Evaluation of soil fertility in citrus planted areas by geostatistics analysis method

The aim of this study is to map citrus planted areas, which have been detected by traditional methods to date, with a high accuracy method and to reveal the land characteristics and fertility conditions. A database was created for citrus planted areas with the help of high-resolution Worldview 2 satellite images in this study. By creating the digital elevation model, orthorectification of satellite images was made and slope, aspect and elevation characteristics were determined. Using soil maps, maps showing terrain characteristics were produced. 43 soil samples were taken to represent citrus planted areas; geostatistical maps showing their pH, salinity, lime, texture, organic matter, total N, available P; exchangeable K, Ca, Mg, Na, available Fe, Cu, Zn, Mn levels were created and their statistical analyses were performed 2,132.08 ha citrus planted area was found in the study area. The parameters obtained from the digital elevation model (slope, aspect, elevation), the data of the land from the soil maps and the physical properties-macro/micro nutritional contents of the soil produced by the geostatistics method were evaluated together. It was determined that the features in all areas mapped as citrus planted area are quite suitable for citrus production. However, it is thought that Fe and Zn uptake from the soil will decrease due to the fact that the pH level is slightly alkaline and high lime contents. Identifying and sustainable monitoring of citrus production areas, which are very important in terms of economy, accurately, up-to-date, without causing loss of time and labor, will be possible with integrated use of GIS and RS techniques.

Keywords:

Citrus, soil fertility, geostatistics Worldview 2 satellite imagery,

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Aimrun, W., Amin, M.S.M., Ahmad, D., Hanafi, M.M., Chan, C.S., 2007. Spatial variability of bulk soil electrical conductivity in a Malaysian paddy field: Key to soil management. Paddy Water Environment 5(2): 113-121.
Akalan, İ.,1965. Toprak Oluşu, Yapısı ve Özellikleri. Ankara Üniversitesi Ziraat Fakültesi Yayınları No: 231. 332s. [in Turkish].
Akgün, C., 2006. Turunçgiller Sektör Profili. Dış Ticaret Şubesi Uygulama Servisi. Ankara. [in Turkish].
Anonymous, 2017. Turkish State Meteorological Service. Available at [Access date: 14.02.2017]: https://mgm.gov.tr/?il=Aydin
Anonymous, 2018. Aydın Tarım Master Planı. Aydın Tarım ve Orman İl Müd. Available at [Access date: 14.02.2017]: https://aydin.tarimorman.gov.tr/Belgeler/Ayd%C4%B1n%20Tar%C4%B1m%20Master%20Plan%C4%B1/MASTER%20PLAN%20%20%2816.01.2019%29-converted.pdf
Ballinger, W.E., Bell, H.K., Childers, N.F., 1966. Peach nutrition. In: Fruit Nutrition. Childers, N.F. (Ed.). Somerset Press, New Jersey, pp. 276-390.
Başayiğit L., Şenol H., 2009. The production of fertility maps of potential land for orchards using geographical ınformation systems. Journal of Plant & Environmental Sciences 1: 36-45 [in Turkish].
Belitz, H.D., Grosch, W., 1999. Fruits and fruit products. In: Food chemistry. Belitz, H. D., Grosch, W. (Eds.). Springer, Berlin, Heidelberg. pp. 748-800.
Black, C.A., 1965. Method of soil analysis. Part 1 Chemical and Microbiological Properties. Agronomy No. 9. American Society of Agronomy, Madison, Wisconsin, USA.
Bouyoucos, G.J., 1962. Hydrometer method improved for making particle size analyses of soils. Agronomy Journal 54(5): 464-465.
Bremner, J.M., 1965. Total Nitrogen. In: Method of Soil Analysis, Part 2. Chemical and Microbiological Properties. Black, C.A. et al. (Eds.) American Society of Agronomy, Madison, Wisconsin, USA. pp. 1149-1178.
Burrough, P.A., 1993. Soil variability: a late 20th century view. Soils and Fertilizers 56: 529-562.
Cambardella, C.A., Moorman, T.B., Parkin, T.B., Karlen, D.L., Novak, J.M., Turco, R.F., Konopka, A.E., 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal 58(5): 1501-1511.
