تعداد نشریات | 161 |
تعداد شمارهها | 6,532 |
تعداد مقالات | 70,501 |
تعداد مشاهده مقاله | 124,104,052 |
تعداد دریافت فایل اصل مقاله | 97,210,057 |
ارزیابی حاصلخیزی خاک با استفاده از توابع عضویت فازی و AHP در اراضی شالیزاری (مطالعه موردی: مزارع پژوهشی گلدشت، آمل) | ||
تحقیقات آب و خاک ایران | ||
دوره 52، شماره 1، فروردین 1400، صفحه 109-122 اصل مقاله (1.2 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2020.308462.668707 | ||
نویسندگان | ||
سیده فاطمه نبوی1؛ نفیسه یغمائیان مهابادی* 1؛ شهرام محمود سلطانی2 | ||
1گروه علوم خاک، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران | ||
2مؤسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران | ||
چکیده | ||
با توجه به نقش مؤثر حاصلخیزی خاک در کشاورزی پیشرفته، تهیه نقشه حاصلخیزی خاک جهت برنامهریزی بهتر و دستیابی به مدیریت ویژه بر پایه تغییرات مکانی خاک ضروری به نظر میرسد. هدف از این پژوهش تهیه نقشه حاصخیزی خاک برای کشت برنج بر اساس پارامترهای مؤثر در حاصلخیزی خاک شامل کربن آلی، ازت کل، فسفر و پتاسیم قابل استفاده، رس و گنجایش تبادل کاتیونی از طریق تلفیق AHP با دو نوع تابع عضویت فازی کندل و S شکل میباشد. به این منظور نمونهبرداری خاک در 50 نقطه مطالعاتی انجام و ویژگیهای مذکور اندازهگیری شدند. درونیابی این نقاط برای پارامترهای مورد مطالعه از طریق روش کریجینگ انجام شد. سپس نقشه فازی هر یک از پارامترها با تعریف توابع عضویت Sشکل و کندل تهیه شده و با استفاده از روش AHP وزندار شدند. در نهایت از تلفیق آنها در محیط GIS نقشه حاصلخیزی خاک برای برنج تهیه شد. نقشههای حاصلخیزی بهدست آمده از توابع عضویت S شکل و کندل نشان میدهد که به ترتیب 73/95 و 68/53 درصد از منطقه مورد مطالعه دارای حاصلخیزی زیاد و خیلی زیاد میباشد. مقایسه نقشههای حاصلخیزی از طریق نقاط نمونهبرداری مجدد برای کنترل دقت نقشهها نشان میدهد که نقشه حاصلخیزی حاصل از تابع عضویت فازی S شکل (64 درصد) نسبت به تابع عضویت کندل (40 درصد) از کارآیی و تطابق بیشتری با واقعیت برخوردار است. بنابراین تلفیق AHP با تابع عضویت فازی S شکل میتواند با دقت قابل قبولی وضعیت حاصلخیزی منطقه مورد مطالعه را به صورت کمی و طبقهبندی شده ارائه کرده و برای مدیریت مصرف کود و پایش تغییرات تغذیهای خاک مفید واقع شود. | ||
کلیدواژهها | ||
تابع عضویت فازی S شکل؛ تابع عضویت فازی کندل؛ نقشه حاصلخیزی؛ برنج | ||
عنوان مقاله [English] | ||
Assessment of Soil Fertility Using Fuzzy Membership Functions and AHP in Paddy Fields (Case Study: Research Fields Goldasht, Amol) | ||
نویسندگان [English] | ||
Seyedeh Fatemeh Nabavi1؛ Nafiseh Yaghmaeian Mahabadi1؛ Shahram MahmoudSoltani2 | ||
1Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran | ||
2Rice Research Institute of Iran, Agricultural Research, Education and Extension, Rasht, Iran | ||
چکیده [English] | ||
Considering the effective role of soil fertility in advanced agriculture, preparing soil fertility map for better planning and achievement of specific management on based soil spatial variability seems necessary. The purpose of this study was to prepare a soil fertility map for rice, based on the effective parameters on soil fertility including organic carbon, total nitrogen, available phosphorus and potassium, clay and cation exchange capacity by integrated AHP with two types of Kandel and S-shaped fuzzy membership functions. For this purpose, soil samples were collected in 50 observation points and their physical and chemical properties were measured. Interpolation of these points for the studied parameters was done by kriging method. Then the fuzzy map of each parameter was prepared by defining the S-shaped and Kandel membership functions and weighted using AHP method. Finally, by integrating them in GIS environment, soil fertility map was prepared for rice. Fertility maps obtained from S-shaped and Kandel membership functions showed that 95.73% and 53.68% of the studied area have high and very high fertility, respectively. Comparison of fertility maps through re-sampling points to control the accuracy of the maps showed that the fertility map resulting from S-shaped fuzzy membership function (64%) is more efficient and realistic than Kandel membership function (40%). Therefore, the integration of AHP with the S-shaped fuzzy membership function can quantify and classify the soil fertility of the studied area and be useful for managing fertilizer use and monitoring soil nutrition changes. | ||
