Calibration and Validation of a Low-Cost Capacitive Moisture Sensor to Integrate the Automated Soil Moisture Monitoring System

Ekanayaka Achchillage Ayesha Dilrukshi Nagahage, Isura Sumeda Priyadarshana Nagahage and Takeshi Fujino
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Ekanayaka Achchillage Ayesha Dilrukshi Nagahage: Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama 338-8570, Japan
Isura Sumeda Priyadarshana Nagahage: Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama 338-8570, Japan
Takeshi Fujino: Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama 338-8570, Japan

Agriculture, 2019, vol. 9, issue 7, 1-10

Abstract: Readily available moisture in the root zone is very important for optimum plant growth. The available techniques to determine soil moisture content have practical limitations owing to their high cost, dependence on labor, and time consumption. We have developed a prototype for automated soil moisture monitoring using a low-cost capacitive soil moisture sensor (SKU:SEN0193) for data acquisition, connected to the internet. A soil-specific calibration was performed to integrate the sensor with the automated soil moisture monitoring system. The accuracy of the soil moisture measurements was compared with those of a gravimetric method and a well-established soil moisture sensor (SM-200, Delta-T Devices Ltd, Cambridge, UK). The root-mean-square error (RMSE) of the soil water contents obtained with the SKU:SEN0193 sensor function, the SM-200 manufacturer’s function, and the SM-200 soil-specific calibration function were 0.09, 0.07, and 0.06 cm 3 cm −3 , for samples in the dry to saturated range, and 0.05, 0.08, and 0.03 cm 3 cm −3 , for samples in the field capacity range. The repeatability of the measurements recorded with the developed calibration function support the potential use of the SKU:SEN0193 sensor to minimize the risk of soil moisture stress or excess water application.

Keywords: calibration function; capacitive soil moisture sensor; internet-based data acquisition; soil moisture content (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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