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

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 m 3 m −3 and a bias of <0.001 m 3 m −3 along with a strong correlation ( R = 0.90). Conversely, soil-specific calibration for mineral soils yielded a lower RMSE of 0.031 m 3 m −3 for loam soil and 0.034 m 3 m −3 for sandy loam soil. In the context of forest organic soil, the LCSM sensor exhibited a higher RMSE of 0.078 m 3 m −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.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-05-23
DOI
https://doi.org/10.3389/fenvs.2025.1590662
Citations
8
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
6.39

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

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8 citations
Frontiers in Environmental Science
Soil Moisture and Remote Sensing
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article

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

Aditya Prasad Kanungo, Michael H. Cosh, N. K. NAGPAL, Younsuk Dong, Gurjeet Singh, Narendra N. Das, Siddhesh Mane
article en
8 citations

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 m 3 m −3 and a bias of <0.001 m 3 m −3 along with a strong correlation ( R = 0.90). Conversely, soil-specific calibration for mineral soils yielded a lower RMSE of 0.031 m 3 m −3 for loam soil and 0.034 m 3 m −3 for sandy loam soil. In the context of forest organic soil, the LCSM sensor exhibited a higher RMSE of 0.078 m 3 m −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.

Frontiers in Environmental ScienceVol. 13
Agricultural Research Service (US), Jet Propulsion Laboratory (US), Michigan State University (US)
National Aeronautics and Space Administration, Michigan State University, Nuclear Safety and Security Commission, College of Engineering, Michigan State University
Openalex Percentile: Top 3%
Soil Moisture and Remote Sensing
6.39
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