Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture

Abstract

Precision farming needs management rules to apply spatially differentiated treatments in agricultural fields. Digital soil mapping (DSM) tools, for example apparent soil electrical conductivity, corrected to 25°C (EC 25 ), and digital elevation models, try to explain the spatial variation in soil type, soil properties (e.g. clay content), site and crop that are determined by landscape characteristics such as terrain, geology and geomorphology. We examined the use of EC 25 maps to delineate management zones, and identified the main factors affecting the spatial pattern of EC 25 at the regional scale in a study area in eastern Germany. Data of different types were compared: EC 25 maps for 11 fields, soil properties measured in the laboratory, terrain attributes, geological maps and the description of 75 soil profiles. We identified the factors that influence EC 25 in the presence of spatial autocorrelation and field-specific random effects with spatial linear mixed-effects models. The variation in EC 25 could be explained to a large degree (R 2 of up to 61%). Primarily, soil organic matter and CaCO 3 , and secondarily clay and the presence of gleyic horizons were significantly related to EC 25 . Terrain attributes, however, had no significant effect on EC 25 . The geological map unit showed a significant relationship to EC 25 , and it was possible to determine the most important soil properties affecting EC 25 by interpreting the geological maps. Including information on geology in precision agriculture could improve understanding of EC 25 maps. The EC 25 maps of fields should not be assumed to represent a map of clay content to form a basis for deriving management zones because other factors appeared to have a more important effect on EC 25 .

Distribuição espacial da condutividade elétrica do solo medida por indução eletromagnética e da produtividade de cana-de-açúcar

“…The same is true for the correlation between the textural properties and EC a -V and EC a -H. The occurrence of low linear correlation values between the textural properties and EC a -V and EC a -Hwas not expected, as the soil clay content is the property that interferes most with the values of EC a -V and EC a -H (McNeill, 1980;Lesch et al, 2005;Sudduth et al, 2005;Kühn et al, 2009;Siqueira et al, 2009). This fact is related to water surplus in the study area, represented by the water table very close to the surface at the time of harvesting sugar cane and sampling other soil properties under study.…”

“…According to McNeill (1980), Lesch et al (2005), Sudduth et al (2005), Kühn et al (2009) and Siqueira et al (2009), EC a is related to the water content in the soil, texture, organic matter content, size and distribution of pores, salinity, cation exchange capacity and electrolyte concentration in the soil solution.…”

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

“…These have been successfully applied by Hedley and Yule [21] and Daccache et al [8]. Readers are directed to [22,23] for a comprehensive overview of electrical conductivity mapping.…”

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

“…The application of geospatial measurements of EC a combined with the use of global navigation satellite systems (GNSS) and geographical information systems (GIS) is one of the most reliable techniques to characterize the spatial pattern of soil properties within fields [2,5–9]. As well as providing a correlation with soil properties, soil electrical conductivity mapping can also be used for delineating management zones and soil boundaries [2,10]. …”