proc. 2nd Int. Conf. on Geospatial Information in Agriculture and Forestry, Lake Buena Vista, Florida 10–12 Jan, 2000.Google Scholar
  10. 10.
    R. J. Godwin, G. A. Wood, J. C. Taylor, S. M. Knight, and J. P. Welsh, “Precision farming of cereal crops: a review of a six year experiment to develop management guidelines,” Biosyst. Engin. 84,(4), 375–391 (2003).CrossRefGoogle Scholar
  11. 11.
    D. B. Jaynes, J. M. Novak, T. B. Moorman, and C. A. Cambardella, “Estimating herbicide partition coefficients from electromagnetic induction measurements.” J. Environ. Qual. 24, 36–41 (1994).CrossRefGoogle Scholar
  12. 12.
    D. B. Jaynes, T. S. Colvin, and J. Ambuel, “Yield mapping by electromagnetic induction,” Proc. 2nd Int. Conf., Minneapolis, MN, 27–30 March 1995 (Madison, WI, 1995), pp. 383–394.Google Scholar
  13. 13.
    D. B. Jaynes, T. C. Kaspar, T. S. Colvin, and D. E. James, “Cluster analysis of spatio-temporal corn yield patterns in an Iowa field,” Agron. J. 95, 574–586 (2003).CrossRefGoogle Scholar
  14. 14.
    J. P. Molin and C. N. de Castro, “Establishing management zones using soil electrical conductivity and other soil properties by fuzzy clustering technique,” Sci. Agric. 65,(6), 567–573 (2008).CrossRefGoogle Scholar
  15. 15.
    N. R. Kitchen and K. A. Sudduth, “Predicting crop production using electromagnetic induction,” Proc. f Inform. Agricult. Conf. Urbana IL (1996).Google Scholar
  16. 16.
    N. R. Kitchen, S. T. Drummond, E. D. Lund, K. A. Sudduth, and G. W. Buchleiter, “Soil electrical conductivity and topography related to yield for three contrasting soil-crop systems,” Agron. J. 95, 483–495 (2003).CrossRefGoogle Scholar
  17. 17.
    N. R. Kitchen, K. A. Sudduth, D. B. Myers, S. T. Drummond, S. Y. Hong, “Delineating productivity zones on claypan soil fields using apparent soil electrical conductivity,” Comput. Electron. Agric. 46, 285–308 (2005).CrossRefGoogle Scholar
  18. 18.
    R. M. Lark and J. V. Stafford, “Classification as a first step in the interpretation of temporal and spatial variation of crop yield,” Ann. Appl. Biol. 130, 111–121 (1997).CrossRefGoogle Scholar
  19. 19.
    Li Yan, Shi Zhou, Li Feng, Li Hong-Yi, “Delineation of site-specific management zones using fuzzy clustering analysis in a coastal saline land,” Comput. Electron. Agric. 56, 174–186 (2007).CrossRefGoogle Scholar
  20. 20.
    Jr. Luchiari, A. Shanahan, J. Francis, D. M. Schlemmer, J. Schepers, M. Liebig, A. Schepers, and S. Payton, “Strategies for establishing management zones for site specific nutrient management,” Proc. Int. Conf. Precision Agric., Vol. 5 (Bloomington, 2000).Google Scholar
  21. 21.
    E. D. Lund, C. D. Christy, and P. E. Drummond, “Using yield and soil electrical conductivity maps to derive crop production performance information,” Proc. 5th Int. Conf. Precision Agriculture (Minneapolis, USA, 2000).Google Scholar
  22. 22.
    A. B. McBratney and J. J. deGruijter, “A continuum approach to soil classification by modified fuzzy k-means with extragrades,” J. Soil Sci. 43, 159–175 (1992).CrossRefGoogle Scholar
  23. 23.
    R. A. McBride, A. M. Gordon, and S. C. Shrive, “Estimating forest soil quality from terrain measurements of apparent electrical conductivity,” Soil Sci. Soc. Am. J. 54, 290–293 (1990).CrossRefGoogle Scholar
  24. 24.
    J. D. McNeill, “Rapid accurate mapping of soil salinity by electromagnetic ground conductivity meters,” im Advances in Measurement of Soil Physical Properties: Bringing Theory into Practice (Special Publication 30, SSSA, Madison, WI, 1992), pp. 209–229.Google Scholar
  25. 25.
    I. O. A. Odeh, A. B. McBratney, and D. J. Chittleborough, “Soil pattern recognition with fuzzy c-means: application to classification and soil-landform interrelationship,” Soil Sci. Soc. Am. J. 56, 505–516 (1992).CrossRefGoogle Scholar
  26. 26.
    J. D. Rhoades, D. L. Corwin, and S. M. Lesch, “Geospatial measurements of soil electrical conductivity to assess soil salinity and diffuse salt loading from irrigation,” in Assessment of Non-Point Source Pollution in the Vadose Zone, Ed. by D. L. Corwin, (Geophys. Monogr. 108, Am. Geophys. Union, Washington DC, 1999), pp. 197–215.CrossRefGoogle Scholar
  27. 27.
    P. Roudier, B. Tisseyre, H. Poilve, and J. M. Roger, “Management zone delineation using a modified watershed algorithm,” Precis. Agric. 9(5), 233–250 (2008).CrossRefGoogle Scholar
  28. 28.
    A. R. Schepers, J. F. Shanahan, M. K. Liebig, J. S. Schepers, S. H. Johnson, A. Jr. Luchiari, “Appropriateness of management zones for characterizing spatial variability of soil properties and irrigated corn yields across years,” Agron. J. 96, 195–203 (2004).CrossRefGoogle Scholar
  29. 29.
    J. V. Stafford, R. M. Lark, and H. C. Bolam, “Using yield maps to regionalize fields into potential management units,” (Proc. 4th Int. Conf. on Precision Agriculture) Ed. by P. C. Robin (Madison, WI, 1998), pp. 225–237.Google Scholar
  30. 30.
    J. A. Taylor, A. B. McBratney, and B. M. Whelan, “Establishing management classes for broadacre grain production,” Agron. J. 99, 1366–1376 (2007).CrossRefGoogle Scholar
  31. 31.
    E. Vrindts, M. Reyniers, P. M. Darius, B. H. Frankinet, M.-F. Destain and D. B. Josse, Analysis of Spatial Soil, Crop and Yield Data in a Winter Wheat Field (ASAE Ann. Int. Meeting, ASAE. Nevada, USA, 2003).Google Scholar
  32. 32.
    B. Williams and D. Hoey, “The use of electromagnetic induction to detect the spatial variability of the salt and clay content of soils,” Austr. J. Soil Res. 25, 21–27 (1987).CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2013

Authors and Affiliations

  • Babankumar S. Bansod
    • 1
  • O. P. Pandey
    • 2
  1. 1.Central Scientific Instruments OrganisationChandigarhIndia
  2. 2.School of PhysicsThapar UniversityPatialaIndia

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