Dinesh*, Pankaj Kumar, Anil Duhan1, Pooja Rani and Anurag2
Department of Soil Science,1Department Agronomy2Department of Agrometeorology, CCS Haryana Agricultural University, Hisar 125004, India
Email: dineshtomarhau@gmail.com
Received-04.10.2022, Revised-16.10.2022, Accepted-29.10.2022
Abstract: The use of GIS to map the spatial variability of soil fertility gives crucial information for present and future usage. To assess the geographical distribution of nutrients, 14 surface soil samples from KVK Sadalpur (Haryana) were collected. The soils in the research area ranged in texture from loamy sand to sandy loam, and their pH ranged from neutral to alkaline (7.40-8.20). Organic carbon levels were determined to be low to medium, ranging from 0.10 to 0.53 percent. Limited CV values indicated low variation in organic carbon (OC).The amount of nitrogen (N) available was low, ranging from 91.00 to 126.00 kg ha-1 with a mean of 101.27 kg ha-1. The available potassium (K) levels in the soils ranged from 181.00 to 5.38.00 kg ha-1, with an average of 291.11kg ha-1. As evidenced by CV values, available K had a lot of variance i.e. 1272. The available phosphorous (P) in the soils of the study area ranged from 4.00 to 45.00kg ha-1, with an average value of 14.53 kg ha-1. Zinc, iron, copper, and manganese had mean values of 0.78, 2.95, 1.26, and 9.94 mg kg-1, respectively, and ranged from 0.09-1.72, 0.77-8.96, 0.16-0.28, and 3.20-6.87 mg kg-1. Low variance revealed that zinc (0.21), iron (2.95),copper (1.26), and manganese (4.94) had little fluctuation. The nutrient spatial variability maps provide insight into the area’s fertility state and will aid in the easy monitoring of precision fertiliser management..
Keywords: Spatial variability, Nitrogen, Phosphorus, Micronutrients, Mapping
References
Behera, S. K., Suresh, K., Rao, B. N., Mathur, R. K., Shukla, A. K., Manorama, K., Ramachandrudu K., Harinarayana, P. and Chandra Prakash, C. (2016). Spatial variability of some soil properties varies in oil palm (Elaeis guineensis Jacq.) plantations of west coastal area of India. Solid Earth, 7: 979-993.
Bhat, M. A., Grewal, M. S., Dinesh, Singh, I. and Grewal, K. S. (2017). Geoinformatics for quantifying salt affected soils in Gohana, Haryana using soil techniques. International Journal of Current Microbiology and Applied Sciences, 6(9):835-858.
Chatterjee, S., Santra, P., Majumdar, K., Ghosh, D. & Das, I. and Sanyal, S. K. (2015). Geostatistical approach for management of soil nutrients with special emphasis on different forms of potassium considering their spatial variation in intensive cropping system of West Bengal, India. Environmental Monitoring and Assessment, 187:183.DOI 10.1007/s10661-015-4414-9.
De-Datta, L. and Buresh, R.J. (1989). Integrated N management in irrigated rice. Advances in Agronomy, 10: 143-69.
Dhaliwal, S.S., Walia, S,S,, Walia, M.K. and Manchanda, J.S. (2013). Build up of macro, micro and secondary nutrients in site specific nutrient management experiment under rice-wheat system. International Journal of Science, Environment and Technology, 2(2): 236-244.
Dobermann, A. and Cassman, K. G. (2002). Plant nutrient management for enhanced productivity in intensive grain production systems of the United States and Asia. Plant and Soil, 247: 153–175.
Ferreira, V., Panagopoulos, T., Andrade, R., Guerrero, C. and Loures, L. (2015). Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed. Solid Earth, 6: 383-392, doi:10.5194/se-6-383-2015.
Levesque, R. (2007). SPSS Programming and Data Management: A Guide for SPSS and SAS Users. 4th Edn., SPSS Inc., Chicago.
Lindsay, W.L. and Norvell, W.A. (1978) Development of DTPA soil test for zinc, iron, manganese and copper. Soil Science Society of America Journal42:421-428.
Olsen, S.R., Cole, C.V., Watnabe, F.S. and Dean, L.A. (1954). Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. U.S. Department of Agriculture, Circular 939.
Osman, A. Z., El-Sherif, A. F. and Bassiouny, H. (1978). Manganese availability as affected by calcium carbonate levels. Journal of Plant Nutrition and Soil Science, 141:77-82.
Piper, C.S. (1950). Soil and Plant Analysis, Academi Press, New York.
Rao, P. S. C. and Wagenet, R. J. (1985). Spatial variability of pesticides in field soils: Methods for data analysis and consequences. Weed Science, 33(Suppl. 2):18-24.
Sarkar, D., Baruah, U., Gangopadhyay, S. K., Sahoo, A. K. and Velayutham, M. (2002) Characterization and classification of soils of Loktak catchment area of Manipur for sustainable land use planning. Journal of the Indian Society of Soil Science50(2):196-204.
Sharma, P., Shukla, M. K. and Mexal, J. G. (2011). Spatial Variability of Soil Properties in Agricultural Fields of Southern New Mexico. Soil Science, 176: 288-302.
Srinivasarao, C., Venkateswarlu, B., Lal, R., Singh, A. K., Kundu, S., Vittal, K. P. R., Patel, J. J. and Patel, M. M. (2014). Long-term manuring and fertilizer effects on depletion of soil organic carbon stocks under pearl millet-cluster bean-castor rotation in Western India, Land Degradation and Development, 25:173-183.
Tesfahunegn, G. B., Tamene, L. and Vlek, P. L. G. (2011). Catchmentscale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia, Soil and Tillage Research, 117:124-139.
Tripathi, R., Nayak, A. K., Shahid, M., Raja, R., Panda, B. B., Mohanty, S., Kumar, A., Lal, B., Priyanka Gautam, P. and Sahoo, R. N. (2015). Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging. Arabian Journal of Geosciences, 8:10693-10703.
Walkley, A. and Black, J. A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science37:29-38.