Application of Regression Tree in Modelling and Mapping of Cation Exchange Capacity of Soils in Akwa Ibom State, Nigeria

Authors

  • Udeme Akpan Department of Soil Science and Land Resources Management, University of Uyo , Akwa Ibom State, Nigeria
  • Uwah I.D. Department of Agricultural Technology, Akwa Ibom State College of Technology, Nung Ukim Ikono, Akwa Ibom State, Nigeria
  • Nkannga N. A. Department of Soil Science and Land Resources Management, University of Uyo , Akwa Ibom State, Nigeria

Keywords:

modelling, regression tree, CEC, soil of Akwa Ibom State

Abstract

 Regression tree   was used in modelling and mapping cation exchange capacity of soils in Akwa Ibom State, Nigeria.The aim was to provide an alternative techinque of estimating ECEC from more readily available soil data and map the distribution for site-specific soil management. The study area (Akwa Ibom State) was grouped into four major mapping units based on parent materials, namely:  coastal plain sand, sandstone, shale and beach ridge sand. Each parent material (major mapping unit) was subdivided into four commonly practice landuse types/soil management systems namely homestead or compound farmland, oil palm plantation, secondary forest of 3 years and above and cultivated farmland.  In each landuse type/soil management system, mini- soil profile pit was dug to a depth of 100cm at representative location. Soil samples were collected from designated depths of 0-20, 20-60 and 60-100 cm. A total of 144 samples were generated for laboratry analysis. The study revealed that ECEC can be predicted using soil organic carbon, clay, silt and soil pH in the study area. The results of independent variable importance to the model showed that organic carbon was the most significant predictor of ECEC with 22.1 % contribution, followed by clay with 17.3 %, followed by silt with 8.5% while soil pH was the least predictor of ECEC with 0.8% contribution in the study area. Based on the model, organic carbon content predicted ECEC of 32.4 cmol/kg in sandstone soil while organic carbon in combination with clay predicted ECEC of 40.24 cmol/kg in soils developed from shale parent material. In coastal plain sand soils, organic carbon in combination with clay and silt predicted ECEC of 24.3 cmol/kg. In beach ridge sand soils, organic carbon in combination with clay and silt predicted ECEC of 17.8 cmol/kg. The model showed that organic carbon content was the only significant predictor of ECEC in sandstone soils while organic carbon in combination with clay made significant prediction of ECEC in shale parent material. In coastal plain sand and beach ridge sand soils, Organic carbon in combination with clay and silt made significant prediction of ECEC. In the application of the model, independent variables included in the final model and measured in the same unit should be used.

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References

Bell, M.A., and Van Keulen J. 1995. Soil predotransfer functions for Mexican soils. Soil Sci. Soc. Am. J. 59:865-871.

Breiman, L.; Friedman, J.; Olshen, R. And Stone, C. 1984. Classification and Regression Trees. Belmont, CA: Wadsworth Int. Group.

Charman P. and Murphy, B. 2007. Soils: The Properties and Management. Oxford University Press, South Melbourne, Victoria. 3205pp.

Diplaris, S.; Symeonidis, A.L.; Mitas, P.A.; Banos, G. and Abas Z.2006. A decision based alarming system for the validation of national genetic evaluation. Journal of computer and electronics in agriculture 52: 21-35

Drake, E. H., and H. L. Motto. 1982. An analysis of the effect of clay and organic matter content on the cation exchange capacity of New Jersey soils. Soil. Sci. 133:281- 288.

Enwenzor, W. O., Ochiri, A. C., Opuwaribo, E. E., Udo, E.J. 1980. A review of fertilizer use on crops in southern zone of Nigeria. In: Literature Review on Soil Fertility Investigation in Nigeria. FMANR. Lagos.6.

Huang, J.; Fang, H and Fan, X. 2010. Decision forest for classification of gene expression data. Computers in Biology and Medicine, Vol. 36, Issue 8, 698-704

John, B., Yamashita, T., Ludwig, B., and Flessa, H. 2005. Storage of organic carbon in aggregate and density fractions of soils under different types of land use. Geoderma. 128: 63-79

Keller, A., B. Von steiger, S.T. Van der Zee, and R. Schulin. 2001. A stochastic empirical model for regional heavy metal balances in agroecosystems. J.E.Q, 30: 1976-1989.

