Real time and accurate measurement of sub-surface soil moisture and nutrients is critical for agricultural and environmental studies. This paper presents a novel on-board solution for a robust, accurate and self-calibrating soil moisture and nutrient sensor with inbuilt wireless transmission and reception capability that makes it ideally suited to act as a node in a network spread over a large area. The sensor works on the principle of soil impedance measurement by comparing the amplitude and phase of signals incident on and reflected from the soil in proximity of the sensor. Accuracy of measurements is enhanced by considering a distributed transmission line model for the on-board connections. Presence of an inbuilt self-calibrating mechanism which operates on the standard short-open-load (SOL) technique makes the sensor independent of inaccuracies that may occur due to variations in temperature and surroundings. Moreover, to minimize errors, the parasitic impedances of the board are taken into account in the measurements. Measurements of both real and imaginary parts of soil impedance at multiple frequencies gives the sensor an ability to detect variations in ionic concentrations other than soil moisture content. A switch-controlled multiple power mode transmission and reception is provided to support highly energy efficient medium access control. 1
This paper presents a dielectric mixture model based approach for in-situ detection of soil-nitrates in real time. The dielectric constant of a material determines the impedance across a pair of electrodes immersed in that medium. We make accurate measurements on soil impedance over multiple frequencies using an in-situ soil-sensor we have designed. The impedance values are then used to determine the effective permittivity of the soil-bulk, which is then used to determine the concentration of individual components like soil, air, water and nutrients, e.g., nitrates using the data from measurements at multiple frequencies, and solving mixing models that involves component concentration as solution variables. The method shows good accuracy in the frequency range 1-70 MHz and can determine nitrate solution with less than 12% error. By considering 3% bound water percentage and assuming snow-like dielectric nature of bound water, this error reduces to 10%. If a parametrized apparent permittivity is considered in the vicinity of constituent particles, this error further reduces to less than 9%. Accurate nitrate detection based on our on-board, real-time, in-situ soil moisture sensors can provide an accurate real-time soil nitrate sensor and has the potential to greatly enhance agricultural production and reduce the impacts to the environment.
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