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Evaluation of soil fertility map for bean cultivation in Eghlid Plain by using Hybrid Fuzzy-AHP and GIS techniques | ||
| Iran Agricultural Research | ||
| مقاله 10، دوره 40، شماره 1، تیر 2021، صفحه 101-112 اصل مقاله (771.52 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22099/iar.2021.40610.1437 | ||
| نویسندگان | ||
| G.R zareian* 1؛ A azadi2؛ S Shakeri3 | ||
| 1Department of Soil and Water Research, Fars Agricultural and Natural Resources Research and Education Center, AREEO, Shiraz, I. R. Iran | ||
| 2Department of Soil and Water Research, Khuzestan Agricultural and Natural Resources Research and Education Center, AREEO, Ahvaz, I. R. Iran | ||
| 3Department of Agriculture, Payame Noor University, Tehran, I. R. Iran | ||
| چکیده | ||
| The increase in the performance of cultivated plants is under the influence of various features including the soil properties. The nutrient elements of the soil are among the important soil features. The soil fertility should be studied to determine the proper level of fertilizer application. The improper use of chemical fertilizers with no attention to soil fertility not only does not increase the quality and quantity of the products but also imposes extra costs while unbalancing the level of nutritional elements of the soil and causing environmental problems. In this regard, the determination of soil fertility and providing a soil fertility map sounds necessary. In this study, the soil fertility of Shadkam plain in Eghlid county of Fars province was determined to prepare the soil fertility map for the cultivation of bean. The soil fertility map was obtained by a fuzzy system using a hierarchical analysis in a GIS environment. To this end, soil sampling was conducted from 210 locations and the input data including organic matter, potassium, phosphorous, iron, manganese, zinc, and copper concentrations were measured. The interpolation of each soil element was achieved by the inverse distance weight (IDW) model in the GIS environment. Then, a membership function was prepared for each factor to obtain the fuzzy map considering their corresponding critical values. Finally, each layer was allocated with weight using the analytic hierarchy process. Based on the relative weight of each criterion, the highest relative weight (0.354) was obtained for organic carbon while iron showed the lowest (0.031) relative weight. The results also indicated that 0.3, 80.3, and 19.4% of the studied region can be categorized as very poor, poor, and moderate groups in terms of fertility for bean cultivation, respectively. | ||
| کلیدواژهها | ||
| Bean؛ Calcareous soil؛ Fars province؛ Soil fertility | ||
| مراجع | ||
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Ama Azghadi, A., Khorasani R., Mokarram M., & Moezi A. (2010). Soil fertility evaluation based on factors phosphorus, potassium and organic matter for plants using fuzzy AHP and GIS techniques. Water and Soil- Agricultural Sciences and Technology, 24 (5), 265-274. (In Persian) Azar, A., & Faraji, H. (2008). Fuzzy management philosophy, (4th ed.). Tehran: Mehraban ketab organization Inc. (In Persian) Azar, A., & Rajabzade, A. (2012). Decision-making applications, (5th ed.). Tehran: Negah danesh press. Inc. (In Persian) Bijanzadeh, E., & Mokarram, M. (2017). Assessment the soil fertility classes for common bean ('Phaseolus Vulgaris' L.) production using fuzzy- analytic hierarchy process (AHP) method. Australian Journal of Crop Science, 11(4), 464-473. Bijanzadeh, E., & Mokarram, M. (2013). The use of fuzzy-AHP methods to assess fertility classes for wheat and its relationship with soil salinity: A case study: East of Shiraz, Iran. Australian Journal of Crop Science, 7(11), 1699–1706. Burrough, P. A., MacMillan, R. A., & Deursen, W. (1992). Fuzzy classification method for determining land suitability from soil profile observations and topography. European Journal of Soil Science, 43,193–210. Cassel- Gintz, M. A., Lu deke, M. K., Petschel-Held, G., Reusswig, F., Plo¨chl, M., Lammel, G., & Schellnhuber, H. J. (1997). Fuzzy logic based global assessment of the marginality of agricultural land use. Climate Research, 63(8),135–150 Davis, B. M. (1987). Uses and abuses of cross-validation in geostatistics. Mathematical geology, 19(3), 241-248. Delbari, M., Loiskandl, W., & Afrasiab, P. (2010). Uncertainty assessment of soil organic carbon content spatial distribution using geostatistical stochastic simulation. Australian Journal of Soil Research, 48(1), 27-35. Dobermann, A., Cassman, K. G., Mamaril, C. P., & Sheehy, J. E. (1998). Management of phosphorus, potassium, and sulfur in intensive, irrigated lowland rice. Field Crops Research, 56(1-2), 113-138. Ebert, T., & Trauth, M. H. (2015). Semi-automated detection of annual laminae (varves) in lake sediments using a fuzzy logic algorithm. Palaeogeography, Palaeoclimatology, Palaeoecology, 435, 272-282. FAO(Food and Agricultural Organization). 