Performance Evaluation of TEROS 10 Sensor in Diverse Substrates and Soils of Different Electrical Conductivity Using Low-Cost Microcontroller Settings

Athanasios Fragkos, Dimitrios Loukatos, Georgios Kargas () and Konstantinos G. Arvanitis
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Athanasios Fragkos: Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece
Dimitrios Loukatos: Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece
Georgios Kargas: Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece
Konstantinos G. Arvanitis: Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece

Land, 2025, vol. 14, issue 2, 1-19

Abstract: This study sheds light on the performance of the common high-precision electromagnetic sensor TEROS 10 to estimate volumetric soil water content (θ) from dry to saturation across three different substrates, six different soil types having three different levels of electrical conductivity of soil solutions (EC w ), and in liquids with increasing salinity level under laboratory conditions, by using low-cost but accurate experimental IoT hardware arrangements. This performance was evaluated using statistical analysis metrics such as Root Mean Square Error (RMSE). It was found that TEROS 10 performance did not conform to the manufacturer’s specifications throughout the full scale range, although in some cases good water content estimation was provided. Some inconsistencies were identified by applying the manufacturer’s calibration equations, and thus recommendations for improvements are provided, aiming to enhance the sensor’s overall performance. TEROS 10 performance across all six soils and three substrates was improved on average from an RMSE of 0.052 and 0.078 cm 3 cm −3 , respectively, by using factory-derived calibration, to 0.031 and 0.031 cm 3 cm −3 by using the multipoint calibration method (CAL). Furthermore, a linear calibration formula, using Raw output as the predictor variable, was tested and resulted in an RMSE of 0.026 and 0.046 cm 3 cm −3 for soils and substrates, respectively.

Keywords: TEROS 10; electrical conductivity; apparent dielectric permittivity; soil moisture; calibration; microcontroller-based measurements; resource preservation; precision agriculture (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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