This paper will show the electronic architecture of a portable andvnon-invasive soi lmoisture system based on an open rectangular waveguide. The spectral information, measured in the range of 1.5–2.7 GHz, is elaborated on by an embedded predictive model, based on a partial least squares (PLS) regression tool, for the estimation of the soil moisture (%) in a real environment. The proposed system is composed of a waveguide, containing Tx and Rx antennas, and an electronic circuit driven by a microcontroller (MCU). It will be shown how the system provides a useful and fast estimation of moisture on a silty clay loam soil characterized by a moisture range of about 9% to 32% and a soil temperature ranging from about 8◦C and 18◦C. Using the PLS approach, the moisture content can be predicted with an R2 value of 0.892, a root mean square error (RMSE) of 1.0%, and a residual prediction deviation (RPD) of 4.3. The results prove that it is possible to make accurate and rapid moisture assessments without the use of invasive electrodes, as currently employed by state-of-the-art approaches.

A Non-Invasive Soil Moisture Sensing System Electronic Architecture: A Real Environment Assessment

Leonardo Franceschelli;Annachiara Berardinelli;Marco Crescentini;Eleonora Iaccheri;Marco Tartagni;Luigi Ragni
2020

Abstract

This paper will show the electronic architecture of a portable andvnon-invasive soi lmoisture system based on an open rectangular waveguide. The spectral information, measured in the range of 1.5–2.7 GHz, is elaborated on by an embedded predictive model, based on a partial least squares (PLS) regression tool, for the estimation of the soil moisture (%) in a real environment. The proposed system is composed of a waveguide, containing Tx and Rx antennas, and an electronic circuit driven by a microcontroller (MCU). It will be shown how the system provides a useful and fast estimation of moisture on a silty clay loam soil characterized by a moisture range of about 9% to 32% and a soil temperature ranging from about 8◦C and 18◦C. Using the PLS approach, the moisture content can be predicted with an R2 value of 0.892, a root mean square error (RMSE) of 1.0%, and a residual prediction deviation (RPD) of 4.3. The results prove that it is possible to make accurate and rapid moisture assessments without the use of invasive electrodes, as currently employed by state-of-the-art approaches.
Leonardo Franceschelli, Annachiara Berardinelli, Marco Crescentini, Eleonora Iaccheri, Marco Tartagni, Luigi Ragni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/777955
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