Electrical conductivity mapping for precision farming

Abstract

Precision farming overcomes the paradigm of uniform field treatment by site‐specific data acquisition and treatment to cope with within‐field variability. Precision farming heavily relies on spatially dense information about soil and crop status. While it is often difficult and expensive to obtain precise soil information by traditional soil sampling and laboratory analysis some geophysical methods offer means to obtain subsidiary data in an efficient way. In particular, geoelectrical soil mapping has become widely accepted in precision farming. At present it is the most successful geophysical method providing the spatial distribution of relevant agronomic information that enables us to determine management zones for precision farming. Much work has been done to test the applicability of existing geoelectrical methods and to develop measurement systems applicable in the context of precision farming. Therefore, the aim of this paper was to introduce the basic ideas of precision farming, to discuss current precision farming applied geoelectrical methods and instruments and to give an overview about our corresponding activities during recent years. Different experiments were performed both in the laboratory and in the field to estimate first, electrical conductivity affecting factors, second, relationships between direct push and surface measurements, third, the seasonal stability of electrical conductivity patterns and fourth, the relationship between plant yield and electrical conductivity. From the results of these experiments, we concluded that soil texture is a very dominant factor in electrical conductivity mapping. Soil moisture affects both the level and the dynamic range of electrical conductivity readings. Nevertheless, electrical conductivity measurements can be principally performed independent of season. However, electrical conductivity field mapping does not produce reliable maps of spatial particle size distribution of soils, e.g., necessary to generate input parameters for water and nutrient transport models. The missing step to achieve this aim may be to develop multi‐sensor systems that allow adjusting the electrical conductivity measurement from the influence of different soil water contents.

<b>Moisture content effect in the relationship between apparent electrical conductivity and soil attributes

“…ECa was significantly correlated with the soil electrical conductivity of saturation extract and the total cation exchange capacity only on November 23 rd , 2010, which is in agreement with the results presented by Rhoades et al (1989). The results of this research reinforce the need to measure the soil moisture content when measuring ECa because discriminating the effects of variation in soil moisture content measurements on ECa is not possible with current technologies (LÜCK et al, 2009). Under conditions of higher soil moisture content, a lower correlation coefficient was observed between the soil moisture content and ECa, which indicates that under these conditions, the variability of the ECa is less influenced by the soil moisture content.…”

“…Thus, soil ECa represents a tool with great potential for precision agriculture (CORWIN et al, 2006, SHANE et al, 2008. However, according to LÜCK et al (2009), the spatial variability of the soil moisture content makes the measurement of ECa unreliable for predicting the variability of soil physical and chemical attributes. Ekwue and Bartholomew (2010) observed in their experiments a strong positive correlation between the ECa and the soil moisture content for three soil types evaluated in laboratory and field conditions.…”

“…Therefore, if at ECa data acquisition the soil moisture content presents a large spatial variability, the obtained ECa values may have a low correlation with the soil properties. According to Lück et al (2009), the soil moisture content affects both the level and the range of the variation of ECa, and to generate reliable maps, the authors suggest the use of a system of multiple sensors that can adjust the ECa measured with different levels of soil moisture. Rhoades et al (1989) suggested that ECa should be measured when the soil has a moisture content close to its field capacity.…”

“…For this purpose, the apparent soil electrical conductivity (ECa) has been widely accepted in precision agriculture. ECa is a geophysical method used to characterize the physical and chemical soil variability, and it has been used to delimit management zones (HOSSAIN et al, 2010;LÜCK et al, 2009).…”

Precision agriculture applied to soybean crop: Part II – Temporal stability of management zones

“…For generating management zones, it is first necessary to collect information closely related to crop yield, and the variables chosen to define these management zones should be quick and inexpensive to measure. For these reasons, apparent soil electrical conductivity (ECa) is an excellent potential variable for the delineation of management zones (Lück et al, 2009).…”