Chen, H., Shen, Z., Liu G., Tong, Z., 2009. Spatial heterogeneity of available zinc, copper, and manganese in Xiangcheng tobacco planting fields, Henan Province, China. Frontiers of Biology in China 4(4): 469–476.
Çokuysal, B., Erbaş, E., 2004. Bitkilerde besin maddeleri noksanlıkları ve toprak tahlillerinin değerlendirilmesi. Ege Üniversitesi Tarımsal Uygulama ve Araştırma Merkezi, Çiftçi Broşürü: 55, İzmir. [in Turkish].
Das, P.T., Tajo, L., Goswami, J., 2009. Assessment of citrus crop condition in Umling block of Ri-Bhoi district using RS and GIS technique. Journal of the Indian Society of Remote Sensing 37: 317–324.
Dengiz, O., Özyazıcı, M.A., Sağlam, 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.
Düzgün, Ş., 2010. Uzaktan Algılamaya Giriş Ünite 6: Görüntü Ortorektifikasyonu. TÜBA-Türkiye Bilimler Akademisi, Ulusal Açık Ders Malzemeleri. Available at [Access date: 14.02.2017]: http://www.acikders.org.tr/pluginfile.php/637/mod_resource/content/0/Ders_Notlari/Unite6_Goruntu_Ortorektifikasyonu.pdf
Foroughifar, H., Jafarzadeh, A.A., Torabi, H., Pakpour, A., Miransari, M. 2013. Using geostatistics and geographic information system techniques to characterize spatial variability of soil properties, including micronutrients. Communications in Soil Science and Plant Analysis 44(8), 1273-1281.
Gamze, Ö., Kısmalı, Ş., 2003. An investigations on the population, distribution and damage of the Wooly whitefly, Aleurothrixus floccosus (Maskell) (Homoptera: Aleyrodidae) on citrus areas in Izmir province of Turkey. Turkish Journal of Entomology 27(1): 61-72. [in Turkish]
Goovaerts, P., 1997. Geostatistics for natural resources evaluation. Oxford Univ. Press, NewYork, USA. 483 p.
Goovaerts, P., 1998. Accounting for estimation optimality criteria in simulated annealing. Mathematical Geology, 30(5); 511–534.
Güzel, M., Akpınar, Ö., 2017. Turunçgil kabuklarının biyoaktif bileşenleri ve antioksidan aktivitelerinin belirlenmesi. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi 7(2): 153-167. [in Turkish]
Heuvelink, G B.M., Webster, R., 2001. Modelling soil variation: past, present, and future. Geoderma 100(3-4): 269-301.
Jackson, M.L., 1967. Soil Chemical Analysis. Prentice Hall of India Pvt. Ltd., New Delhi. 498p.
Jones, Jr.J.B., 2001. Laboratory guide for conducting soil tests and plant analysis. CRC Press, New York, USA. 363p.
Kacar, B, Katkat, V., 2007. Bitki Besleme. Nobel Yayın Dağıtım, Ankara, Turkey. 678s.[in Turkish].
Karaçal, I., 2008. Toprak Verimliliği. Nobel Yayın Dağıtım, Ankara. Turkey. 222s.[in Turkish].
Karaman, R., Brohi, A.R., Müftüoğlu, N.M., Öztaş, T., Zengin, M., 2007. Sürdürülebilir Toprak Verimliliği. Detay Yayın Dağıtım, Ankara, Turkey. 224s. [in Turkish].
Krasilnikov, P., Sidorova, V., 2008. Geostatistical analysis of the spatial structure of acidity and organic carbon in zonal soils of the Russian plain. In: Soil geography and geostatistics: Concepts and Applications. Krasilnikov, P., Carré, F., Montanarella, L. (Eds.). Institute for Environment and Sustainability, European Communities, Luxembourg, pp. 55-67.
Lindsay, W.L., Norvell, W.A., 1978. Development of a DTPA Test for zinc, iron, manganese and copper. Soil Science Society America Journal 42(3): 421-428.
Loue A.T., 1968. Diagnostic petiolaire des prospectian etudes sur la nutrition at la fertilization potassiques de la vigne. Societe Commerciale des Potasses d’Alsace. Services Agronomiques, pp.31-41
López-García, F., Andreu-García, G., Blasco, J., Aleixos, N., Valiente, J.M., 2010. Automatic detection of skin defects in citrus fruits using a multivariate image analysis approach. Computers and Electronics in Agriculture 71(2): 189-197.
