Computational Intelligence Application in Modeling Seismic Record and Soil Test Data at a Specified Area

2015 ◽  
Author(s):  
Tienfuan Kerh ◽  
Yu-Hsiang Su ◽  
Ayman Mosallam
Keyword(s):  
Test Data ◽  
Computational Intelligence ◽  
Soil Test ◽  
Seismic Record ◽  
Intelligence Application

scholarly journals Trends in some soil test data over a 14‐year period in New Zealand

2004 ◽  
Vol 47 (2) ◽  
pp. 155-166 ◽  
Author(s):  
D. M. Wheeler ◽  
G. P. Sparling ◽  
A. H. C. Roberts
Keyword(s):  
New Zealand ◽  
Test Data ◽  
Soil Test

scholarly journals Factor analysis for soil test data: a methodological approach in environment friendly soil fertility management

2007 ◽  
Vol 8 ◽  
pp. 8-19 ◽  
Author(s):  
Hari Dahal
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Soil Fertility ◽  
Test Data ◽  
Methodological Approach ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Test ◽  
Soil Fertility Management ◽  
Fertility Management

Soil test data were used in factor analysis employing the Principal Component Analysis technique for the reduction and summarization of soil variables. Principal component analysis was found to be highly suggestive in analyzing soil test data on which a rational fertilizer nutrients recommendation can be made for a sustainable soil fertility management reign. The Journal of AGRICULTURE AND ENVIRONMENT Vol. 8, 2007, pp. 8-19

COMPUTER MAPPING OF ALBERTA SOIL TEST DATA

1970 ◽  
Vol 50 (1) ◽  
pp. 1-7 ◽  
Author(s):  
D. R. CAMERON ◽  
J. A. TOOGOOD
Keyword(s):  
Test Data ◽  
Moving Average ◽  
Mapping Function ◽  
Available Phosphorus ◽  
Soil Test ◽  
Nitrogen Levels ◽  
Ph Values ◽  
Soil Zone ◽  
Weighted Moving Average ◽  
Phosphorus Levels

A circular mapping function based on the principle of a weighted moving average was applied in a computer program to the available Alberta soil test data, and nutrient levels of soils in the province were plotted and contoured. The finished maps displayed clearly marked trends. Variation in nitrate-nitrogen levels for samples from fallow and cropped land was readily seen, but correlation with soil zone was not well marked. Available phosphorus levels were relatively higher on the Solonetzic soils in central Alberta. Exchangeable potassium levels appeared to be closely related to the soil zones of Alberta. The mapped pH values presented the least variable picture. The electronic computer was essential for the mapping of data as reported in this study, and future applications of the computer to other soil data appear to be unlimited.

Technical note on the determination of tangent stiffness parameters from soil test data

1986 ◽  
Vol 2 (3) ◽  
pp. 131-140 ◽  
Author(s):  
J.H. Atkinson ◽  
D. Richardson ◽  
R.I. Woods
Keyword(s):  
Test Data ◽  
Technical Note ◽  
Soil Test ◽  
Tangent Stiffness

scholarly journals Fertilizer Prescriptions under STCR-IPNS for Rice-Rice Cropping Sequence on An Inceptisol (Typic Ustropept)

2019 ◽  
Author(s):  
U Bagavathi Ammal ◽  
K Coumaravel ◽  
R Sankar ◽  
Pradip Dey
Keyword(s):  
Nutrient Uptake ◽  
Test Data ◽  
Soil Test ◽  
Fertilizer N ◽  
Crop Response ◽  
Npk Fertilizers ◽  
Cropping Sequence ◽  
Target Yield ◽  
Basic Parameters ◽  
Data Yield

To develop fertilizer prescription equations based on soil test crop response (STCR) approach for rice-rice cropping sequence, trials were conducted at farmer’s field in Karikalampakkam village, U.T. of Puducherry, during 2015-16. Soil test data, yield and nutrient uptake by successive crops were recorded to calculate four basic parameters viz. nutrient required to produce one quintal of rice, contribution of nutrients from fertilizers, contribution of nutrients from soil and contribution of nutrients from FYM used in developing STCR based fertilizer prescription equations. The per cent nutrient contribution of nutrients from soil (CS), fertilizer ( CF) and FYM (CFYM) were found to be 19.15, 45.90 and 23.27 for N, 12.13,40.16 and 26.98 for P2O5 and 13.76, 79.64 and 41.07 for K2O respectively for rice cv. White ponni. The same for the rice cv.ADT 45 were 13.48, 40.46 and 34.26 for N, 15.81, 44.64 and 19.89 for P2O5 and 10.48, 58.64 and 41.51 for K2O respectively. Based on fertilizer prescription equations and nomograms formulated for a range of soil test values and desired yield target for the cropping sequence. It was revealed that under the treatment NPK + FYM @ 12.5 t ha- 1 , 47, 29 and 34 kg ha- 1 for rice cv.White ponni and 41 , 22 and 27 kg ha- 1 for rice cv.ADT 45 of fertilizer N , P2O5 and K2O, respectively could be saved for attaining target yield of 70 q ha- 1 compared to NPK fertilizers alone.

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