AUTHOR=Mane Siddhesh , Singh Gurjeet , Das Narendra N. , Kanungo Anant , Nagpal Nishit , Cosh Michael , Dong Younsuk 

TITLE=Development of low-cost handheld soil moisture sensor for farmers and citizen scientists

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2025.1590662

DOI=10.3389/fenvs.2025.1590662

ISSN=2296-665X

ABSTRACT=In recent years, the emergence of sensor technologies has highlighted the key role of in situ soil moisture measurement in various hydrological, agricultural, and ecological applications. However, the widespread adoption of technology is hindered by the costs and accessibility of existing sensor devices. This study aims to bridge a significant research gap by designing an economical and user-friendly handheld device, a Low-Cost Soil Moisture (LCSM) sensor ensuring reliable in situ measurements. This study has two main objectives: developing the LCSM sensor and establishing robust calibrations to ensure accuracy. Calibration experiments were conducted to develop generalized and soil-specific calibrations for the LCSM sensor across various field sites, encompassing diverse soil types (mineral-rich and forest organic soil) and land cover conditions. A total of 408 soil samples were collected from 83 locations (70 mineral soil sites- 301 samples; 13 organic soil sites- 107 samples) for the LCSM sensor calibration. All samples were collected from the same general fields during sampling period with similar experimental conditions. At each location, three LCSM readings were taken in a triangular configuration, and a gravimetric sample was extracted from the center using a coring method. The arithmetic average of the three sensor readings was used as the representative value for calibration against the corresponding gravimetric measurement, ensuring consistency and reliability. For generalized calibration in mineral soils, we observed an overall Root Mean Square Error (RMSE) of 0.035 m3m−3 and a bias of <0.001 m3m−3 along with a strong correlation (R = 0.90). Conversely, soil-specific calibration for mineral soils yielded a lower RMSE of 0.031 m3m−3 for loam soil and 0.034 m3m−3 for sandy loam soil. In the context of forest organic soil, the LCSM sensor exhibited a higher RMSE of 0.078 m3m−3 with a moderate correlation (R = 0.80). Furthermore, the comparison of calibrated LCSM sensor soil moisture readings with commercially available handheld soil moisture sensors (HydraProbe and ThetaProbe) demonstrated a strong agreement, with a high correlation (R > 0.90) and minimal difference in soil moisture measurements. These statistical findings highlight that the LCSM sensor measures soil moisture as accurately as commercially available sensors, strengthening its credibility and reliability for diverse conditions.