Comparison of Multi-Frequency and Multi-Coil Electromagnetic Induction (EMI) for Mapping Properties in Shallow Podsolic Soils

• Published in: Sensors
• Main Authors: Daniel Altdorff, Kamaleswaran Sadatcharam, Adrian Unc, Manokarajah Krishnapillai, Lakshman Galagedara
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2020
• Subjects: multi-coil EMI; multi-frequency EMI; comparative study; proximal soil sensing; noninvasive mapping; instrument selection; Chemical technology; TP1-1185; Canada; Newfoundland
• Online Access: https://doi.org/10.3390/s20082330; https://doaj.org/article/428473059d924129b886da7fb290af51

Electromagnetic induction (EMI) technique is an established method to measure the apparent electrical conductivity (EC a ) of soil as a proxy for its physicochemical properties. Multi-frequency (MF) and multi-coil (MC) are the two types of commercially available EMI sensors. Although the working principles are similar, their theoretical and effective depth of investigation and their resolution capacity can vary. Given the recent emphasis on non-invasive mapping of soil properties, the selection of the most appropriate instrument is critical to support robust relationships between EC a and the targeted properties. In this study, we compared the performance of MC and MF sensors by their ability to define relationships between EC a (i.e., MF–EC a and MC–EC a ) and shallow soil properties. Field experiments were conducted under wet and dry conditions on a silage-corn field in western Newfoundland, Canada. Relationships between temporally stable properties, such as texture and bulk density, and temporally variable properties, such as soil water content (SWC), cation exchange capacity (CEC) and pore water electrical conductivity (EC w ) were investigated. Results revealed significant ( p < 0.05) positive correlations of EC a to silt content, SWC and CEC for both sensors under dry conditions, higher correlated for MC–EC a . Under wet conditions, correlation of MF–EC a to temporally variable properties decreased, particularly to SWC, while the correlations to sand and silt increased. We concluded that the MF sensor is more sensitive to changes in SWC which influenced its ability to map temporally variable properties. The performance of the MC sensor was less affected by variable weather conditions, providing overall stronger correlations to both, temporally stable or variable soil properties for the tested Podzol and hence the more suitable sensor toward various precision agricultural practices.