کلیدواژهها [English] | ||
S-shaped fuzzy membership function, Kandel fuzzy membership function, Fertility map, Rice | ||
مراجع | ||
Aama Azghadi, A., Khorassani, R., Mokarram, R. and Moezi, A. (2010). Soil fertility evaluation based on soil K, P and organic matter factors for wheat by using fuzzy logic-AHP and GIS techniques. Journal of Water and Soil, 24(5), 973-984. (In Farsi) Aishah, A.W., Zauyah, S., Anuar, A. R. and Fauziah, C.I. (2010). Spatial variability of selected chemical characteristic of paddy soils in Sawash Sempadon, Selangor, Malaysia. Malaysian Journal of Soil Science, 14, 27-39. Ali, A.M.S. (2003). Farmers knowledge of soils and the sustainability of agriculture in a saline water ecosystem in southwestern Bangladesh. Geoderma, 111, 333-353 Bagherzadeh, A., Gholizadeh, A. and Keshavarzi, A. (2018). Assessment of soil fertility index for potato production using integrated Fuzzy and AHP approaches, northeast of Iran. Eurasian Journal of Soil Science, 7(3), 203-212. Banai, M.H. (1998). A map of the soil and moisture regime of Iranian soils. Soil and water research institute, Tehran. (In Farsi) Barrera-Bassols, N., Zinck, J. and Van Ranst, E. (2006). Symbolism, knowledge a management of soil and land resources in indigenous communities: Ethnopedology at global, regional and local scales. Catena, 65(2), 118-137. Beckford, C. and Barker, D. (2007). The role and value of local knowledge in Jamaican agriculture: adaption and change in small-scale farming. Geographical Journal, 173(2), 118-128. Bouman, B.A., Barker, R., Humphreys, E., Tuong, T.P., Atlin, G., Bennett, J. and Fujimoto, N. (2007). Rice: feeding the billions (No. 612-2016-40554). Bower, C.A., Reitemeier, R.F. and Fireman, M. (1952). Exchangeable cation analysis of saline and alkali soils. Soil Science, 73(4), 251-262. Bremner, J.M. and Mulvaney, C.S. (1982). Nitrogen total 1. Methods of soil analysis. Part 2. Chemical and microbiological properties, (methods of soil analysis), 595-624. Carter, M.R. (2000). Soil sampling and methods of analysis. pp: 499-511. Cheng, Y.Q., Yang, L.Z., Cao, Z.H., Ci. E. and Yin. Sh. (2009). Chronosequential changes of selected pedogenic properties in paddy soils as compared with non-paddy soils. Geoderma, 151(1-2), 31-41 Choi, W.J., Kwak, J.H. and Lim, S.S. (2017). Synthetic fertilizer and livestock manure differently affect 15N in the agricultural landscape: A review. Agricultural Ecosystems and Environment, 237, 1–15. Davatgar, N., Neishabouri, M.R. and Sepaskhah. A.R. (2012). Delineation of site specific nutrient management zones for a paddy cultivated area based on soil fertility using fuzzy clustering. Geoderma, 173, 111-118. Delsouz Khaki, B., Honarjoo, N., Davatgar, N., Jalalian, A. and Torabi Gelsefidi, H. (2017). Land Suitability Evaluation and Inherent Soil Fertility Quality for Rice Cultivation in Paddy Fields of Shaft and Fouman Counties. Journal of Soil Research (Soil and Water Sciences), 32 (1), 116-128. (In Farsi) Delsouz Khaki, B., Honarjoo, N., Dvatgar, N. and Jalalian, A. (2015). Predicting rice grain yield using soil fertility qualities: Inherent soil fertility potential and nutrient availability (Case Study: Southern half of Foumanat plain in north of Iran) International Conference on Chemical, Agricultural and Biological Sciences Istanbul (Turkey).137-143. Dengiz, O., Ozyazici, M.A. and Saglam, M. (2015). Multi-criteria assessment and geostatistical approach for determination of rice growing suitability sites in Gokirmak catchment. Paddy and Water Environment, 13(1), 1-10. Dobermann, A. and