Marangoz, A.M., Karakış, S., Oruç, M., Büyüksalih, G., 2005. Nesne-tabanlı görüntü analizi ve ıkonos pan-sharpened görüntüsünü kullanarak yol ve binaların çıkarımı. TMMOB Harita ve Kadastro Mühendisleri Odası 10. Türkiye Harita Bilimsel ve Teknik Kurultayı 28 Mart - 1 Nisan 2005, Ankara, Turkey. [in Turkish]
Matsuoka, M., 2012. Comparison of the spectral properties of pansharpened images generated from AVNIR-2 and prism onboard Alos. XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia.
Mc Cormick, N., 1999. Satellite-based forest mapping using the silvics software, user manual. Space Applications Institute, EGEO, Commission of the European Communities, Joint Research Centre, I-21020 Ispra (VA), Italy, 13-28 p.
Mousavifard, S.M., Momtaz, H., Sepehr, E., Davatgar, N., Sadaghiani, M.H.R., 2013. Determining and mapping some soil physico-chemical properties using geostatistical and GIS techniques in the Naqade region, Iran. Archives of Agronomy and Soil Science 59(11): 1573-1589.
Mulla, D.J., Mc Bratney, A.B., 2000. Soil Spatial Variability. In: Handbook of Soil Science. Sumner, M.E. (Ed.). CRC Press, New York, USA. pp. A321-A352
Mulla, D.J., McBratney, A.B., 2002. Soil spatial variability. In: Soil physics companion, Warrick, A.W. (Ed.). CRC Press, New York, USA. pp.343-373.
Naseem, S., Mahmood, S., Ali, Z., 2016. Occurrence of Citrus tristeza virus in Pakistan: a GIS based approach combining host distribution and disease reports. Pakistan Journal of Agricultural Sciences 53(3): 513-521.
Oliver, M.A., Webster, R., 2014. A tutorial guide to geostatistics: Computing and modelling variograms and kriging. Catena 113: 56–69.
Olsen, S.R., Sommers, L.E., 1982. Phosphorus. In: Methods of Soil Analysis Part 2 Chemical and Microbiological Properties. Page, A.L. (Ed.). American Society of Agronomy, Soil Science Society of America, Madison, USA. pp. 403-430.
Özdemir, M., 2017. Evaluation of image pan-sharpening methods in terms of object-oriented classification. Harita Dergisi 158: 26-34. [in Turkish].
Özyazıcı, M.A., Dengiz, O., Aydoğan, M., Bayraklı, B., Kesim, E., Urla, Ö., Yıldız, H., Ünal, E., 2016. Levels of basic fertility and the spatial distribution of agricultural soils in Central and Eastern Black Sea Region. Anadolu Journal of Agricultural Sciences 31(1): 136-148.
Panday, D., Maharjan, B., Chalise, D., Shrestha, R.K., Twanabasu, B., 2018. Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS. PloS one 13(10): 1-20.
Knudsen, D., Peterson, G.A., Pratt, P.F., 1982. Lithium, Sodium, and Potassium. In: Methods of Soil Analysis Part 2 Chemical and Microbiological Properties. Page, A.L. (Ed.). American Society of Agronomy, Soil Science Society of America, Madison, USA. pp. 225-246.
Rauterberg, E., Kremkus, F., 1951. Bestimmung von Gesamthumus und Alkalilöslichen Humusstoffen im Boden. Z.F. Planzenernaehrung, Düngung und Bodenkunde, Verlag, Chemice Gmbh, Weinheim.
Richards, L.A., 1954. Diagnosis and improvement of saline and alkali soil. U.S. Salinity Lab. Staff, U.S. Department of Agriculture, Agricultural Research Service, Handbook 60. Washington D.C. USA. 160p.
Robinson, T.P., Metternicht, G., 2006. Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and Electronics in Agriculture 50(2): 97-108.
Santos-Francés, F., Martínez-Graña, A., Zarza C.A., García Sánchez, A., Rojo, P.A., 2017a. Spatial distribution of heavy metals and the environmental quality of soil in the Northern Plateau of Spain by Geostatistical Methods. International Journal of Environmental Research and Public Health 14(6):568.
