Development of a 3D-Printed Capacitive Sensor for Soil Water Content Estimation Using Nickel-Based Conductive Paint

Area of Science:

• Soil Science
• Environmental Monitoring
• Agricultural Engineering

Background:

• Accurate measurement of soil hydraulic parameters like volumetric water content (θ) is crucial for understanding hydrological, agricultural, and environmental processes.
• Capacitive sensors are increasingly favored for θ estimation due to their cost-effectiveness, robustness, and suitability for distributed and IoT-based monitoring.
• Existing methods require validation for new sensor technologies in diverse soil types.

Purpose of the Study:

• To develop and validate a low-cost capacitive sensor for estimating soil volumetric water content (θ).
• To utilize 3D printing and conductive paint for fabricating the sensor's capacitive electrode.
• To assess the sensor's performance against the established time-domain reflectometry (TDR) method.

Main Methods:

• A novel capacitive sensor was constructed using 3D-printed guides and nickel-based conductive paint.
• The sensor operated at a frequency of 60 MHz, measuring soil dielectric permittivity to infer θ.
• Calibration and validation were performed in laboratory settings using three distinct soil textures, comparing results with TDR measurements.

Main Results:

• The developed 3D-printed capacitive sensor demonstrated effective performance in estimating soil volumetric water content (θ).
• The sensor exhibited good reliability across a validation range of θ from 0 to 0.40 cm³/cm³.
• Performance was comparable to the reference TDR technique within the tested range.

Conclusions:

• The low-cost, 3D-printed capacitive sensor is a viable tool for accurate soil moisture estimation.
• This technology offers a promising solution for affordable and distributed soil water monitoring in various environmental and agricultural contexts.
• Further research can explore its application in different soil types and field conditions.