Fairhurst, T.H. (2000). Rice: Nutrient disorders and nutrient management. Handbook Series, Potash and Phosphate Institute (PPI), Potash & Phosphate Institute of Canada (PPIC) and International Rice Research Institute (IRRI), Makati City 1271, Philippines. ISBN 981-04-2742-5 Dobermann, A. and Oberthur, T. (1997). Fuzzy mapping of soil fertility a case study on irrigated riceland in the philippines. Geoderma, 77(2), 317-339. Dobermann, A., Witt, C., Abdulrachman, S., Gines, H.C., Nagarajan, R., Son, T.T. and Tan, P.S. (2003). Soil fertility and indigenous nutrient supply in irrigated rice domains of Asia. Agronomy Journal, 95(4), 913-923. Fageria, N.K. (2001). Nutrient management for improving upland rice productivity and sustainability. Soil Science and Plant Analysis, 32, 2603 -2629. Fairhurst, T., Buresh, R. and Dobermann, A. (2007). Rice: A practical guide to nutrient management. Second edition, International Plant Nutrition Institute., International Potash Institute. Pp 92. FAO. (2015). Healthy soils are the basis for healthy food production. FAO 2015 I4405E/1/02.15. Guo, L., Wu, G. and Li, Y. (2016). Effects of cattle manure compost combined with chemical fertilizer on topsoil organic matter, bulk density and earthworm activity in a wheat–maize rotation system in Eastern China. Soil and Tillage Research, 156, 140–147. Kavoosi, M. and 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 Farsi) Kazemi PoshtMasari, H., Tahmasebi, Z., Kamkar, B., Shatai, Sh. and Sadeghi, S. (2012). Evaluation of geostatistical methods for estimating and zoning of primary nutrients in some agricultural lands of Golestan province, Water and Soil Science, 22(1), 201-220. (In Farsi) Koorehpazan Dezfuli, A. (2005). Principles of fuzzy set theory and its applications in the modeling of water engineering problems. Iranian Academic Center for Education Culture and Research, Amirkabir University of Technology Branch, 261p. (In Farsi) Kweon, G. (2012). Delineation of site-specific productivity zones using soil properties and topographic attributes with a fuzzy logic system. Biosystem Enginearing, 112(4), 261- 277. Li, G.L., Chen, J., Sun, Z.Y. and Tan, M.Z. (2007). Establishing a minimum data set for soil quality assessment based on soil properties and land-use changes. Acta Ecologica Sinica, 27(7), 2715-2724. Liu, Z., Zhou W., Shen, J., He, P., Lei, Q. and Liang, G. (2014). A simple assessment on spatial variability of rice yield and selected soil chemical properties of paddy fields south China. Geoderma, 235, 39-47. Mahmoudsoltani, S., Davatgar, N., Shakouri, M. and Paykan, M. (2017). Spatial variability of phosphorus fractions in paddy soils. Journal of Water and Soil Conservation, 24(5), 93-109. (In Farsi) Mokarram, M. and Bardideh, M. (2013). Soil fertility evaluation for wheat cultivation by fuzzy theory approach and compared with Boolean method and soil test method in GIS area. Agronomy Journal (Pajouhesh & Sazandegi), 96, 111- 123. (In Farsi) Momtaz, H. and Servati, M. (2017). Comparison of three membership function in land suitability by fuzzy set theory in Amol region, IRAN. Applied Soil Research, 5(1), 57-66. (In Farsi) Olde Venterink, H., Davidsson, T.E., Kiehl, K. and Leonardson, L. (2002). Impact of drying and rewetting on N, P and K dynamics in a wetland soil. Plant and Soil. 243:1, 119-130. Olsen, S.R. and Sommers. L.E. (1982). Phosphorus. In: Page A L., Miller R.H. and Keeney D.R. (Eds.), Methods of soil analysis- Part 2. American Society of Agronomy, Madison, pp: 403-430. Owliaie, H.R and Najafi Ghiri, M. (2012). Effect of long-term rice cultivation on physico-chemical properties and clay mineralogy of soils in Yasouj region. Journal of Science and Technology of Agriculture and Natural Resources, 17(65), 39-49. (In Farsi) Ozturk, D. and Batuk, F. (2010). Analytic hierarchy process for spatial decision