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Desert
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Esfandiarpour, I., Ranjbar Khorasani, M., Shirani, H. (2017). Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system. Desert, 22(1), 135-143. doi: 10.22059/jdesert.2017.62190
I. Esfandiarpour; M. Ranjbar Khorasani; H. Shirani. "Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system". Desert, 22, 1, 2017, 135-143. doi: 10.22059/jdesert.2017.62190
Esfandiarpour, I., Ranjbar Khorasani, M., Shirani, H. (2017). 'Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system', Desert, 22(1), pp. 135-143. doi: 10.22059/jdesert.2017.62190
Esfandiarpour, I., Ranjbar Khorasani, M., Shirani, H. Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system. Desert, 2017; 22(1): 135-143. doi: 10.22059/jdesert.2017.62190

Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system

Article 13, Volume 22, Issue 1, Winter and Spring 2017, Page 135-143  XML PDF (260.18 K)
Document Type: Research Paper
DOI: 10.22059/jdesert.2017.62190
Authors
I. Esfandiarpour email 1; M. Ranjbar Khorasani2; H. Shirani3
1Soil Science Department, Vali-e-Asr University
2Former MSc Student of Soil Science Department, College of Agriculture, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
3Vali-e-Asr University, Rafsanjan, Iran
Abstract
The main purpose of the current research is comparing the results of Artificial Neural Network (ANN) with Adaptive Neuro-Fuzzy Inference System (ANFIS) with regard to determination of the importance of soil properties affecting clay dispersibility. After taking samples from two depths of 0-40 and 40-80 cm, the spontaneous and mechanical dispersions of clay were recorded using both weighing and turbidimetric methods. To determine the degree of importance of soil properties affecting clay dispersibility, first ANNs and ANFIS in MATLAB Software were determined, using all research variables. After determining less effective properties and omitting them, the mentioned networks with the remaining variables including percentage of clay and sand, soil reaction, Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) were measured and the degree of importance of each variable in clay dispersibility was determined. Finally, the results of ANNs and ANFIS were compared by calculation of validation parameters. Existence of high correlation between calculated values for weighing and turbidimetric methods showed a linear relationship between the two methods. In general, in both depths and for both weighing and turbidimetric methods, the sensitivity of clay dispersibility to the percentage of the clay, sand and SAR, was higher than any other variable. Although the results obtained from the validation statistics indicate high accuracy of both ANN and ANFIS models, the last model showed relatively better results as compared to ANN model.
Keywords
Arid regions; Dispersible clay; Land degradation; Neuro-fuzzy models; Sodic soils
Main Subjects
Agriculture
References
Agassi, M., I. Shainberg, J. Morin, 1981. Effect of electrolyte concentration and soil sodicity on the infiltration rate and crust formation. Soil Science, 45; 848-851.

Alipour, H., S.J. Hosseinifard, 2006. Diagnosis of Nutrient Deficiency in Pistachio, 2 nd ed., Iran's Pistachio Research Institute, Rafsanjan, Iran. 53 pp.

Amezketa, E., R. Aragüés, R. Gazol, 2004. Infiltration of water in disturbed soil columns as affected by clay dispersion and aggregate slaking. Spanish Journal of Agricultural Research, 2; 459-471.

Amezketa, E., R. Aragues, R. Carranza, B. Urgel, 2003. Chemical, spontaneous and mechanical dispersion of clays in arid-zone soils. Spanish Journal of Agriculture Research, 1; 95-107.

Ayars, J.G., R.B. Hutmacher, R.A. Schoneman, S.S. Vait, 1993. Long term use of saline water for irrigation. Irrigation Science, 14; 27-34.

Barin, J., 1984. Genesis, distribution and classification of sodic soils in Oklahama. Soil Science, 17; 300-314.

Boardman, J., 2010. A short history of muddy floods. Soil Science Society of America Journal, 21; 303-309.