Santos-Francés, F., Martínez-Graña, A., Rojo, P.A., García Sánchez, A., 2017b. Geochemical background and baseline values determination and spatial distribution of heavy metal pollution in soils of the andes mountain range (Cajamarca-Huancavelica, Peru). International Journal of Environmental Research and Public Health 14(8): 859.
Schlichting, E., Blume, H.P., 1966. Bodenkundliches Praktikum, Verlag Paul Parey, Hamburg-Berlin.
Shen, Q., Wang, Y., Wang, X., Liu, X., Zhang, X., Zhang, S., 2019. Comparing interpolation methods to predict soil total phosphorus in the Mollisol area of Northeast China. Catena 174: 59-72.
Shi, W., Liu, J., Du, Z., Song, Y., Chen, C., Yue, T., 2009. Surface modelling of soil pH. Geoderma 150(1-2): 113-119.
Srivastava, A.K., Singh, S., 2009. Citrus decline: Soil fertility and plant nutrition. Journal of Plant Nutrition 32(2): 197-245.
Soil Survey Staff, 1951. Soil survey manual. Agricultural Research Administration, United States Department of Agriculture, Agricultural Handbook No.18, Washington, USA. 503p.
Tsegaye, T., Hill, R.L., 1998. Intensive tillage effects on spatial variability of soil test, plant growth and nutrient uptake measurement. Soil Science 163(2): 155-165.
Uysal, O., Polatöz, S., 2017. Dünyada ve Türkiye’de turunçgil üretimi ve dış ticareti. TÜRKTOB Dergisi 22: 6-11 [in Turkish].
Ülgen, N., Yurtsever, N., 1995. Türkiye gübre ve gübreleme rehberi. Toprak ve Gübre Araştırma Enstitüsü Yayınları, Genel Yayın No: 209, Teknik Yayınlar No: T.66, Ankara. [in Turkish].
Wilding L.P., 1985. Spatial Variability: It's documentation, accommodation and implication to soil surveys. In: Soil Spatial Variability. Nielsen, D.R., Bouma J. (Eds.). Pudoc, Wageningen, The Netherlands, pp: 166-194.
Wu, W., Liu, H.B., Dai, H.L., Li, W., Sun, P.S., 2011. The management and planning of citrus orchards at a regional scale with GIS. Precision Agriculture 12(1): 44-54.
Yayçep, 2010. Turunçgil Yetiştiriciliği. Televizyon Yoluyla Yaygın Çiftçi Eğitimi Projesi (YAYÇEP). Tarım ve Köyişleri Bakanlığı Yayın Dairesi Başkanlığı. Yayın No:54. Ankara. Available at [Access date: 17.03.2017] : http://www.katipogluziraat.com/kitap/turuncgil_cesitleri.pdf
Yeşilkanat, C., Kobya, Y., Taşkın, H., Çevik, U., 2014. Jeoistatistik tahmin ve simülasyon yöntemleri ile artvin ilindeki doğal kaynak suları için toplam alfa ve toplam betanın ara değer modellemesi ve haritalanması. Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Fen Bilimleri Dergisi 35(4): 11-35 [in Turkish].
Yuhendra, Sumantyo, J.T.,, Kuze, H., 2011. Performance analyzing of high resolution pan-sharpening techniques: Increasing image Quality for Classiﬁcation using supervised kernel support vector machine. Research Journal of Information Technology 8(1): 12-28.
Zabihi, H., Vogeler, I., Amin, Z.M., Gourabi, B.R., 2016. Mapping the sensitivity of citrus crops to freeze stress using a geographical information system in Ramsar, Iran. Weather and Climate Extremes 14: 17-23.
Zabihi, H., Alizadeh, M., Kibet Langat, P., Karami, M., Shahabi, H., Ahmad, A., Nor Said, M., Lee, S., 2019. GIS multi-criteria analysis by ordered weighted averaging (OWA): toward an integrated citrus management strategy. Sustainability 11(4): 1009.

Yayın Aralığı: Yılda 4 Sayı
Başlangıç: 2012
Yayıncı: Avrasya Toprak Bilimleri Dernekleri Federasyonu

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