scholarly journals Spatial and Temporal Patterns of Apparent Electrical Conductivity: DUALEM vs. Veris Sensors for Monitoring Soil Properties

Sensors ◽  
2014 ◽  
Vol 14 (6) ◽  
pp. 10024-10041 ◽  
Author(s):  
João Serrano ◽  
Shakib Shahidian ◽  
José Silva
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Temporal Patterns ◽  
Spatial And Temporal Patterns ◽  
Apparent Electrical Conductivity

Apparent Electrical Conductivity, Soil Properties and Spatial Covariance in the U.S. Southern High Plains

2005 ◽  
Vol 6 (3) ◽  
pp. 297-311 ◽  
Author(s):  
K. F. Bronson ◽  
J. D. Booker ◽  
S. J. Officer ◽  
R. J. Lascano ◽  
S. J. Maas ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
High Plains ◽  
Spatial Covariance ◽  
Southern High Plains ◽  
Apparent Electrical Conductivity ◽  
The U.S

Relating apparent electrical conductivity to soil properties across the north-central USA

2005 ◽  
Vol 46 (1-3) ◽  
pp. 263-283 ◽  
Author(s):  
K.A. Sudduth ◽  
N.R. Kitchen ◽  
W.J. Wiebold ◽  
W.D. Batchelor ◽  
G.A. Bollero ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
North Central ◽  
The North ◽  
Apparent Electrical Conductivity ◽  
Central Usa

Delineation of management zones with measurements of soil apparent electrical conductivity in the southeastern pampas

2013 ◽  
Vol 93 (2) ◽  
pp. 205-218 ◽  
Author(s):  
Nahuel Raúl Peralta ◽  
José Luis Costa ◽  
Mónica Balzarini ◽  
Hernán Angelini
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Stepwise Regression ◽  
Clay Soil ◽  
Crop Yields ◽  
Management Strategies ◽  
Site Specific ◽  
Management Zones ◽  
Apparent Electrical Conductivity ◽  
Specific Management

Peralta, N. R., Costa, J. L., Balzarini, M. and Angelini, H. 2013. Delineation of management zones with measurements of soil apparent electrical conductivity in the southeastern pampas. Can. J. Soil Sci. 93: 205–218. Site-specific management demands the identification of subfield regions with homogeneous characteristics (management zones). However, determination of subfield areas is difficult because of complex correlations and spatial variability of soil properties responsible for variations in crop yields within the field. We evaluated whether apparent electrical conductivity (ECa) is a potential estimator of soil properties, and a tool for the delimitation of homogeneous zones. ECamapping of a total of 647 ha was performed in four sites of Argentinean pampas, with two fields per site composed of several soil series. Soil properties and ECawere analyzed using principal components (PC)–stepwise regression and ANOVA. The PC–stepwise regression showed that clay, soil organic matter (SOM), cation exchange capacity (CEC) and soil gravimetric water content (θg) are key loading factors, for explaining the ECa(R2≥0.50). In contrast, silt, sand, extract electrical conductivity (ECext), pH values and [Formula: see text]-N content were not able to explain the ECa. The ANOVA showed that ECameasurements successfully delimited three homogeneous soil zones associated with spatial distribution of clay, soil moisture, CEC, SOM content and pH. These results suggest that field-scale ECamaps have the potential to design sampling zones to implement site-specific management strategies.

scholarly journals Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

2014 ◽  
Vol 34 (6) ◽  
pp. 1224-1233 ◽  
Author(s):  
Domingos S. M. Valente ◽  
Daniel M. de Queiroz ◽  
Francisco de A. de C. Pinto ◽  
Fábio L. Santos ◽  
Nerilson T. Santos
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Chemical Properties ◽  
Coffee Production ◽  
Management Zones ◽  
Apparent Electrical Conductivity ◽  
The Relationship ◽  
Dense Sampling

Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

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