making. Journal of Engineering and Natural Sciences, 28, 124–137. Saaty, T.H. and Vargas, L.G. (2001). Models, methods, concepts, and applications of the analytic hierarchy process. Kluwer Academic, 160p. Saito, K., Linquist, B., Atlin, G.N., Phanthaboon, K., Shirawa, T. and Horie, T. (2006). Response of traditional and improved upland rice cultivars to N and P fertilizer in northern Laos. Field Crops Research, 96, 216-223. Salehi, N., Ghajar Sepanlou, M. and Jafari Gorzin, B. (2013). An evaluation of soil fertility using soil organic carbon, potassium, phosphorus and salinity factors for rice cultivation by fuzzy logic and AHP techniques. International Journal of Agriculture and Crop Sciences, 5(19), 2233- 2241. Sarmadian, F. and Keshavarzi. A. (2014). The use of a hybrid fuzzy-AHP system on the evaluation and mapping of soil fertility. Journal of Soil and Water Resources Conservation, 3(2), 45-56. (In Farsi) ShakouriKatigari, M., Mahmoudsoltani, Sh., Karbalai Aghamolki, M.T. and Keshtekar Talemi, F. (2019). Relationship between yield and a soil quality index in paddy fields. Journal of Water and Soil, 33(2), 198-213. (In Farsi) Servati M., Jafarzadeh A.A., Ghorban M.A., Shahbazi F., and Davatgar, N. (2014). Comparison of the FAO and Albero models in prediction of irrigated wheat production potentials in the Khajeh region. Journal of Water and Soil Science, 24, 1-14. (In Farsi) Seyed Mohammadi, J., Esmaeelnejad, L. and Ramezanpour, H. (2016). Increasing efficiency of soil fertility map for rice Cultivation Using Fuzzy Logic, AHP and GIS. Journal of Water and Soil, 30(4), 1114-1129. (In Farsi) Sicat, S., Rodrigo, Carranza, M., Emmanuel, J. and Nidumolu, U.B. (2005). Fuzzy modeling of farmer s knowledge for land suitability. Agricultural Systems, 83, 49-75. Silva Cruz, J., De Assis Junior, R.N., Rocha Matias, S.S. and Camacho Tamayo, J.H. (2011). Spatial variability of an Alfisols cultivated with sugarcane. Cienciae Investigacion Agraria, 38(1), 155-164. Sunila, R., Laine, E. and Kermenova, O. (2004). Fuzzy model and kriging for imprecise soil polygon boundaries. In 1st International Conference on Advances in Mineral Resources Management and Environmental Geotechnology. Heliotopos Conferences. Sys, I.C., Van Ranst, E., Debaveye, I.J., and Beenaert. F. (1993). Land evaluation (Part IIII). Crop Requirements. 199p. General Administration for Development Cooperation, Brussels. Belgium. Tesfahunegn, G.B., Tamene, L. and Vlek, P.L. (2011). Catchment-scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia. Soil and Tillage Research, 117, 124-139. Virgilio, N.D., Monti, A. and Venturi, G. (2007). Spatial variability of switchgrass (Panicum virgatum L.) yield as related to soil parameters in a small field. Field Crops Research, 101, 232–239. Walkley, A. and Black, I.A. (1934). An examination of the Degtiareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil science, 37, 29-38. Westerman, R.E.L. (1990). Soil testing and plant analysis. Soil Science Society of America, Mandison Wisconzin, USA. Wilding, L.P. and Dress. L.R. (1983). Spatial variability and pedology. In: L.P. Wilding, N.E. Smeckand and G.F. Hall (eds.), Pedogenesis and Soil Taxonomy. I. Concepts and Interactions. Elsvier Science Pub. 83-116. Yemefack, M., Rossiter, D.G. and Njomana, R. (2005). Multi-scale characterization of soil variability within an agricultural landscape mosaic system in southern Cameroon. Geoderma, 125, 117-143. Wu, R. and Tiessen, H. (2002). Effect of land use on soil degradation in alpine grassland soil. China. Soil Science Society of America Journal. 66(5): 1648-1655. Zhao, J.H., Hou, H.Y., Ren, A.Q., Zhang, H. and Han, Y.Q. (2010). Comprehensive evaluation of tobacco ecological suitability of Henan province based on GIS. Agricultural Sciences, 9, 583-592. | ||
آمار تعداد مشاهده مقاله: 453 تعداد دریافت فایل اصل مقاله: 346 |