Czyz, E.A., A.R. Dexter, H. Terelak, 2002. Content of readily dispersible clay in the arable layer of some Polish soils. In: Pagliai M., Jones J., editors. Sustainable Land Management-Environmental Protection-A Soil Physical Approach. Advances in Geoecology. Catena Verlag, Germany; p. 115-124.

During, P.B., J.G. Chaney, 1984. Dispersion of kaolinite dissolved organic matter from Douglas-fir roots. Canadian Journal of Soil Science, 64; 445-455.

Duxbury, J.M., M.S. Smith, J.W. Doran, 1989. Soil organic matter as a source and a sink of plant nutrients. In: Coleman D.C., Oades J.M., Uehara G., editors. Dynamics of soil organic matter in tropical ecosystems. University of Hawaii press, Honolulu; p. 33-67.

Emerson, W.W., 1983. Inter-particle bonding. In: Kamper J.D., Rhoades J.D., editors. An Australian Viewpoint. Division of soils, CSIRO: Melbourne/Academic Press, London; p. 477-498.

Eswaran, H., R. Lal, P.F. Reich, 2001. Land degradation: an overview. In: Bridges E.M., Hannam I.D., Oldeman L.R., Pening de Vries F.W.T., Scherr S.J., Sompatpanit, S., editors. Responses to Land Degradation. Proc. 2 nd . International Conference on
Land Degradation and Desertification, Khon Kaen, Thailand. Oxford Press, New Delhi, India.

Etana, A., T. Rydberg, J. Arvidsson, 2009. Readily dispersible clay and particle transport in five Swedish soils under long-term shallow tillage and mouldboard ploughing. Soil and Tillage Research, 106; 79-84.

Evelyn, S.K., O.S. Jan, A.B. Jaffery, 2004. Functions of soil organic matter and the effect on soil properties. Grains Research and Development Corporation (GRDC), project No. CSO 00029, Residue Management, Soil Organic Carbon and Crop Performance.

Ezekiel, M ., 1930. Methods of Correlation Analysis. John Wiley and Sons, New York .

Farifteh, J., F. Van der Meer, C. Atzberger, E.J.M. Carranza, 2007. Quantitative analysis of salt-affected soil reflectance spectra: a comparison of two adaptive methods (PLSR and ANN). Remote Sensing of Environment, 110; 59-78.

Fuller, L.G., T.B. Goh, D.W. Oscarson, 1995. Cultivation effects on dispersible clay of soil aggregates. Soil Science, 75; 101-107.

Gharaibeh, M.A., N.I. Eltaif, S.H. Shra’ah, 2010. Reclamation of a calcareous saline-sodic soil using phosphoric acid and by product gypsum. Soil Use and Management, 26; 93-195.

Goldberg, S., B.S. Kapoor, J.D. Rhoades, 1990. Effect of Aluminum and iron oxides and organic matter flocculation and dispersion of arid zone soils. Soil Science, 5; 588-593.

Gregne, H.E., N.T. Chou, 1994. Global desertification dimensions and cots. In: Dregne H.E., editor. Degradation and Restoration of Arid Land. Texas Technical University, Lubbook, USA; p. 90-101.

Igwe, C.A., O.N. Udegbuhnam, 2008. Soil properties influencing water-dispersible clay and silt in an Ultisol in southern Nigeria. International Agrophysics, 2; 319-325.

Ithaca, N.Y., Z. Kazman, I. Shainberg, M. d Gal, 1983. Effect of low levels of exchangeable Na and applied phosphor-gypsum on the infiltration rate of various soils. Soil Science, 35; 184-192.

Jones, F.O., 1964. Influence of chemical composition of water on clay blocking of permeability. Journal of Petroleum Technology , ۱۶; ۴۴۱-۴۴۶.

Kay, B.D., A.R. Dexter, V.C.D. Rasiah, 1994. Weather, cropping practices and sampling depth effects on tensile strength and aggregate stability. Soil and Tillage Research, 32; 135-148.

