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IJSTR >> Volume 3- Issue 9, September 2014 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



The Impact Of Water And Soil Electrical Conductivity And Calcium Carbonate On Wheat Crop Using A Combination Of Fuzzy Inference System And GIS

[Full Text]

 

AUTHOR(S)

Kazem Aliabadi, Hadi Soltanifard

 

KEYWORDS

Index Terms: Fuzzy inference system, Water electrical conductivity, Soil electrical conductivity, Calcium carbonate, GIS

 

ABSTRACT

Abstract: Regarding population growth, reduction of food resources, issues of water scarcity, droughts, and water and soil pollution, there is no doubt that agriculture in the form of science and by up to date technologies such as GIS and expert systems like fuzzy inference system would be important. In this study, the performance of wheat with attend to soil electrical conductivity, electrical conductivity of the water, and the percentage of calcium carbonate and using a combination of GIS and fuzzy inference system is acceptance and analysis of several parameters simultaneously. If parameters increase, the accuracy will be improved. Inference system estimated the performance using soil EC, water EC, and calcium carbonate in soil as input parameters and also analyzing them. With respect to the results of fuzzy inference system, 76 percent of accuracy for the method of Mamdani and 52 percent of accuracy for the method Sugeno were achieved.

 

REFERENCES

[1] Badenko, v., and kurtener, D. 2004. Fuzzy modeling in GISenvironment to support sustainable land use planning. The AGILEconference on geographic information science. 29 April-1may. Heralion, Greece, parallel session a.1- "geographic knowledge discovery.

[2] Baja, S., Chapman, D.M., and Dragovich, D. 2002. Fuzzy modelingof environmental suitability index for rural land use systems: anassessment using GIS. Environment and Planning B: Planning andDesign. 29:3–20.

[3] Balali, M., Mohajermilani, P., and Khademi, Z. 2000. Comprehensive computer models of chemical fertilizers in line with recommendations of sustainable agricultural productions. Soil and Water Research Institute.

[4] Bolton FE. 1991. Tillage and stubble management. In: Harris, H.C., Cooper, P.J.M., Pala, M. (Eds.), Soil and Crop Management for Improved Water Use Efficiency in Rainfed Areas. ICARDA, Aleppo, Syria, 39–47.

[5] Bouroubi, B. Panneton, S. Guillaume, P. Vigneault, and C. Bélec. 2010,"Develop and Validation of Fuzzy Logic Iference to determine optimum rate of N for corn on the basis of field and crop features". Precision Agriculture, 11:621-635,
[6]
[7] Briggle LW and Curtis BC. 1987, Wheat Worldwide. In: Heyne, E.G. (ed). Wheat and Wheat Improvement. American Society of Agronomy, Madison, WI. pp. 1-31.

[8] Dikshit AK, Padmavathi T, Das RK. 2001, “Locating Potential Landfill Sites Using Geographic Information Systems.”, Journal of Environmental Systems, 28(1), 43-54

[9] Edrees AS, Rafea A,Fathy Iand Yahia M. 2003," NEPER: a Multiple Strategy wheat expert system", Computers and Electronics in Agriculture, 40, 1-3, 27-43

[10] Effati, M. and Rajabi, M. 2011. Presentation of a new method to identify road black spots using GIS and fuzzy inference: A case study. Science and Technology Mapping, 2: 1-15.

[11] El Hajj M, Begue A, Guillaume S, Martine JF. 2010," Combining Multi _ source information for Crop monitoring", Information Fusion, 2008 11th International Conference on, 1 - 7

[12] Engelbrecht, A. P. 2007. Computational Intelligence: An Introduction, Second Edition, John Wiley Sons, Ltd

[13] Foong Kwong, ch., Chuah, T. and Lee,W.(2010). "Adaptive Network Fuzzy Inference System (ANFIS) HandoffAlgorithm". International Journal of Network and Mobile Technologies, 1(2), 54-59.