Krogh, L., B.M. Henrik, H.G. Mogens, 2000. Cation- exchange capacity pedotransfer functions for Danish soils. Acta Agriculturae Scandinavica, Section B- Plant Soil Science, 50; 1-12.

Manrique, L. A., C. A. Jones and P. T. Dyke. 1991. Predicting cation exchange capacity from soil physical and chemical properties. Soil Sci. Soc. Am. J. 55:787-794.

Pachepsky, Y.A. and W.J. Rawls. 1999. Accuracy and reliability of pedotransfer functions as affected by grouping soils. Soil Sci. Soc. Am. J, 63: 1748-1757.

Parfitt, R.L., D.J. Giltrap, and J.S. Whitton. 1995. Contribution of organic matter and clay minerals to the cation exchange capacity of soils. Commun. Soil Sci. Plant Anal. 26:1343–1355.

Rengasamy, P. and Churchman, G.J. 1999. Cation Exchange Capacity, Exchangeabl Cations and Sodicity. In Soil Analysis: an Interpretation Manual. Csiro Publishing. Collingwood, Vic. 147-157

Stevenson, F.J. 1982. Humus Chemistry- Genesis, Composition and Reactions. John and Wiley and Sons, New York, pp 158

Soil Survey Staff. (2006). Soil Taxonomy. A Basic System of Soil Classification for Making and Interpreting Soil Surveys. USDA Agric. Handbook. No.436, second edition. U.S.Govt. Printing Office, Washington, D.C. 871.

Solomon, D., Fritzsche, F., Tekalign, M., Lehmaann, J.& Zech, W. 2002. Soil organic matter composition in the subhumid Ethiopian highlands as influenced by deforestation and agricutural management. Soil Sci. Soc. Am. J. 66, 68-82

Thomas G. W. 1982. Exchangeable cation. Methods of Soil Analysis Part 2, Agronomy, Monography 9 (2nd edition). SSSA Madison, Wisconsin and USA, pp 159-165

Nelson, D.W., Sommers, L. E. 1996. Total organic carbon and organic matter. In: Methods of Soil Analysis, 2nd Ed. D. L.Spans; A.L. Page; P.A. Helmke; R.H. Leoppert; P.N. Soltanpour; M.A. Tabatabai & C.I. Johnson, Eds. American Society of Agronomy: Madison, WI, US.A pp. 961-1010.

Oades, J.M. 1993. The role of soil biology in the formation, stabilization and degradation of soil structure. Geoderma, 56, 377-400.

Petters, S.W.; Usoro, E.J.; Udo, E. J.; Obot, U. W. & Okpon, S.N. 1989. Akwa Ibom State Physical Background, Soils and Land Use Ecological Problems. Technical Report of the Task Force on Soils and L anduse. Govt. Printer Uyo, pp 602.

Udo, E. J., Ibia, T.O., Ogunwale, J.A., Ano, A.A. & Esu I. E. 2009. Manual of Soil, Plant and Water Analysis. Sibon Books Limited, Lagos, pp 82-92

Whitebread, A.M., Lefroy, R.D.B. & Blair, G.J. 1998 . A survey of the impact of cropping on soil physical and chemical properties New South Wales. Aus.J. Soil Res. 36,669-681.

Wagner, B., V.R. Tranawski, V. Hennings, U. Muller, G. Wessolek,.and R. Plagge. 2001. Evaluation of pedotransfer functions for unsaturated soil hydraulic conductivity using an independent data set. Geoderma, 102: 275-279.

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Published

2019-09-30

How to Cite

Akpan, U., I.D., U., & N. A., N. (2019). Application of Regression Tree in Modelling and Mapping of Cation Exchange Capacity of Soils in Akwa Ibom State, Nigeria. International Journal For Research In Agricultural And Food Science, 5(8), 71–92. Retrieved from https://gnpublication.org/index.php/afs/article/view/960