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 Establishing management zones using soil electrical conductivity and other soil properties by the fuzzy clustering technique

2008 ◽  
Vol 65 (6) ◽  
pp. 567-573 ◽  
Author(s):  
José Paulo Molin ◽  
Cesar Nunes de Castro
Keyword(s):  
Electrical Conductivity ◽  
Soil Fertility ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Principal Component ◽  
Site Specific ◽  
Management Zones ◽  
Physical Attributes ◽  
Definition Of ◽  
Specific Management

The design of site-specific management zones that can successfully define uniform regions of soil fertility attributes that are of importance to crop growth is one of the most challenging steps in precision agriculture. One important method of so proceeding is based solely on crop yield stability using information from yield maps; however, it is possible to accomplish this using soil information. In this study the soil was sampled for electrical conductivity and eleven other soil properties, aiming to define uniform site-specific management zones in relation to these variables. Principal component analysis was used to group variables and fuzzy logic classification was used for clustering the transformed variables. The importance of electrical conductivity in this process was evaluated based on its correlation with soil fertility and physical attributes. The results confirmed the utility of electrical conductivity in the definition of management zones and the feasibility of the proposed method.

scholarly journals Site-Specific Management Zones Based on Soil Electrical Conductivity in a Semiarid Cropping System

2003 ◽  
Vol 95 (2) ◽  
pp. 303 ◽  
Author(s):  
Cinthia K. Johnson ◽  
David A. Mortensen ◽  
Brian J. Wienhold ◽  
John F. Shanahan ◽  
John W. Doran
Keyword(s):  
Electrical Conductivity ◽  
Cropping System ◽  
Soil Electrical Conductivity ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management

Delineation of site-specific management zones based on soil properties for a hillside field in central China

2012 ◽  
Vol 58 (10) ◽  
pp. 1075-1090 ◽  
Author(s):  
Hou-Long Jiang ◽  
Guo-Shun Liu ◽  
Shu-Duan Liu ◽  
En-Hua Li ◽  
Rui Wang ◽  
...  
Keyword(s):  
Soil Properties ◽  
Central China ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management

Determination of site-specific management zones using soil physico-chemical properties and crop yields in coastal reclaimed farmland

Geoderma ◽  
2014 ◽  
Vol 232-234 ◽  
pp. 381-393 ◽  
Author(s):  
Rong-Jiang Yao ◽  
Jing-Song Yang ◽  
Tong-Juan Zhang ◽  
Peng Gao ◽  
Xiang-Ping Wang ◽  
...  
Keyword(s):  
Crop Yields ◽  
Chemical Properties ◽  
Site Specific ◽  
Management Zones ◽  
Physico Chemical ◽  
Specific Management

scholarly journals Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

2015 ◽  
Vol 13 (4) ◽  
pp. e1103 ◽  
Author(s):  
Nahuel R. Peralta ◽  
Pablo L. Cicore ◽  
Maria A. Marino ◽  
Jose R. Marques da Silva ◽  
Jose L. Costa
Keyword(s):  
Electrical Conductivity ◽  
Regression Analysis ◽  
Soil Properties ◽  
Principal Components ◽  
Latent Variables ◽  
Stepwise Regression ◽  
Livestock Production ◽  
Site Specific ◽  
Support Tool ◽  
Negatively Associated

<p>The spatial variability in soils used for livestock production (<em>i.e. </em>Natraquoll and Natraqualf) at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa), a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM) content, pH, the saturation extract electrical conductivity (EC<sub>ext</sub>), available phosphorous (P), and anaerobically incubated Nitrogen (Nan). Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA), and stepwise regression. Principal components (PC) and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and EC<sub>ext</sub> exhibited a high correlation with ECa (<em>R</em><sup>2</sup>=0.76; 0.70 and 0.65, respectively). Whereas P and Nan showed a lower correlation (<em>R</em><sup>2</sup>=0.54 and 0.11 respectively). The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, EC<sub>ext</sub>, pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors&gt;0.4). Results showed that ECa is associated with the spatial distribution of some important<strong> </strong>soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use.</p>

scholarly journals Site-Specific Management Zones Based on Soil Electrical Conductivity in a Semiarid Cropping System

2003 ◽  
Vol 95 (2) ◽  
pp. 303-315 ◽  
Author(s):  
Cinthia K. Johnson ◽  
David A. Mortensen ◽  
Brian J. Wienhold ◽  
John F. Shanahan ◽  
John W. Doran
Keyword(s):  
Electrical Conductivity ◽  
Cropping System ◽  
Soil Electrical Conductivity ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management

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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