What is it about?
utilisation of mathematicaland statistical functions to explain spatial variability of soil properties at microwatershed level.on this experimental field, ordinary kriging performed best for top soil and exponential method gave best results of interpolation with small residual sum of squares.A grid sampling technique with 97 soil samples at a distance of 250 X 250 m interval were collected and analysed for 11 soil parameters.Applied three interpolation techniques viz., ordinary kriging , inverse distance weighting and splines.
Featured Image
Why is it important?
It is important for site specific nutrient management and delineate biophysical constraints in attaining potential yields of major crops at microwatershed level.
Perspectives
The study is made on grids at distance of 250 X 250m and estimated 11 soil properties.Soils are real natural bodies that varies with landforms and have strong relation with land units. The soil properties under study are highly dynamics with crops and then level management. The grid surveys may not not consider these variations . This disavange may provoke to think twice for any nutrient management strategies at microwatershed level.statistical tools and its interpretation for soil - crop studies is still not fully explored and not justified by statistical means.
bhaskar PHANEENDRA
National Bureau of Soil Survey and Land Use Planning
Read the Original
This page is a summary of: Assessment of Spatial Variability of Soil Properties in Gopalapur Microwatershed, Gundlupet Taluk, Chamarajanagar District, Karnataka, India, Current Journal of Applied Science and Technology, March 2018, Sciencedomain International,
DOI: 10.9734/cjast/2018/38787.
You can read the full text:
Contributors
The following have contributed to this page
