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Performance Evaluation of Soil Moisture Sensors in Coarse- and Fine-Textured Michigan Agricultural Soils

Author

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  • Younsuk Dong

    (Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA)

  • Steve Miller

    (Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA)

  • Lyndon Kelley

    (Michigan State University Extension, Michigan State University, East Lansing, MI 48824, USA)

Abstract

Soil moisture content is a critical parameter in understanding the water movement in soil. A soil moisture sensor is a tool that has been widely used for many years to measure soil moisture levels for their ability to provide nondestructive continuous data from multiple depths. The calibration of the sensor is important in the accuracy of the measurement. The factory-based calibration of the soil moisture sensors is generally developed under limited laboratory conditions, which are not always appropriate for field conditions. Thus, calibration and field validation of the soil moisture sensors for specific soils are needed. The laboratory experiment was conducted to evaluate the performance of factory-based calibrated soil moisture sensors. The performance of the soil moisture sensors was evaluated using Root Mean Squared Error (RMSE), Index of Agreement (IA), and Mean Bias Error (MBE). The result shows that the performance of the factory-based calibrated CS616 and EC5 did not meet all the statistical criteria except the CS616 sensor for sand. The correction equations are developed using the laboratory experiment. The validation of correction equations was evaluated in agricultural farmlands. Overall, the correction equations for CS616 and EC5 improved the accuracy in field conditions.

Suggested Citation

  • Younsuk Dong & Steve Miller & Lyndon Kelley, 2020. "Performance Evaluation of Soil Moisture Sensors in Coarse- and Fine-Textured Michigan Agricultural Soils," Agriculture, MDPI, vol. 10(12), pages 1-11, December.
    • Handle: RePEc:gam:jagris:v:10:y:2020:i:12:p:598-:d:455246
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    References listed on IDEAS

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    1. Luca Stevanato & Gabriele Baroni & Yafit Cohen & Cristiano Lino Fontana & Simone Gatto & Marcello Lunardon & Francesco Marinello & Sandra Moretto & Luca Morselli, 2019. "A Novel Cosmic-Ray Neutron Sensor for Soil Moisture Estimation over Large Areas," Agriculture, MDPI, vol. 9(9), pages 1-14, September.
    2. Cardenas-Lailhacar, B. & Dukes, M.D., 2010. "Precision of soil moisture sensor irrigation controllers under field conditions," Agricultural Water Management, Elsevier, vol. 97(5), pages 666-672, May.
    3. Varble, J.L. & Chávez, J.L., 2011. "Performance evaluation and calibration of soil water content and potential sensors for agricultural soils in eastern Colorado," Agricultural Water Management, Elsevier, vol. 101(1), pages 93-106.
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    Cited by:

    1. Datta, Sumon & Taghvaeian, Saleh, 2023. "Soil water sensors for irrigation scheduling in the United States: A systematic review of literature," Agricultural Water Management, Elsevier, vol. 278(C).

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