Korkanç, S.Y., M. Korkanç, 2016. Physical and chemical degradation of grassland soils in semi-arid regions: A case from Central Anatolia, Turkey. Journal of African Earth Sciences, 124; 1-11.

Kretzscmar, R., W.P. Roberg, S.B. Weed, 1993. Flocculation of kaolinitic soil clays: Effect of humic substances and iron oxides. Soil Science Society of America Journal, 57; 1277-1287.

Kumari, K.G., P. Moldrup, M. Paradelo, L. Elsgaard, L.W. de Jonge, 2017. Effects of biochar on dispersibility of colloids in agricultural soils. Journal of Environmental Quality, 46; 143-152.

Liu, Z., F. Xu, Y. Zu, R. Meng, W. Wang, 2016. Study on water dispersible colloids in saline–alkali soils by atomic force microscopy and spectrometric methods.
 

Microscopy Research and Technique, 79; 525-531.

McIntyre, D.S., 1985. Permeability measurement of soil crusts formed by raindrop impact. Soil Science, 85; 185-189.

Neath, M.A., D.S. Chanasyk, R. Izaurralde, J. Bateman, L. Campbell, 1996. In-situ amelioration of sodic mine spoil using sulfur, gypsum and crop management. Soil Science, 63; 123-138.

Paradelo, R., F. van Oort, C. Chenu, 2013. Water-dispersible clay in bare fallow soils after 80 years of continuous fertilizer addition. Geoderma, 200-201; 40-44.

Park, S.J., P.L.G. Vlek, 2002. Environmental correlation of three-dimensional soil spatial variability: a comparison of three adaptive techniques. Geoderma, 109; 117-140.

Pavanelli, D., A. Pagliarani, 2002. Monitoring water flow, turbidity and suspended sediment load from Apennine catchment basin, Italy. Biosystem Engineering, 83; 463-468.

Rashad, M., S. Dultz, 2007. Decisive factors of clay dispersion in Alluvial soils of the Nile River delta: A study on surface charge properties. Agricultural and Environmental Science, 2; 213-217.

Rengasamy, P., R.S.B. Greene, G.W. Ford, A.H. Mehanni, 1984. Identification of dispersive behavior and management of red-brown earths. Soil Research, 22; 413-431.

Shirani, H., M. Habibi, A.A. Besalatpour, I. Esfandiarpour, 2015. Determining the features influencing physical quality of calcareous soils in a semiarid region of Iran using a hybrid PSO-DT algorithm . Geoderma, 259-260; 1-11.

Soil Survey Staff, 1996. Soil survey laboratory methods manual. Report No. 42, USDA, NRCS, NCSS, USA.

Sumner, M.E., 1993. Sodic soils: new perspectives. Australian Journal of Soil Research,31; 683-750.

Tisadle, J.M., J.M. Oades, 1982. Organic matter and water-stable aggregates in soils. Soil Science, 33; 141-163.

Vahdati Daneshmand, F., 1990. Geological Quadrangle Map of Iran, Rafsanjan, No. 110. Ministry of Industry, Mine and Trade. Geological Survey of Iran Available online at http://www.gsi.ir .

Wei, J.B., D.N. Xiao, H. Zeng, Y.K. Fu, 2008. Spatial variability of soil properties in relation to land use and topography in a typical small watershed of to black soil region, northeastern China. Environmental Geology, 53; 1663-1672.

Wimp, G., M. Elhadji, 2002. Causes, General Extent and Physical Consequence of Land Degradation in Arid, Semi-arid and Dry Sub-humid Areas. Forest conservation and natural resources, Forest Department, FAO, Rome, Italy.

Zadeh, L.A., 1965. Fuzzy sets. Information Control, 8; 338-353.

Zorluer, I., Y. Icage, S. Yurtcu, H. Tosun, 2010.
Application of a fuzzy rule-based method for the
determination of clay dispersibility. Geoderma, 160;
189-196.

 

 

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