[14] Ghadirimasoum, M., Nasiri, H., and Rafiee, Y. 2012. Implementing make-up agriculture model using fuzzy inference system and GIS: A case study in Marvdasht city. GeographicalSciences andApplied Research, 25: 195-218.

[15] Ghodsipour, H. 2006. Hierarchy processes. Amirkabir University of Technology of Tehran.

[16] Hartati S, sitanggang ISM.2010,." A Fuzzy Based Decision Support for Evaluating Land Suitability and Selecting Crops", Journal of computer science, 6(4), 417-424

[17] Karimi, M., Sadimesgari, M., and Sharifi, M. 1999. Modeling ecological comptetnce of land using fuzzy logic: A case study in Barkhar and Meyme. Remote Sensing and GIS in Iran, 1: 17-38.

[18] Keshavarzi A, Sarmadiyan F, Heidari A,.2010,."land Suitability Evaluation Using Fuzzy Continuous classification (A Case Study: Ziaran Region) ", Vol 4(7) , Modern Applied Science.

[19] Khorasan Regional Water Company. 2001.

[20] Kourepazan, A. 2008. Fuzzy set theory and its applications in modeling water engineering issues. Tehran: Amirkabir Publication.

[21] Kurtener D, Green TR, Krueger–Shvetsova E, Erskine RH. 2005,"Exploring Relationships Between Geomorphic Factors and Weaht Yield Using Fuzzing Inference System", Hydrology Days, 121-130

[22] Lashgari, H. and Rezaie, A. 2011. Locating of Kalza cultivated areas in Sarpolzahab area in Iran. Geography Research, 78: 29-48.

[23] Menhaj, P. and Nasaji, M. 2000. Foundations of fuzzy reasonings. Knowledge of Management, 51: 24-34. N. Tremblay, M.Y.

[24] Mousazadeh, M. and Ghasemaghayi, N. 2009. A fuzzy expert sytem to estimate irrigation need of wheat fields.

[25] Parhizgar, A. 1999. Suitable model to study the location of urban centers, urban models and GIS. Ph.D. Dissertation, Tarbiat Modarres University of Tehran.

[26] Reshmidevi ,T.V., T.L., Eldho , R., Jana. 2009. A GIS-integrated fuzzy rule-based inference system forland suitability evaluation in agriculturalwatersheds. Agricultural Systems. 101: 101 –109

[27] Robin, A.K.Szmidt & Andrew. 2001. Use of compost in agriculture, Frequently Asked Question (FAQ).

[28] Samandarzadegan, F., Abbaspour, R., and Pahlavani, P.2007. Application of Geographic Information Systems (GIS) in locating emergency housing residents in disaster areas based on fuzzy theory: Disaster management, 1: 172-178.

[29] Sikora LJ, Szmide RAK.2001. Nitrogen Source, Mineralization, rates and plant nutrient benefits from copost. pp. 287-305. In: P. J. Stoffella and B. A. Kahn (eds.) Compost utilization in horticultural cropping system. New York, USA: Lewis Publishers.

[30] Slafer GA and Rawson HM. 1994." Sensitivity of Wheat Phasic Development to Major Environmental-Factors - a Reexamination of Some Assumptions Made by Physiologists and Modelers ", Australian Journal of Plant Physiology, 21(4), 393-426

[31] Slamfar, S. 2000.Wheat, ecology, physiology and performance estimation.

[32] Smith cj, Freney JR, Chapman SL, Galbally JE. 1989. Fate of urea nitrogen applied to irrigated wheat at heating. Aust.J.Agric.Res, 40, 951-963

[33] Tandon, j.p. 1984. "Wheat improvement programs for the hotter parts of India . pp: 63- 67".

[34] Welech,R.M.,W.Allaway,W.A.House.1991. Geographic distribution of trace-element problem. In: micronutrient in Agriculture., P : 31-57. Soil sci. Soc.Am. Madison, USA.

[35] Zimmermann HJ and Zysno P. 1980, Latent Connectives in Human Decision Making. Fuzzy Sets and Systems, 4:37-51