Identifying Soil Properties that Influence Cotton Yield Using Soil Sampling Directed by Apparent Soil Electrical Conductivity

2003 ◽  
Vol 95 (2) ◽  
pp. 352-364 ◽  
Author(s):  
D. L. Corwin ◽  
S. M. Lesch ◽  
P. J. Shouse ◽  
R. Soppe ◽  
J. E. Ayars
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Soil Sampling ◽  
Soil Electrical Conductivity ◽  
Cotton Yield

scholarly journals Using Multivariate Geostatistics to Assess Patterns of Spatial Dependence of Apparent Soil Electrical Conductivity and Selected Soil Properties

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Glécio Machado Siqueira ◽  
Jorge Dafonte Dafonte ◽  
Montserrat Valcárcel Armesto ◽  
Ênio Farias França e Silva
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Clay Content ◽  
Data Sets ◽  
Soil Electrical Conductivity ◽  
Multivariate Geostatistics ◽  
Northwestern Spain

The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECadata sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0–0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECaand gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECaand clay content (ranging from 0.197 to 0.495, when different ECarecording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECadata sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECaas secondary variable with respect to the use of ordinary kriging.

Soybean Root Distribution Related to Claypan Soil Properties and Apparent Soil Electrical Conductivity

Crop Science ◽  
2007 ◽  
Vol 47 (4) ◽  
pp. 1498-1509 ◽  
Author(s):  
D. Brenton Myers ◽  
Newell R. Kitchen ◽  
Kenneth A. Sudduth ◽  
Robert E. Sharp ◽  
Randall J. Miles
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Root Distribution ◽  
Soil Electrical Conductivity ◽  
Soybean Root ◽  
Claypan Soil

Development and Testing of a Low-Cost Portable Apparent Soil Electrical Conductivity Sensor Using a Beaglebone Black

2020 ◽  
Vol 36 (3) ◽  
pp. 341-355
Author(s):  
Daniel M. Queiroz ◽  
Emanoel D. T. S. Sousa ◽  
Won Suk Lee ◽  
John K. Schueller
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Low Cost ◽  
Satellite System ◽  
Mountainous Area ◽  
Soil Electrical Conductivity ◽  
Resistivity Method ◽  
Conductivity Sensor ◽  
Global Navigation Satellite

Abstract.The adoption of apparent soil electrical conductivity (soil ECa) sensors has increased in precision agricultural systems, especially in systems pulled by vehicles. This work developed a portable soil sensor for measuring soil ECa that could be used without vehicles in mountainous areas and small farms. The developed system was based on the electrical resistivity method. The system measured the electrical conductivity by applying a square wave signal at frequencies defined by the user. The acquired data were georeferenced using a low-cost global navigation satellite system (GNSS) receiver. The sensor system was developed using a BeagleBone Black, a low-cost single-board computer. A user interface was developed in C++, and a touch screen with a resolution of 800×480 pixels was used to display the results. This interface performed statistical analysis, and the results were used to guide the user to identify more field locations to be sampled to increase mapping accuracy. The system was tested in a coffee plantation located in a mountainous area and in a sugarcane plantation in Minas Gerais, Brazil. The system worked well in mapping the soil ECa. The apparent soil electrical conductivities measured using frequencies of 10, 20, 30, and 40 Hz were highly correlated. In the sugarcane field that had more variation in soil texture, a greater number of soil properties presented a significant correlation with the soil ECa. Keywords: Electrical conductivity, Geostatistics, Precision agriculture, Soil properties, Soil sensing, Spatial variability.

Inversion of soil electrical conductivity data to estimate layered soil properties

2017 ◽  
Vol 8 (2) ◽  
pp. 433-438 ◽  
Author(s):  
K. A. Sudduth ◽  
N. R. Kitchen ◽  
S. T. Drummond
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Initial Conditions ◽  
Salt Content ◽  
Clay Content ◽  
Depth Range ◽  
Soil Electrical Conductivity ◽  
Conductivity Data ◽  
Linear Relationships ◽  
Using Data

Bulk apparent soil electrical conductivity (ECa) sensors respond to multiple soil properties, including clay content, water content, and salt content (i.e. salinity). They provide a single sensor value for an entire soil profile down to a sensor-dependent measurement depth, weighted by a nonlinear response function. Because of this, it is generally difficult to elucidate strong relationships between ECa and the measured properties of individual soil layers. This research investigated inversion of the equations that govern the ECa-depth response relationship to reconstruct the soil conductivity in profile layers using data collected in multiple fields in the Midwest US. Layer conductivities obtained by inversion were first validated by comparison with true conductivities measured as a function of depth with an ECa-sensing penetrometer. Then, the validated layer conductivities were related to laboratory- measured soil properties. Inversion worked well but sometimes required iterative adjustment of initial conditions and other input parameters to obtain best results. Strong linear relationships (r2≥0.76) were obtained between inversion-estimated and measured layer conductivity data in all cases, sometimes with a truncated depth range. Layer conductivity data was successfully used to estimate soil texture fractions in the two alluvial fields examined. This was not the case for a claypan soil field, where there appeared to be parameters other than texture strongly affecting the EC response. Further examination of this approach is warranted to potentially provide improved ways to estimate depth-variable soil properties using ECa.

Scale dependent variability of soil electrical conductivity by indirect measures of soil properties

2005 ◽  
Vol 42 (3-4) ◽  
pp. 339-351 ◽  
Author(s):  
Asfaw Bekele ◽  
Wayne H. Hudnall ◽  
Jerry J. Daigle ◽  
Jacqueline A. Prudente ◽  
Maurice Wolcott
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Soil Electrical Conductivity ◽  
Indirect Measures
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