2008. Production and trade yearbook, 2007, FAO, Rome. Franzen, D. W., Hofman, V. L., Cihacek, L. J., & Swenson, L. J. (1999). Soil nutrient relationships with topography as influenced by crop. Precision Agriculture, 1(2), 167-183. Helmke, P. A., & Sparks, D. L. (1996). Lithium, sodium, potassium, rubidium and cesium. In: Sparks, D. L. (Ed.), Method of soil analysis, Part 3. Chemical methods. (pp 551-574). No. 5. Madison, WI, USA: American Society of Agronomy. Jonse, B. J. J. (2001). Laboratory guide for conducting soil test and plant analysis. Boca Raton: FL: CRC Ppresss LLC. Kˇremenov´, O. (2004). Fuzzy modeling of soil maps. (Master’s thesis, Helsinki University of technology, Department of surveying, pp. 81). Kavoosi M., & Malakoti M. J. (2006). Determination of available potassium critical level with ammonium acetate extractor in Guilan paddy soils. Journal of Science and Technology of Agriculture and Natural Resources, 3, 113–123. (In Persian) Khajehpour, M. R., & Naeni, A. B. (2002). The response of yield components and seed yield of bean (Phaseolus vulgaris L.) genotypes to delay in planting. Journal of Water and Soil Science, 5(4), 121-136. Khazaie, E., Bostani, A. A., & Davatgar, N. (2017). Geostatic and GIS evaluation of spatial variability of nitrogen, phosphorus, potassium, and cation exchange capacity in agro-industrial land of Sharif Abad in Qazvin. Iranian Journal of Soil Research, 31(2), 195-213. Malakouti, M. J., & Gheibi, M. N. (2000). "Determination of critical levels of nutrients in soil, plant, and fruit for the quality and yield improvements in strategic crops of Iran. (completely revised)." High Concoil for Appropriate Use of Pesticides and Chemical Fertilizers, Ministry of Agriculture . pp. 92. Iran: Karaj. Malczewski, J. (1999). GIS and multicriteria decision analysis. New York: Wiley. Maphosa, Y., & Jideani, V. A. (2017). The role of legumes in human nutrition. Functional food-improve health through adequate food, 1, 13. Moreno, J. S. (2007). Applicability of knowledge-based and Fuzzy theory-oriented approaches to land suitability for upland rice and rubber. (PhD dissertation, M. Sc. Thesis, ITC, the Netherland). Nelson, D. W., & Sommers, L. E. (1996). Total carbon, organic carbon, and organic matter. In: Sparks, D. L. (Ed.), Methods of soil analysis part 3. Chemical methods (pp. 961-1010). Madison WI, USA: American Society of Agronomy. Oberthür, T., Dobermann, A., & Aylward, M. (2000). Using auxiliary information to adjust fuzzy membership functions for improved mapping of soil qualities. International Journal of Geographical Information Science, 14(5), 431-454. Olsen, S. R. (1954). Estimation of available phosphorus in soils by extraction with Sodium bicarbonate (No. 939). US: Department of Agriculture. Parhizkar, A., & Ghafari gilande, Ata. (2006). GIS and multi standard decision analysis. Tehran: Samt publication. Qudsipour, S. H. (2005). Issues in multi-criteria decision making, analytical hierarchy process. Tehran: Amir Kabir University of Technology Press. Saaty, T. L. (1980). The analytical hierarchy process, planning, priority. USA: Resource allocation. RWS publications. Scully, B., & Waines, J. G. (1987). Germination and emergence response of common and tepary beans to controlled temperature 1. Agronomy Journal, 79(2), 287-291. Sokouti, R., & Mahdian, M. H. (2011). Spatial variability of macronutrient for soil fertilization management: A case study on Urmia plain. International Journal of Soil Science, 6(1), 49-59. Stutter, M. I., Deeks, L. K., & Billett, M. F. (2004). Spatial variability in soil ion exchange chemistry in a granitic upland catchment. Soil Science Society of America Journal, 68(4), 1304-1314. Taghizadeh, M. R., zareeian, J. M., Mahmoudi, S., Heydari, A., & Sarmadian, F. (2009). Investigation of interpolation methods to determine spatial distribution of groundwater quality in Rafsanjan. Iranian Journal of Watershed Management Science and Engineering, 2(5), 63-70. Van Schoonhoven, A., & Voysest, O. (1991). Common beans: Research for crop improvement. Cali, Colombia: CIAT. Lotfi Zadeh L. H. (1965). Fuzzy Sets. Information and control, 8(3), 338-353. Zhang, B., Zhang, Y., Chen, D., White, R. E., & Li, Y. (2004). A quantitative evaluation system of soil productivity for intensive agriculture in China. Geoderma, 123(3-4), 319-331. | ||
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