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Prof. Essmat Hassan nofal :: Publications:

Title:
Mapping and modeling soil characteristics to evaluate precision farming. Annals of Agric. Sci., Moshtohor. Vol. 48(4) (2010), 129-135 http://annagricmoshj.com
Authors: Esmat H. Noufal1, Alaa H. El-Nahry2, Haythum M.H. Salem1, and Wessam R. Zahra1.
Year: 2010
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: Local
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available
Abstract:

The study was carried out on the southern sector of Kalubia Governorate, Egypt, with an area of 89512.86 Feddans (93988.50 acres). The general objective of this study was to obtain accurate and timely information about the spatial variability and status of the soil characteristics using geographic information system (GIS) and remote sensing techniques. Collection of soil data were conducted by systematic sampling and a global positioning system (GPS) was used to precisely determine site locations of the samples. All samples were analyzed to determine selected soil properties of CEC, EC, organic matter, CaCO3, ESP and gypsum. Soil mapping variability was later analyzed using the geostatistics software. Kriging analysis was used to determine the value of each point in the area of study. A semi variogram was developed to describe the spatial relationship between the locations where the value of a soil property was estimated and characterized. Semi variogram analysis using geostatistics produced kriged map for CEC (6.09 – 57.14). Calcium carbonate, organic matter and gypsum contents were 2.35 - 45.38 g/kg, 1.80 - 12.07 g/kg, and 6.51-34.68 g/kg respectively. The EC value ranged between 0.83 and 44.51 dS/m. The ESP value ranged between 2.84 and 79.30. The study implies that site-specific or precision agriculture provides a useful management tool in the forecasting of crop yield and future market intelligence. Further research with respect to integrating the use of remotely sensed data with GPS and GIS to improve accuracy of systematic variability mapping in the studied area should be carried out.

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